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diff --git a/_layouts/home.html b/_layouts/home.html
index f1c52cafc..93613d21d 100644
--- a/_layouts/home.html
+++ b/_layouts/home.html
@@ -48,11 +48,6 @@ -assi (selection1) (selection2) distance, lower-bound correction, upper-bound correction +assign (selection1) (selection2) distance, lower-bound correction, upper-bound correctionThe lower limit for the distance is calculated as: distance minus lower-bound correction @@ -332,7 +341,7 @@ Here would be an example of a distance restraint between the CB carbons of resid allowed distance range between 10 and 20Å:
-assi (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0 +assign (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0@@ -351,13 +360,13 @@ create now a distance restraint file suitable for use in HADDOCK.
-assi (segid A and resid 27 and name CA) (segid B and resid 18 and name CA) 23 23 0 -assi (segid A and resid 122 and name CA) (segid B and resid 125 and name CA) 23 23 0 -assi (segid A and resid 122 and name CA) (segid B and resid 128 and name CA) 23 23 0 -assi (segid A and resid 122 and name CA) (segid B and resid 127 and name CA) 23 23 0 -assi (segid A and resid 55 and name CA) (segid B and resid 169 and name CA) 26 26 0 -assi (segid A and resid 55 and name CA) (segid B and resid 179 and name CA) 26 26 0 -assi (segid A and resid 54 and name CA) (segid B and resid 179 and name CA) 26 26 0 +assign (segid A and resid 27 and name CA) (segid B and resid 18 and name CA) 23 23 0 +assign (segid A and resid 122 and name CA) (segid B and resid 125 and name CA) 23 23 0 +assign (segid A and resid 122 and name CA) (segid B and resid 128 and name CA) 23 23 0 +assign (segid A and resid 122 and name CA) (segid B and resid 127 and name CA) 23 23 0 +assign (segid A and resid 55 and name CA) (segid B and resid 169 and name CA) 26 26 0 +assign (segid A and resid 55 and name CA) (segid B and resid 179 and name CA) 26 26 0 +assign (segid A and resid 54 and name CA) (segid B and resid 179 and name CA) 26 26 0@@ -366,10 +375,11 @@ __Note:__ Under Linux (or OSX), this file could be generated automatically from file provided with the data for this tutorial by giving the following command (one line) in a terminal window:_ -cat restraints_filtered.txt | awk \'{if ( NF == 8 ) {print \"assi ( segid \",$1,\" and resid \",$2,\" and name \",$3,\" ) ( segid \",$4,\" and resid \",$5,\" and name \",$6,\" ) \",$8,$8,$7}}\' > restraints_filtered.tbl +cat restraints_filtered.txt | awk \'{if ( NF == 8 ) {print \"assign ( segid \",$1,\" and resid \",$2,\" and name \",$3,\" ) ( segid \",$4,\" and resid \",$5,\" and name \",$6,\" ) \",$8,$8,$7}}\' > restraints_filtered.tbl
++23,24,80,82,84,96,98,100,124,126,128 ++ +Let us visualize this interface on our unbound protein structure. For this start PyMol and load the PDB file of the unbound protein: + + +File menu -> Open -> select 2ZEW_clean.pdb + + +color white, all
+
++ HADDOCKscore = 1.0 * Evdw + 0.2 * Eelec + 1.0 * Edesol + 0.1 * Eair ++where Evdw is the intermolecular van der Waals energy, Eelec the intermolecular electrostatic energy, Edesol represents an empirical desolvation energy term adapted from Fernandez-Recio *et al.* J. Mol. Biol. 2004, and Eair the AIR energy. + +Consider the cluster scores and their standard deviations. +Is the top ranked cluster significantly better than the second one? What about the third cluster? + +In case the scores of various clusters are within standard deviation from each other, all should be considered as a valid solution for the docking. Ideally, some additional independent experimental information should be available to decide on the best solution. In this case we do have such a piece of information, namely the crystal structure of the complex. + +
+ 2ZEX_l_u.pdb: 1.071 + cluster1_1.pdb: 1.004 + cluster2_1.pdb: 0.968 + cluster10_1.pdb: 0.954 + ... ++
+ 
+
+
+ 
+ 
+ +B 520 CB C 135 CB 0.0 30.0 +B 520 CB C 138 CB 0.0 30.0 +B 520 CB C 141 CB 0.0 30.0 ++ +This is the format used by DisVis to represent the cross-links. Each cross-link definition consists of eight fields: + +* chainID of the 1st molecule +* residue number +* atom name +* chainID of the 2nd molecule +* residue number +* atom name +* lower distance limit +* upper distance limit + + +
+ 
+ 
+ From an analysis of the diagonal blocks we can identify the three wHTH domains, whose stucture is well predicted. When considering the off-diagonal blocks, the last domain of C34, wHTH3, seems to be the best defined with respect to C82. We will make use of this in our modelling strategy 2 in this tutorial. Since the orientation of the other domains are not well defined with respect with C82, we will treat them as separate entities during our modelling.
+
+ +assi (selection1) (selection2) distance, lower-bound correction, upper-bound correction ++ +The lower limit for the distance is calculated as: distance minus lower-bound correction +and the upper limit as: distance plus upper-bound correction + +The syntax for the selections can combine information about chainID - `segid` keyword -, residue number - `resid` +keyword -, atom name - `name` keyword. +Other keywords can be used in various combinations of OR and AND statements. Please refer for that to the [online CNS manual][link-cns]{:target="_blank"}. + +As an example, a distance restraint between the CB carbons of residues 10 and 200 in chains A and B with an +allowed distance range between 10 and 20Å can be defined as: + +
+assi (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0 ++ + +Can you think of a different way of defining the target distance and its lower and upper corrections while maintaining the same +allowed range? + + + +Under Linux (or OSX), this file can be generated automatically from a disvis restraint input file, e.g. `xlinks-C82-C34.disvis` +file provided with the data for this tutorial by giving the following command (one line) in a terminal window: + + +cat xlinks-C82-C34.disvis| awk '{if (NF == 8) {print "assi (segid ",$1," and resid ",$2," and name ",$3,") (segid ",$4," and resid ",$5," and name ",$6,") ",$8,$8,$7}}' > xlinks-C82-C34.disvis.tbl + + +A pre-generated CNS/HADDOCK formatted restraints file containing all cross-links is available in the `restraints` directory as: + + * `xlinks-all-core-C82-C34-wHTH1-wHTH2-C31-K91-K111.tbl` + +Inspect it (open it as a text file) + + +We used CB atoms to define the restraints in the disvis restraint file. Can you find those is this file? +Are there other atoms defined? What could those be? (Hint... MARTINI) + + +
Additional atoms are included in the distance restraints definitions: `BB`. These correspond to the backbone beads in the MARTINI representation.
+C34 consists of three winged-helix-turn-helix domains which could be docked separately in principle. These are connected by flexible linkers. +The defined restraints impose upper limits to the distance between the C- and N-terminal domains of the the domains. The upper limit was estimated as the number of missing segments/residues * 4.5Å (a typical distance observed in diffraction data for amyloid fibrils, representing a CA-CA distance in an extended conformation). +The same applies to C31 for which only two peptide fragments will be used to be able to make use of the cross-link restraints.
+There are clearly several regions where the two molecules are clashing.
+
+The fit in chimeraX has clearly removed some of the chain clashes, but there are still regions where the two molecules are clashing (especially considering we don't visualize the side-chains.
+
++ PolIII-core-C82-C34-wHTH3-chimera-fitted-merged.pdb: 0.9478 + PolIII-core-C82-C34-wHTH3-chimera-fitted-watref.pdb: 0.9427 + PolIII-core-C82-C34-wHTH3-chimera-fitted-CGref.pdb: 0.9517 ++
Both cross-links are violated, but especially the one between core residue 5394 and C82 residue 472 (~70Å!). +The EM fitting solution for C82+C34wHTH3 was well defined according to PowerFit. There seems thus to be discrepancy between the EM and MS data. +Another explanation could be conformational changes in the structures that are not accounted for in our modelling.
+
+ChimeraX view of the various clusters, superimposed on PolIII core
+The fit is better than in strategy 1, but thre is still one heavily violated cross-link between resid 472 of C82 and resid 5394 of the core. This might well be a false positive. It was not detected by DISVIS because the analysis is only performed for pair of domain and it can be satisfied, while when considering all molecules and all cross-links it can not.
+In the case of C34 wHTH1, all cross-links are satisfied.
+In the case of C34 wHTH2, all cross-links are satisfied.
+All cross-links are now stastified, including the one with C82 that was not in strategy 1.
+
+View of cluster2_4 in the the EM map (correlation 0.9526). C82 and C34 wHTH3 domain (coral) nicely fit into the density. The other two C34 domains (dark see green and burly wood are found in a region where some density starts to appear seen when playing with the density level, which might indicate some disorder / conformational variability.
+
](https://bioexcel.eu){:target="_blank"} Center of Excellence for Computational Biomolecular Research.
+
+[link-cns]: http://cns-online.org/v1.3/ "CNS online"
+[link-chimerax]: https://www.cgl.ucsf.edu/chimerax/ "UCSF ChimeraX"
+[link-disvis]: https://github.com/haddocking/disvis "DisVis GitHub repository"
+[link-disvis-web]: https://wenmr.science.uu.nl/disvis "DisVis web server"
+[link-disvis-submit]: https://wenmr.science.uu.nl/disvis/submit "DisVis submission"
+[link-disvis-register]: https://wenmr.science.uu.nl/auth/register "DisVis registration"
+
+[link-haddock]: https://bonvinlab.org/software/haddock2.2 "HADDOCK 2.2"
+[link-haddock-web]: https://wenmr.science.uu.nl/haddock2.4/ "HADDOCK 2.4 webserver"
+[link-haddock-easy]: https://alcazar.science.uu.nl/services/HADDOCK2.2/haddockserver-easy.html "HADDOCK2.2 webserver easy interface"
+[link-haddock-expert]: https://alcazar.science.uu.nl/services/HADDOCK2.2/haddockserver-expert.html "HADDOCK2.2 webserver expert interface"
+[link-haddock-register]: https://wenmr.science.uu.nl/auth/register/"HADDOCK web server registration"
+[link-molprobity]: http://molprobity.biochem.duke.edu "MolProbity"
+[link-powerfit]: https://github.com/haddocking/powerfit "PowerFit"
+[link-powerfit-web]: https://alcazar.science.uu.nl/services/POWERFIT/ "PowerFit web server"
+[link-powerfit-register]: https://wenmr.science.uu.nl/auth/register "PowerFit registration"
+[link-powerfit-submit]: https://alcazar.science.uu.nl/cgi/services/POWERFIT/powerfit/submit "PowerFit submission"
+[link-powerfit-help]: https://alcazar.science.uu.nl/cgi/services/POWERFIT/powerfit/help "PowerFit submission"
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diff --git a/education/HADDOCK24/XL-MS-oligomer/AlphaFold3Server-runs.zip b/education/HADDOCK24/XL-MS-oligomer/AlphaFold3Server-runs.zip
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diff --git a/education/HADDOCK24/XL-MS-oligomer/index.md b/education/HADDOCK24/XL-MS-oligomer/index.md
index 88c43ee96..f137465b7 100644
--- a/education/HADDOCK24/XL-MS-oligomer/index.md
+++ b/education/HADDOCK24/XL-MS-oligomer/index.md
@@ -13,16 +13,17 @@ This tutorial consists of the following sections:
-assi (selection1) (selection2) distance, lower-bound correction, upper-bound correction +assign (selection1) (selection2) distance, lower-bound correction, upper-bound correctionThe lower limit for the distance is calculated as: distance minus lower-bound correction @@ -317,7 +328,7 @@ E. g. a distance restraint between the CB carbons of residues 10 and 200 in chai allowed distance range between 10 and 20Å would be defined as follows:
-assi (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0 +assign (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0@@ -329,14 +340,14 @@ A HADDOCK-compatible distance restraint file based on the cross-links defined ab It contains the following distance restraints (8 in total):
-assi (segid A and resid 40 and name CA ) (not segid A and resid 252 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 90 and name CA ) (not segid A and resid 176 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 135 and name CA ) (not segid A and resid 158 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 161 and name CA ) (not segid A and resid 132 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 252 and name CA ) (not segid A and resid 40 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 176 and name CA ) (not segid A and resid 90 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 158 and name CA ) (not segid A and resid 135 and name CA ) 10.0 7.0 0.0 -assi (segid A and resid 132 and name CA ) (not segid A and resid 161 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 40 and name CA ) (not segid A and resid 252 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 90 and name CA ) (not segid A and resid 176 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 135 and name CA ) (not segid A and resid 158 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 161 and name CA ) (not segid A and resid 132 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 252 and name CA ) (not segid A and resid 40 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 176 and name CA ) (not segid A and resid 90 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 158 and name CA ) (not segid A and resid 135 and name CA ) 10.0 7.0 0.0 +assign (segid A and resid 132 and name CA ) (not segid A and resid 161 and name CA ) 10.0 7.0 0.0Since we might be docking various numbers of monomers - and we thus don't know to which monomer a cross-link should be defined, @@ -389,7 +400,7 @@ PDB structure to submit -> Browse and select *monomer-B.pdb* Segment ID to use during docking -> B -* **Step 4X:** Repeat Step3 as many times to complete the number of molecules you chose in Step2. For this unfold the **Third Molecule menu** and additional ones as needed. +* **Step 4':** Repeat Step4 as many times to complete the number of molecules you chose in Step2. For this unfold the **Third/Fourth/Fifth Molecule menu** and additional ones as needed. XX molecule: where is the structure provided? -> "I am submitting it" @@ -432,6 +443,7 @@ The protein sequence starts at residue 32 and ends at residue 254. Use those num Use this type of restraints -> switch on +Number of CX symmetry segment pairs -> 1 For the symmetry that matches your chosen oligomeric state (C2, C3, C4 or C5), unfold the first CX symmetry segment menu and enter the first and last residue numbers and specify the chainID for each monomer. @@ -451,6 +463,7 @@ Eair 3 -> 1.0
+QAFWKAVTAEFLAMLIFVLLSLGSTINWGGTEKPLPVDMVLISLCFGLSIATMVQCFGHISGGHINPAVTVAMVCTRKISIAKSVFYIAAQCLGAIIGAGILYLVTPPSVVGGLGVTMVHGNLTAGHGLLVELIITFQLVFTIFASCDSKRTDVTGSIALAIGFSVAIGHLFAINYTGASMNPARSFGPAVIMGNWENHWIYWVGPIIGAVLAGGLYEYVFCP ++* **Step 4:** Click on "Continue and preview job" +* **Step 5:** Job Name: X-mer. +* **Step 6:** Switch the seed button on and select a pseudo-random seed for your run. +* **Step 7:** Click on "Confirm and submit job" + +All your submitted jobs will be displayed in a table at the bottom of the page. +This recapitulates their status (running or succeeded), their name and the time they were created. +__Note__ that you can have multiple jobs running concurrently. This will allow you to try-out multiple oligomeric states simply by modifying the number of copies in __step 2__, and re-submitting. + + +Time to grab a cup of tea or a coffee! +And while waiting, try to answer the following questions: + + + How do you interpret AlphaFold's predictions? What are the predicted LDDT (pLDDT), PAE, PTM, iPTM? + + +_Tip_: Try to find information about the prediction confidence at [https://golgi.sandbox.google.com/faq#how-can-i-interpret-confidence-metrics-to-check-the-accuracy-of-structures](https://golgi.sandbox.google.com/faq#how-can-i-interpret-confidence-metrics-to-check-the-accuracy-of-structures) + +Pre-calculated AlphFold3 predictions are provided here. +The single zip archive contains the four different runs tested. +Each run consits of an archive containing information about the run and five predicted models (the naming indicates the rank). + +* [`AlphaFold3Server-runs.zip`](/education/HADDOCK24/XL-MS-oligomer/AlphaFold3Server-runs.zip) + - `fold_dimer.zip`: contains the dimer run results (copies = 2) + - `fold_trimer.zip`: contains the trimer run results (copies = 3) + - `fold_tetramer.zip`: contains the tetramer run results (copies = 4) + - `fold_pentamer.zip`: contains the pentamer run results (copies = 5) + + +### Analysis of the generated models + +Once the run is finished and the status reached succeeded, you can click on one of the table rows to go to the provided visualizing tool. + +On the top, best model metrics will be shown (ipTM and PTM), and in the visualizer, residues are colored based on their pLDDT values. + +Take time to look at the generated models and the arrangement of the various monomers. When submitting our prediction, we only defined the number of monomers, but not the symmetry. + + + Does AlphaFold3 generate symmetrical solutions? Compare results from different oligomeric states. + + +Consider the `iPTM` score (value between 0 and 1) of the various oligomeric states (assuming that you run the notebook with different oligomeric states). + + + Which oligomeric state results in the highest iPTM score? + + +
+Dimer: ipTM = 0.77, pTM = 0.86 +Trimer: ipTM = 0.83, pTM = 0.86 +Tetramer: ipTM = 0.90, pTM = 0.91 +Pentamer: ipTM = 0.74, pTM = 0.78 ++ +
-
-
-
-
-(haddock3)$ haddock3 -h
-usage: haddock3 [-h] [--restart RESTART] [--extend-run EXTEND_RUN] [--setup]
- [--log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}] [-v]
- recipe
-
-positional arguments:
- recipe The input recipe file path
-
-optional arguments:
- -h, --help show this help message and exit
- --restart RESTART Restart the run from a given step. Previous folders from the
- selected step onward will be deleted.
- --extend-run EXTEND_RUN
- Start a run from a run directory previously prepared with the
- `haddock3-copy` CLI. Provide the run directory created with
- `haddock3-copy` CLI.
- --setup Only setup the run, do not execute
- --log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
- -v, --version show version
-
-- ============================================================ - | | - | Crystallography & NMR System (CNS) | - | CNSsolve | - | | - ============================================================ - Version: 1.3 at patch level U - Status: Special UU release with Rg, paramagnetic - and Z-restraints (A. Bonvin, UU 2013) - ============================================================ - Written by: A.T.Brunger, P.D.Adams, G.M.Clore, W.L.DeLano, - P.Gros, R.W.Grosse-Kunstleve,J.-S.Jiang,J.M.Krahn, - J.Kuszewski, M.Nilges, N.S.Pannu, R.J.Read, - L.M.Rice, G.F.Schroeder, T.Simonson, G.L.Warren. - Copyright (c) 1997-2010 Yale University - ============================================================ - Running on machine: hostname unknown (Linux,64-bit) - Program started by: l00902 - Program started at: 16:34:22 on 06-Dec-2023 - ============================================================ - - FFT3C: Using FFTPACK4.1 - -CNSsolve> --
-assi (selection1) (selection2) distance, lower-bound correction, upper-bound correction -- -The lower limit for the distance is calculated as: distance minus lower-bound correction -and the upper limit as: distance plus upper-bound correction - -The syntax for the selections can combine information about: - -* chainID - `segid` keyword -* residue number - `resid` keyword -* atom name - `name` keyword. - -Other keywords can be used in various combinations of OR and AND statements. Please refer for that to the [online CNS manual][link-cns]{:target="_blank"}. - -E. g. a distance restraint between the CB carbons of residues 10 and 200 in chains A and B with an -allowed distance range between 10 and 20Å would be defined as follows: - -
-assi (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0 -- - -Can you think of a different way of defining the distance and lower and upper corrections while maintaining the same -allowed range? - - - -
-31,32,33,34,35,52,54,55,56,100,101,102,103,104,105,106,151,152,169,170,173,211,212,213,214,216 -- -The numbering corresponds to the numbering of the `4G6K_clean.pdb` PDB file. - -Let us visualize those onto the 3D structure. -For this start PyMOL and load `4G6K_clean.pdb` - - -File menu -> Open -> select 4G6K_clean.pdb - - -Alternatively, if PyMol is accessible from the command line simply type: - - -pymol 4G6K_clean.pdb - - -We will now highlight the predicted paratope. In PyMOL type the following commands: - - -color white, all - - -select paratope, (resi 31+32+33+34+35+52+54+55+56+100+101+102+103+104+105+106+151+152+169+170+173+211+212+213+214+216)
- 
--72,73,74,75,81,83,84,89,90,92,94,96,97,98,115,116,117 -- -We will now visualize the epitope on Interleukin-1β. For this start PyMOL and from the PyMOL File menu open the provided PDB file of the antigen. - - -File menu -> Open -> select 4I1B_clean.pdb - - - -color white, all - - -show surface - - -select epitope, (resi 72+73+74+75+81+83+84+89+90+92+94+96+97+98+115+116+117) - - -color red, epitope - - -Inspect the surface. - - -Do the identified residues form a well defined patch on the surface? - - -The answer to that question should be yes, but we can see some residues not colored that might also be involved in the binding - there are some white spots around/in the red surface. - -
- 
- -1 32 33 34 35 52 54 55 56 100 101 102 103 104 105 106 151 152 169 170 173 211 212 213 214 216 - -- -* For the antigen we will use the NMR-identified epitope as active and the surface neighbors as passive. The corresponding file can be found in the `restraints` directory as `antigen-NMR-epitope.act-pass`: - -
-72 73 74 75 81 83 84 89 90 92 94 96 97 98 115 116 117 -3 24 46 47 48 50 66 76 77 79 80 82 86 87 88 91 93 95 118 119 120 -- -Using those two files, we can generate the CNS-formatted AIR restraint files with the following command: - - -haddock3-restraints active_passive_to_ambig ./restraints/antibody-paratope.act-pass ./restraints/antigen-NMR-epitope.act-pass > ambig-paratope-NMR-epitope.tbl - - -This generates a file called `ambig-paratope-NMR-epitope.tbl` that contains the AIR -restraints. - - -Inspect the generated file and note how the ambiguous distances are defined. - - -
-assign (resi 31 and segid A) -( - (resi 72 and segid B) - or - (resi 73 and segid B) - or - (resi 74 and segid B) - or - (resi 75 and segid B) - or - (resi 81 and segid B) - or - (resi 83 and segid B) - or - (resi 84 and segid B) - or - (resi 89 and segid B) - or - (resi 90 and segid B) - or - (resi 92 and segid B) - or - (resi 94 and segid B) - or - (resi 96 and segid B) - or - (resi 97 and segid B) - or - (resi 98 and segid B) - or - (resi 115 and segid B) - or - (resi 116 and segid B) - or - (resi 117 and segid B) - or - (resi 3 and segid B) - or - (resi 24 and segid B) - or - (resi 46 and segid B) - or - (resi 47 and segid B) - or - (resi 48 and segid B) - or - (resi 50 and segid B) - or - (resi 66 and segid B) - or - (resi 76 and segid B) - or - (resi 77 and segid B) - or - (resi 79 and segid B) - or - (resi 80 and segid B) - or - (resi 82 and segid B) - or - (resi 86 and segid B) - or - (resi 87 and segid B) - or - (resi 88 and segid B) - or - (resi 91 and segid B) - or - (resi 93 and segid B) - or - (resi 95 and segid B) - or - (resi 118 and segid B) - or - (resi 119 and segid B) - or - (resi 120 and segid B) -) 2.0 2.0 0.0 -... --
- assign (segid A and resi 110 and name CA) (segid A and resi 132 and name CA) 47.578 0.0 0.0 - assign (segid A and resi 97 and name CA) (segid A and resi 204 and name CA) 33.405 0.0 0.0 -- -This file is also provided in the `restraints` directory. - - -
-model md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq cluster-id cluster-ranking model-cluster-ranking air angles bonds bsa cdih coup dani desolv dihe elec improper rdcs rg sym total vdw vean xpcs -../06_emref/emref_4.pdb - 1 -145.275 1.034 0.879 2.856 1.929 0.819 - - - 69.699 0.000 0.000 1976.860 0.000 0.000 0.000 6.775 0.000 -493.142 0.000 0.000 0.000 0.000 -483.835 -60.391 0.000 0.000 -../06_emref/emref_6.pdb - 2 -132.350 1.255 0.828 2.269 2.166 0.783 - - - 67.962 0.000 0.000 1882.240 0.000 0.000 0.000 11.799 0.000 -510.162 0.000 0.000 0.000 0.000 -491.112 -48.912 0.000 0.000 -../06_emref/emref_1.pdb - 3 -131.650 0.822 0.862 2.060 1.269 0.858 - - - 79.712 0.000 0.000 1879.870 0.000 0.000 0.000 -2.596 0.000 -487.314 0.000 0.000 0.000 0.000 -447.165 -39.562 0.000 0.000 -../06_emref/emref_2.pdb - 4 -129.551 1.296 0.776 2.308 2.364 0.760 - - - 129.685 0.000 0.000 1862.120 0.000 0.000 0.000 1.240 0.000 -508.711 0.000 0.000 0.000 0.000 -421.043 -42.018 0.000 0.000 -... -- -If clustering was performed prior to calling the `caprieval` module the `capri_ss.tsv` file will also contain information about to which cluster the model belongs to and its ranking within the cluster. - - -The relevant statistics are: - -* **score**: *the HADDOCK score (arbitrary units)* -* **irmsd**: *the interface RMSD, calculated over the interfaces the molecules* -* **fnat**: *the fraction of native contacts* -* **lrmsd**: *the ligand RMSD, calculated on the ligand after fitting on the receptor (1st component)* -* **ilrmsd**: *the interface-ligand RMSD, calculated over the interface of the ligand after fitting on the interface of the receptor (more relevant for small ligands for example)* -* **dockq**: *the DockQ score, which is a combination of irmsd, lrmsd and fnat and provides a continuous scale between 1 (exactly equal to reference) and 0* - -Various other terms are also reported including: - -* **bsa**: *the buried surface area in squared Angstromn* -* **elec**: *the intermolecular electrostatic energy* -* **vdw**: *the intermolecular van der Waals energy* -* **desolv**: *the desolvation energy* - - -The iRMSD, lRMSD and Fnat metrics are the ones used in the blind protein-protein prediction experiment [CAPRI](https://capri.ebi.ac.uk/){:target="_blank"} (Critical PRediction of Interactions). - -In CAPRI the quality of a model is defined as (for protein-protein complexes): - -* **acceptable model**: i-RMSD < 4Å or l-RMSD<10Å and Fnat > 0.1 (0.23 < DOCKQ < 0.49) -* **medium quality model**: i-RMSD < 2Å or l-RMSD<5Å and Fnat > 0.3 (0.49 < DOCKQ < 0.8) -* **high quality model**: i-RMSD < 1Å or l-RMSD<1Å and Fnat > 0.5 (DOCKQ > 0.8) - - -What is based on this CAPRI criterion the quality of the best model listed above (emref_6.pdb)? - - -In case the `caprieval` module is called after a clustering step an additional file will be present in the directory: `capri_clt.tsv`. -This file contains the cluster ranking and score statistics, averaged over the minimum number of models defined for clustering -(4 by default), with their corresponding standard deviations. E.g.: - -
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 1 13 - -134.706 6.188 1.102 0.190 0.836 0.039 2.373 0.294 0.805 0.037 86.764 25.183 1900.272 44.896 4.305 5.461 -499.832 9.836 -460.789 28.355 -47.721 8.079 1 -2 2 10 - -103.801 6.412 5.072 0.072 0.125 0.007 11.718 0.592 0.184 0.008 119.323 25.301 1602.258 76.499 8.380 2.269 -300.700 36.597 -245.350 36.102 -63.973 3.596 2 -3 3 9 - -96.625 5.281 9.931 0.292 0.069 0.012 19.389 0.457 0.084 0.005 163.724 58.987 1525.055 31.387 2.803 1.489 -367.539 27.148 -246.109 63.575 -42.293 5.960 3 -4 4 4 - -96.089 15.346 14.725 0.026 0.090 0.007 23.152 0.311 0.073 0.003 174.066 46.134 1793.750 120.512 3.950 1.692 -332.615 23.798 -209.472 70.181 -50.923 6.901 4 -- - -In this file you find the cluster rank, the cluster ID (which is related to the size of the cluster, 1 being always the largest cluster), the number of models (n) in the cluster and the corresponding statistics (averages + standard deviations). The corresponding cluster PDB files will be found in the processing `09_seletopclusts` directory. - -While these simple text file can be easily checked from the command line already, they might be cumbersome to read. For that reason we have developed a post-processing analysis that automatically generates html reports for all `caprieval` steps in the workflow. These are located in the respective `analysis/XX_caprieval` directories and can be viewed using your favorite web browser. - - - -
-
-
--============================================== -== run1/02_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 16 out of 50 -Total number of medium or better models: 12 out of 50 -Total number of high quality models: 0 out of 50 - -First acceptable model - rank: 4 i-RMSD: 1.229 Fnat: 0.707 DockQ: 0.744 -First medium model - rank: 4 i-RMSD: 1.229 Fnat: 0.707 DockQ: 0.744 -Best model - rank: 21 i-RMSD: 1.154 Fnat: 0.828 DockQ: 0.795 -============================================== -== run1/05_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 16 out of 50 -Total number of medium or better models: 12 out of 50 -Total number of high quality models: 2 out of 50 - -First acceptable model - rank: 1 i-RMSD: 0.778 Fnat: 0.897 DockQ: 0.877 -First medium model - rank: 1 i-RMSD: 0.778 Fnat: 0.897 DockQ: 0.877 -Best model - rank: 1 i-RMSD: 0.778 Fnat: 0.897 DockQ: 0.877 -============================================== -== run1/07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 16 out of 50 -Total number of medium or better models: 12 out of 50 -Total number of high quality models: 2 out of 50 - -First acceptable model - rank: 1 i-RMSD: 1.034 Fnat: 0.879 DockQ: 0.819 -First medium model - rank: 1 i-RMSD: 1.034 Fnat: 0.879 DockQ: 0.819 -Best model - rank: 3 i-RMSD: 0.822 Fnat: 0.862 DockQ: 0.858 -============================================== --
- In terms of iRMSD values we only observe very small differences in the best model. The fraction of native contacts and the DockQ scores are however improving much more after flexible refinement, but increases again slightly after final minimisation. All this will of course depend on how different are the bound and unbound conformations and the amount of data used to drive the docking process. In general, from our experience, the more and better data at hand, the larger the conformational changes that can be induced. -
-- This is not the case. The scoring function is not perfect, but does a reasonable job in ranking models of acceptable or better quality on top in this case. -
-Top-ranked model of the top cluster superimposed onto the reference crystal structure (in yellow)
-
- 
-- 4G6K_abb_clean RMSD = 0.428 Å - 4G6K_af2_clean RMSD = 0.765 Å --
- 4G6K_abb_clean RMSD = 0.330 Å - 4G6K_af2_clean RMSD = 0.675 Å - 4G6K_clean RMSD = 0.393 Å --
-============================================== -== run1/10_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 1 out of 4 -Total number of medium or better clusters: 1 out of 4 -Total number of high quality clusters: 0 out of 4 - -First acceptable cluster - rank: 1 i-RMSD: 1.102 Fnat: 0.836 DockQ: 0.805 -First medium cluster - rank: 1 i-RMSD: 1.102 Fnat: 0.836 DockQ: 0.805 -Best cluster - rank: 1 i-RMSD: 1.102 Fnat: 0.836 DockQ: 0.805 - -============================================== -== run1-abb/10_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 1 out of 5 -Total number of medium or better clusters: 1 out of 5 -Total number of high quality clusters: 0 out of 5 - -First acceptable cluster - rank: 1 i-RMSD: 1.103 Fnat: 0.832 DockQ: 0.797 -First medium cluster - rank: 1 i-RMSD: 1.103 Fnat: 0.832 DockQ: 0.797 -Best cluster - rank: 1 i-RMSD: 1.103 Fnat: 0.832 DockQ: 0.797 - -============================================== -== run1-af2/10_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 2 out of 5 -Total number of medium or better clusters: 0 out of 5 -Total number of high quality clusters: 0 out of 5 - -First acceptable cluster - rank: 1 i-RMSD: 2.956 Fnat: 0.375 DockQ: 0.413 -Best cluster - rank: 3 i-RMSD: 2.903 Fnat: 0.375 DockQ: 0.327 --
-============================================== -== run1/07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 16 out of 50 -Total number of medium or better models: 12 out of 50 -Total number of high quality models: 2 out of 50 - -First acceptable model - rank: 1 i-RMSD: 1.034 Fnat: 0.879 DockQ: 0.819 -First medium model - rank: 1 i-RMSD: 1.034 Fnat: 0.879 DockQ: 0.819 -Best model - rank: 3 i-RMSD: 0.822 Fnat: 0.862 DockQ: 0.858 - -============================================== -== run1-abb/07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 13 out of 50 -Total number of medium or better models: 10 out of 50 -Total number of high quality models: 2 out of 50 - -First acceptable model - rank: 1 i-RMSD: 1.249 Fnat: 0.793 DockQ: 0.773 -First medium model - rank: 1 i-RMSD: 1.249 Fnat: 0.793 DockQ: 0.773 -Best model - rank: 4 i-RMSD: 0.901 Fnat: 0.862 DockQ: 0.857 - -============================================== -== run1-af2/07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 23 out of 50 -Total number of medium or better models: 1 out of 50 -Total number of high quality models: 0 out of 50 - -First acceptable model - rank: 2 i-RMSD: 2.492 Fnat: 0.466 DockQ: 0.508 -First medium model - rank: 22 i-RMSD: 1.780 Fnat: 0.448 DockQ: 0.592 -Best model - rank: 22 i-RMSD: 1.780 Fnat: 0.448 DockQ: 0.592 --
-============================================== -== run1-ens-clst//12_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 3 out of 7 -Total number of medium or better clusters: 1 out of 7 -Total number of high quality clusters: 0 out of 7 - -First acceptable cluster - rank: 1 i-RMSD: 1.276 Fnat: 0.828 DockQ: 0.779 -First medium cluster - rank: 1 i-RMSD: 1.276 Fnat: 0.828 DockQ: 0.779 -Best cluster - rank: 1 i-RMSD: 1.276 Fnat: 0.828 DockQ: 0.779 --
-============================================== -== run1-ens-clst//02_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 50 out of 150 -Total number of medium or better models: 25 out of 150 -Total number of high quality models: 0 out of 150 - -First acceptable model - rank: 3 i-RMSD: 1.273 Fnat: 0.672 DockQ: 0.716 -First medium model - rank: 3 i-RMSD: 1.273 Fnat: 0.672 DockQ: 0.716 -Best model - rank: 46 i-RMSD: 1.154 Fnat: 0.828 DockQ: 0.795 -============================================== -== run1-ens-clst//05_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 28 out of 68 -Total number of medium or better models: 10 out of 68 -Total number of high quality models: 0 out of 68 - -First acceptable model - rank: 3 i-RMSD: 1.273 Fnat: 0.672 DockQ: 0.716 -First medium model - rank: 3 i-RMSD: 1.273 Fnat: 0.672 DockQ: 0.716 -Best model - rank: 15 i-RMSD: 1.229 Fnat: 0.707 DockQ: 0.744 -============================================== -== run1-ens-clst//07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 27 out of 68 -Total number of medium or better models: 10 out of 68 -Total number of high quality models: 3 out of 68 - -First acceptable model - rank: 1 i-RMSD: 1.454 Fnat: 0.759 DockQ: 0.720 -First medium model - rank: 1 i-RMSD: 1.454 Fnat: 0.759 DockQ: 0.720 -Best model - rank: 22 i-RMSD: 0.908 Fnat: 0.776 DockQ: 0.803 --
-QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDES -YNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS -- -* Antibody light chain: -
-DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPS -RFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK -- -* Antigen: -
-VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGL -KEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYI -STSQAENMPVFLGGTKGGQDITDFTMQFVSS --
-QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDESYNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS:DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPSRFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK:VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGLKEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYISTSQAENMPVFLGGTKGGQDITDFTMQFVSS -- - - -Define the _jobname_, e.g. Ab-Ag - - - -In the _Advanced settings_ block you can check the option to save the results to your Google Drive (if you have an account) - - - -In the top section of the Colab, click: _Runtime > Run All_ - - -(It may give a warning that this is not authored by Google, because it is pulling code from GitHub - you can ignore it). - -This will automatically install, configure and run AlphaFold for you - leave this window open. -After the prediction complete you will be asked to download a zip-archive with the results (if you configured it to use Google Drive, a result archive will be automatically saved to your Google Drive). - -
- Model1: pLDDT=90.4 pTM=0.654 ipTM=0.525 - Model2: pLDDT=88.0 pTM=0.65 ipTM=0.522 - Model3: pLDDT=88.2 pTM=0.647 ipTM=0.52 - Model4: pLDDT=88.0 pTM=0.644 ipTM=0.516 - Model5: pLDDT=88.1 pTM=0.641 ipTM=0.512 --
- 
- 
- Analysis report of step 10_caprieval
-
-
-
--assign (selection1) (selection2) distance, lower-bound correction, upper-bound correction -- -The lower limit for the distance is calculated as: distance minus lower-bound -correction and the upper limit as: distance plus upper-bound correction. The -syntax for the selections can combine information about chainID - `segid` -keyword -, residue number - `resid` keyword -, atom name - `name` keyword. -Other keywords can be used in various combinations of OR and AND statements. -Please refer for that to the [online CNS manual](http://cns-online.org/v1.3/){:target="_blank"}. - -We will shortly explain in this section how to generate both ambiguous -interaction restraints (AIRs) and specific distance restraints for use in -HADDOCK illustrating a scenario in which no _a priori_ knowledge is available -about the antibody binding site, but in which the antigen epitope has been pinpointed -by an NMR chemical shift perturbation experiment. - -Information about various types of distance restraints in HADDOCK can also be -found in our [online manual][air-help]{:target="_blank"} pages. - -
-31,32,33,34,35,52,54,55,56,100,101,102,103,104,105,106,151,152,169,170,173,211,212,213,214,216 -- -The numbering corresponds to the numbering of the `4G6K_clean.pdb` PDB file. - -Let us visualize those onto the 3D structure. -For this start PyMOL and load `4G6K_clean.pdb` - - -File menu -> Open -> select 4G6K_clean.pdb - - -We will now highlight the predicted paratope. In PyMOL type the following commands: - - -color white, all - - -select paratope, (resi 31+32+33+34+35+52+54+55+56+100+101+102+103+104+105+106+151+152+169+170+173+211+212+213+214+216)
-
--72,73,74,75,81,83,84,89,90,92,94,96,97,98,115,116,117 -- -We will now visualize the epitope on Interleukin-1β. For this start PyMOL and from the PyMOL File menu open the provided PDB file of the antigen. - - -File menu -> Open -> select 4I1B_clean.pdb - - - -color white, all - - -show surface - - -select epitope, (resi 72+73+74+75+81+83+84+89+90+92+94+96+97+98+115+116+117) - - -color red, epitope - - -Inspect the surface. - - -Do the identified residues form a well defined patch on the surface? - - -The answer to that question should be yes, but we can see some residues not colored that might also be involved in the binding - there are some white spots around/in the red surface. - -
- -1 32 33 34 35 52 54 55 56 100 101 102 103 104 105 106 151 152 169 170 173 211 212 213 214 216 - -- -* and for the antigen (the file called `antigen-NMR-epitope.act-pass` from the `restraints` directory): -
-72 73 74 75 81 83 84 89 90 92 94 96 97 98 115 116 117 -3 24 46 47 48 50 66 76 77 79 80 82 86 87 88 91 93 95 118 119 120 -- -Using those two files, we can generate the CNS-formatted AIR restraint files with the following command: - - -haddock3-restraints active_passive_to_ambig ./restraints/antibody-paratope.act-pass ./restraints/antigen-NMR-epitope.act-pass > ambig-paratope-NMR-epitope.tbl - - -This generates a file called `ambig-paratope-NMR-epitope.tbl` that contains the AIR -restraints. The default distance range for those is between 0 and 2Å, which -might seem short but makes senses because of the 1/r^6 summation in the AIR -energy function that makes the effective distance be significantly shorter than -the shortest distance entering the sum. - -The effective distance is calculated as the SUM over all pairwise atom-atom -distance combinations between an active residue and all the active+passive on -the other molecule: SUM[1/r^6]^(-1/6). - -If you modify manually this file, it is possible to quickly check if the format is valid. - - -haddock3-restraints validate_tbl ambig-paratope-NMR-epitope.tbl --silent - - -No output means that your TBL file is valid. - -
- assign (segid A and resi 110 and name CA) (segid A and resi 132 and name CA) 47.578 0.0 0.0 - assign (segid A and resi 97 and name CA) (segid A and resi 204 and name CA) 33.405 0.0 0.0 -- -This file is also provided in the `restraints` directory of the archive you downloaded. - -If you are considering Alphafold2 or ABodyBuilder2 antibodies you have to create the appropriate distance restraints: - - -haddock3-restraints restrain_bodies 4G6K_af2_clean.pdb > af2-antibody-unambig.tbl - - - -haddock3-restraints restrain_bodies 4G6K_abb_clean.pdb > abb-antibody-unambig.tbl - - -
-model md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq air bsa desolv elec total vdw -../06_emref/emref_2.pdb - 1 -164.078 2.111 0.621 5.456 4.368 0.555 96.928 2077.920 6.253 -584.597 -550.774 -63.105 -../06_emref/emref_8.pdb - 2 -144.476 1.472 0.759 2.659 2.691 0.726 43.505 2018.670 5.884 -549.010 -550.413 -44.908 -../06_emref/emref_4.pdb - 3 -138.888 1.087 0.724 2.888 1.830 0.759 116.384 1817.670 2.875 -558.618 -483.913 -41.678 -../06_emref/emref_3.pdb - 4 -138.860 0.983 0.931 1.826 1.554 0.862 100.098 1822.150 1.606 -503.198 -452.935 -49.836 -../06_emref/emref_1.pdb - 5 -138.754 1.146 0.828 1.738 1.846 0.806 36.138 1924.090 5.316 -528.536 -534.375 -41.976 -../06_emref/emref_5.pdb - 6 -138.362 0.921 0.914 1.817 1.482 0.866 73.832 1897.950 4.279 -484.430 -463.736 -53.138 -../06_emref/emref_6.pdb - 7 -138.054 1.153 0.862 2.220 1.880 0.809 63.112 1958.060 5.507 -529.438 -510.311 -43.985 -../06_emref/emref_9.pdb - 8 -134.536 1.313 0.810 2.508 2.239 0.765 63.951 1862.230 7.050 -522.799 -502.269 -43.421 -../06_emref/emref_11.pdb - 9 -131.577 0.965 0.862 1.337 1.428 0.848 58.716 1905.400 9.684 -519.910 -504.344 -43.151 -.... -- -If clustering was performed prior to calling the `caprieval` module the `capri_ss.tsv` file will also contain information about to which cluster the model belongs to and its ranking within the cluster. - -The relevant statistics are: - -* **score**: *the HADDOCK score (arbitrary units)* -* **irmsd**: *the interface RMSD, calculated over the interfaces the molecules* -* **fnat**: *the fraction of native contacts* -* **lrmsd**: *the ligand RMSD, calculated on the ligand after fitting on the receptor (1st component)* -* **ilrmsd**: *the interface-ligand RMSD, calculated over the interface of the ligand after fitting on the interface of the receptor (more relevant for small ligands for example)* -* **dockq**: *the DockQ score, which is a combination of irmsd, lrmsd and fnat and provides a continuous scale between 1 (exactly equal to reference) and 0* - -The iRMSD, lRMSD and Fnat metrics are the ones used in the blind protein-protein prediction experiment [CAPRI](https://capri.ebi.ac.uk/) (Critical PRediction of Interactions). - -In CAPRI the quality of a model is defined as (for protein-protein complexes): - -* **acceptable model**: i-RMSD < 4Å or l-RMSD<10Å and Fnat > 0.1 (0.23 < DOCKQ < 0.49) -* **medium quality model**: i-RMSD < 2Å or l-RMSD<5Å and Fnat > 0.3 (0.49 < DOCKQ < 0.8) -* **high quality model**: i-RMSD < 1Å or l-RMSD<1Å and Fnat > 0.5 (DOCKQ > 0.8) - - -What is based on this CAPRI criterion the quality of the best model listed above (emref_6.pdb)? - - -In case the `caprieval` module is called after a clustering step an additional file will be present in the directory: `capri_clt.tsv`. -This file contains the cluster ranking and score statistics, averaged over the minimum number of models defined for clustering -(4 by default), with their corresponding standard deviations. E.g.: - -
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 2 10 - -139.014 7.386 1.426 0.182 0.746 0.081 3.235 0.650 0.715 0.056 131.826 51.848 2002.760 76.340 8.397 4.920 -584.336 90.832 -496.236 89.379 -43.727 11.464 1 -2 3 10 - -120.115 6.139 14.964 0.018 0.069 0.000 23.390 0.342 0.065 0.001 189.120 18.758 1998.883 56.075 4.601 5.111 -426.788 71.303 -295.939 64.795 -58.270 8.018 2 -3 1 19 - -86.814 2.027 8.747 0.451 0.112 0.019 16.725 0.548 0.115 0.010 203.898 11.457 1554.495 32.501 7.527 1.994 -355.098 23.298 -194.910 27.573 -43.710 4.911 3 -... -- - -In this file you find the cluster rank, the cluster ID (which is related to the size of the cluster, 1 being always the largest cluster), the number of models (n) in the cluster and the corresponding statistics (averages + standard deviations). The corresponding cluster PDB files will be found in the processing `09_seletopclusts` directory. - -
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 1 17 - -146.575 10.361 1.413 0.442 0.759 0.112 3.207 1.357 0.726 0.110 89.229 27.411 1934.102 116.109 4.155 1.970 -548.856 29.400 -509.509 42.520 -49.882 8.168 1 -2 2 15 - -108.943 2.131 4.978 0.092 0.134 0.014 11.239 0.427 0.194 0.009 158.010 45.857 1670.585 42.916 8.673 2.771 -344.907 20.265 -251.333 32.787 -64.436 2.947 2 -3 3 5 - -96.132 13.387 9.913 0.553 0.077 0.019 19.462 0.471 0.087 0.009 155.613 56.813 1460.395 15.293 1.130 1.740 -348.077 48.270 -235.672 68.325 -43.208 9.309 3 -4 4 4 - -87.709 10.400 14.477 0.276 0.073 0.026 23.422 0.445 0.067 0.010 99.097 12.356 1602.033 180.993 6.684 2.524 -311.045 11.794 -254.042 22.508 -42.094 8.503 4 --
-============================================== -== runs/run1-CDR-NMR-CSP/10_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 1 out of 4 -Total number of medium or better clusters: 1 out of 4 -Total number of high quality clusters: 0 out of 4 - -First acceptable cluster - rank: 1 i-RMSD: 1.413 Fnat: 0.759 DockQ: 0.726 -First medium cluster - rank: 1 i-RMSD: 1.413 Fnat: 0.759 DockQ: 0.726 -Best cluster - rank: 1 i-RMSD: 1.413 Fnat: 0.759 DockQ: 0.726 --
-============================================== -== ./runs/run1-CDR-NMR-CSP/02_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 25 out of 96 -Total number of medium or better models: 15 out of 96 -Total number of high quality models: 0 out of 96 - -First acceptable model - rank: 1 i-RMSD: 2.504 Fnat: 0.328 DockQ: 0.405 -First medium model - rank: 5 i-RMSD: 1.169 Fnat: 0.828 DockQ: 0.788 -Best model - rank: 13 i-RMSD: 1.013 Fnat: 0.672 DockQ: 0.735 -============================================== -== ./runs/run1-CDR-NMR-CSP/05_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 18 out of 48 -Total number of medium or better models: 15 out of 48 -Total number of high quality models: 4 out of 48 - -First acceptable model - rank: 1 i-RMSD: 1.107 Fnat: 0.810 DockQ: 0.805 -First medium model - rank: 1 i-RMSD: 1.107 Fnat: 0.810 DockQ: 0.805 -Best model - rank: 10 i-RMSD: 0.857 Fnat: 0.810 DockQ: 0.848 -============================================== -== ./runs/run1-CDR-NMR-CSP/07_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 18 out of 48 -Total number of medium or better models: 15 out of 48 -Total number of high quality models: 5 out of 48 - -First acceptable model - rank: 1 i-RMSD: 2.111 Fnat: 0.621 DockQ: 0.555 -First medium model - rank: 2 i-RMSD: 1.472 Fnat: 0.759 DockQ: 0.726 -Best model - rank: 6 i-RMSD: 0.921 Fnat: 0.914 DockQ: 0.866 -============================================== -== ./runs/run1-CDR-NMR-CSP/10_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 17 out of 41 -Total number of medium or better models: 15 out of 41 -Total number of high quality models: 5 out of 41 - -First acceptable model - rank: 1 i-RMSD: 2.111 Fnat: 0.621 DockQ: 0.555 -First medium model - rank: 2 i-RMSD: 1.472 Fnat: 0.759 DockQ: 0.726 -Best model - rank: 6 i-RMSD: 0.921 Fnat: 0.914 DockQ: 0.866 --
- In terms of iRMSD values we only observe very small differences in the best model. The fraction of native contacts and the DockQ scores are however improving much more after flexible refinement. All this will of course depend on how different are the bound and unbound conformations and the amount of data used to drive the docking process. In general, from our experience, the more and better data at hand, the larger the conformational changes that can be induced. -
-- This is clearly not the case. The scoring function is not perfect, but does a reasonable job in ranking models of acceptable or better quality on top in this case. -
-Top4 models of the top cluster superimposed onto the reference crystal structure (in yellow)
-
-
--QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDES -YNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS -- -* Antibody light chain: -
-DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPS -RFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK -- -* Antigen: -
-VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGL -KEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYI -STSQAENMPVFLGGTKGGQDITDFTMQFVSS --
- Model1: pLDDT=90.4 pTM=0.654 ipTM=0.525 - Model2: pLDDT=88.0 pTM=0.65 ipTM=0.522 - Model3: pLDDT=88.2 pTM=0.647 ipTM=0.52 - Model4: pLDDT=88.0 pTM=0.644 ipTM=0.516 - Model5: pLDDT=88.1 pTM=0.641 ipTM=0.512 -- -
-
-
- Analysis report of step 10_caprieval
-
+ 
+ 
+
+
+(haddock3)$ haddock3 -h
+usage: haddock3 [-h] [--restart RESTART] [--extend-run EXTEND_RUN] [--setup]
+ [--log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}] [-v]
+ recipe
+
+positional arguments:
+ recipe The input recipe file path
+
+optional arguments:
+ -h, --help show this help message and exit
+ --restart RESTART Restart the run from a given step. Previous folders from the
+ selected step onward will be deleted.
+ --extend-run EXTEND_RUN
+ Start a run from a run directory previously prepared with the
+ `haddock3-copy` CLI. Provide the run directory created with
+ `haddock3-copy` CLI.
+ --setup Only setup the run, do not execute
+ --log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
+ -v, --version show version
+
+assign (selection1) (selection2) distance, lower-bound correction, upper-bound correction-The lower limit for the distance is calculated as: distance minus lower-bound -correction and the upper limit as: distance plus upper-bound correction. The -syntax for the selections can combine information about chainID - `segid` -keyword -, residue number - `resid` keyword -, atom name - `name` keyword. -Other keywords can be used in various combinations of OR and AND statements. -Please refer for that to the [online CNS manual](http://cns-online.org/v1.3/){:target="_blank"}. +The lower limit for the distance is calculated as: distance minus lower-bound correction +and the upper limit as: distance plus upper-bound correction. + +The syntax for the selections can combine information about: + +* chainID - `segid` keyword +* residue number - `resid` keyword +* atom name - `name` keyword. + +Other keywords can be used in various combinations of OR and AND statements. Please refer for that to the [online CNS manual][link-cns]{:target="_blank"}. -We will shortly explain in this section how to generate both ambiguous -interaction restraints (AIRs) and specific distance restraints for use in -HADDOCK illustrating two scenarios: +E.g.: a distance restraint between the CB carbons of residues 10 and 200 in chains A and B with an +allowed distance range between 10Å and 20Å would be defined as follows: -* **HV loops on the antibody, full surface on the antigen** -* **HV loops on the antibody, NMR interface mapping on the antigen** +
+assign (segid A and resid 10 and name CB) (segid B and resid 200 and name CB) 20.0 10.0 0.0 ++ + +Can you think of a different way of defining the distance and lower and upper corrections while maintaining the same +allowed range? + -Information about various types of distance restraints in HADDOCK can also be -found in our [online manual][air-help]{:target="_blank"} pages.
-31,32,33,34,35,52,54,55,56,100,101,102,103,104,105,106,1031,1032,1049,1050,1053,1091,1092,1093,1094,1096 +31,32,33,34,35,52,54,55,56,100,101,102,103,104,105,106,151,152,169,170,173,211,212,213,214,216The numbering corresponds to the numbering of the `4G6K_clean.pdb` PDB file. @@ -426,22 +427,18 @@ For this start PyMOL and load `4G6K_clean.pdb` File menu -> Open -> select 4G6K_clean.pdb -or from the command line: +Alternatively, if PyMOL is accessible from the command line, simply type: pymol 4G6K_clean.pdb -We will now highlight the predicted paratope. In PyMOL type the following commands: +We will now highlight the predicted paratope residues in red. In PyMOL type the following commands: -color white, all - - -select paratope, (resi 31+32+33+34+35+52+54+55+56+100+101+102+103+104+105+106+1031+1032+1049+1050+1053+1091+1092+1093+1094+1096)
+ 
-REM FreeSASA 2.0.3 -REM Absolute and relative SASAs for 4I1B_clean.pdb -REM Atomic radii and reference values for relative SASA: ProtOr -REM Chains: A -REM Algorithm: Lee & Richards -REM Probe-radius: 1.40 -REM Slices: 20 -REM RES _ NUM All-atoms Total-Side Main-Chain Non-polar All polar -REM ABS REL ABS REL ABS REL ABS REL ABS REL -RES VAL A 3 84.83 55.8 13.08 11.8 71.76 172.9 30.45 26.5 54.38 147.5 -RES ARG A 4 200.36 84.1 192.85 98.3 7.51 17.9 71.92 98.3 128.44 77.8 -RES SER A 5 48.69 41.1 25.55 34.1 23.14 53.3 22.44 47.8 26.25 36.8 -RES LEU A 6 71.91 40.0 70.87 50.7 1.04 2.6 71.91 50.5 0.00 0.0 -RES ASN A 7 31.01 21.4 25.87 25.0 5.14 12.4 0.00 0.0 31.01 30.0 -... -- -The following command will return all residues with a relative SASA for either -the backbone or the side-chain > 15% (we use 15% to limit the number of surface residues selected as their -number does increase the computational requirements) - - - awk \'{if (NF==13 && ($7>15 || $9>15)) printf \"\%d \",$3; if (NF==14 && ($8>15 || $10>15)) print $0}\' 4I1B_clean.rsa - - -The resulting list of residues can be found in the `restraints/antigen-surface.act-pass` file. Note in this file the empty first line. The file consists -of two lines, with the first one defining the `active` residues and the second line the `passive` ones, in this case the solvent accessible residues. -We will use later this file to generate the ambiguous distance restraints for HADDOCK. - -If you want to generate the same file, first create an empty line and then use the `awk` command, piping the results to an output file, e.g.: - - - echo \" \" \> antigen-surface.pass
-14/03/2023 13:15:20 L157 INFO - Calculate accessibility... -14/03/2023 13:15:20 L228 INFO - Chain: B - 151 residues -14/03/2023 13:15:20 L234 INFO - Applying cutoff to side_chain_rel - 0.15 -14/03/2023 13:15:20 L244 INFO - Chain B - 3,4,5,6,7,11,13,14,15,20,21,22,23,24,25,27,29,30,32,33,34,35,36,37,38,41,43,46,48,49,50,51,52,53,54,55,56,63,64,65,66,72,73,74,75,76,77,79,81,83,84,86,87,88,89,91,92,93,94,96,97,98,105,106,107,108,109,115,116,117,118,119,120,125,126,127,128,129,130,131,133,135,137,138,139,140,141,142,145,147,149,150,151,152,153 -- -We can visualize the selected surface residues of Interleukin-1β. - -For this start PyMOL and from the PyMOL File menu open the PDB file of the antigen. - - -color white, all - - -show surface - - -select surface15, (resi 3+4+5+6+13+14+15+20+21+22+23+24+25+30+32+33+34+35+37+38+48+49+50+51+52+53+54+55+61+63+64+65+66+73+74+75+76+77+80+84+86+87+88+89+90+91+93+94+96+97+105+106+107+108+109+118+119+126+127+128+129+130+135+136+137+138+139+140+141+142+147+148+150+151+152+153) - - -color green, surface40 - - - -color white, all - - -show surface - - -select surface40, (resi 3+4+5+6+13+14+15+20+21+22+23+24+25+30+32+33+34+35+37+38+48+49+50+51+52+53+54+55+61+63+64+65+66+73+74+75+76+77+80+84+86+87+88+89+90+91+93+94+96+97+105+106+107+108+109+118+119+126+127+128+129+130+135+136+137+138+139+140+141+142+147+148+150+151+152+153) - - -color green, surface40 - - -
+ 
+ 
+ -31 32 33 34 35 52 54 55 56 100 101 102 103 104 105 106 1031 1032 1049 1050 1053 1091 1092 1093 1094 1096 -+*__Active residues__*: These residues are "forced" to be at the interface. If they are not part of the interface in the final models, an energetic penalty will be applied. The interface in this context is defined by the union of active and passive residues on the partner molecules. -* and for the antigen (the file called `antigen-surface.pass` from the `restraints` directory): -
-3 4 5 6 13 14 15 20 21 22 23 24 25 30 32 33 34 35 37 38 48 49 50 51 52 53 54 55 61 63 64 65 66 73 74 75 76 77 80 84 86 87 88 89 90 91 93 94 96 97 105 106 107 108 109 118 119 126 127 128 129 130 135 136 137 138 139 140 141 142 147 148 150 151 152 153 -+*__Passive residues__*: These residues are expected to be at the interface. However, if they are not, no energetic penalty is applied. -Using those two files, we can generate the CNS-formatted AIR restraint files -with the following command: - -haddock3-restraints active_passive_to_ambig ./restraints/antibody-paratope.act-pass ./restraints/antigen-surface.pass > ambig-paratope-surface.tbl - +In general, it is better to be too generous rather than too strict in the definition of passive residues. +An important aspect is to filter both the active (the residues identified from your mapping experiment) and passive residues by their solvent accessibility. +This is done automatically when using the `haddock3-restraints passive_from_active` command: residues with less that 15% relative solvent accessibility (same cutoff as the default in the HADDOCK server) are discared. +This is, however, not a hard limit, and you might consider including even more buried residues if some important chemical group seems solvent accessible from a visual inspection. -This generates a file called `ambig-paratope-surface.tbl` that contains the AIR -restraints. The default distance range for those is between 0 and 2Å, which -might seem short but makes senses because of the 1/r^6 summation in the AIR -energy function that makes the effective distance be significantly shorter than -the shortest distance entering the sum. -The effective distance is calculated as the SUM over all pairwise atom-atom -distance combinations between an active residue and all the active+passive on -the other molecule: SUM[1/r^6]^(-1/6). +
+1 32 33 34 35 52 54 55 56 100 101 102 103 104 105 106 151 152 169 170 173 211 212 213 214 216 --### Defining ambiguous restraints for scenario 2b +* For the antigen we will use the NMR-identified epitope as active and the surface neighbors as passive. +The corresponding file can be found in the `restraints` directory as `antigen-NMR-epitope.act-pass`: -In this scenario the NMR epitope is defined as active (meaning ambiguous distance restraints will be defined from the NMR epitope residues) and the surface neighbors are used as passive residues in HADDOCK. +
+
+72 73 74 75 81 83 84 89 90 92 94 96 97 98 115 116 117 +3 24 46 47 48 50 66 76 77 79 80 82 86 87 88 91 93 95 118 119 120 +-The creation of the AIR tbl file for scenario 2b is similar to scenario 1, but instead using the `antigen-NMR-epitope.act-pass` file for the antigen: +Using those two files, we can generate the CNS-formatted Ambiguous Interaction Restraints (AIRs) file with the following command: -haddock3-restraints active_passive_to_ambig ./restraints/antibody-paratope.act-pass ./restraints/antigen-NMR-epitope.act-pass > ambig-paratope-NMR-epitope.tbl +haddock3-restraints active_passive_to_ambig ./restraints/antibody-paratope.act-pass ./restraints/antigen-NMR-epitope.act-pass \-\-segid-one A \-\-segid-two B > ambig-paratope-NMR-epitope.tbl -
- assign (segid A and resi 220 and name CA) (segid A and resi 1018 and name CA) 47.578 0.0 0.0 - assign (segid A and resi 193 and name CA) (segid A and resi 1014 and name CA) 33.405 0.0 0.0 -- -This file is also provided in the `restraints` directory of the archive you downloaded. - -
+assign (resi 31 and segid A) +( + (resi 72 and segid B) + or + (resi 73 and segid B) + or + (resi 74 and segid B) + or + (resi 75 and segid B) + or + (resi 81 and segid B) + or + (resi 83 and segid B) + or + (resi 84 and segid B) + or + (resi 89 and segid B) + or + (resi 90 and segid B) + or + (resi 92 and segid B) + or + (resi 94 and segid B) + or + (resi 96 and segid B) + or + (resi 97 and segid B) + or + (resi 98 and segid B) + or + (resi 115 and segid B) + or + (resi 116 and segid B) + or + (resi 117 and segid B) + or + (resi 3 and segid B) + or + (resi 24 and segid B) + or + (resi 46 and segid B) + or + (resi 47 and segid B) + or + (resi 48 and segid B) + or + (resi 50 and segid B) + or + (resi 66 and segid B) + or + (resi 76 and segid B) + or + (resi 77 and segid B) + or + (resi 79 and segid B) + or + (resi 80 and segid B) + or + (resi 82 and segid B) + or + (resi 86 and segid B) + or + (resi 87 and segid B) + or + (resi 88 and segid B) + or + (resi 91 and segid B) + or + (resi 93 and segid B) + or + (resi 95 and segid B) + or + (resi 118 and segid B) + or + (resi 119 and segid B) + or + (resi 120 and segid B) +) 2.0 2.0 0.0 +... ++
+ assign (segid A and resi 110 and name CA) (segid A and resi 132 and name CA) 26.326 0.0 0.0 + assign (segid A and resi 97 and name CA) (segid A and resi 204 and name CA) 19.352 0.0 0.0 +-#### 2. batch mode +This file is also provided in the `restraints` directory. -In this mode HADDOCK3 will typically be started on your local server (e.g. the login node) and will dispatch jobs to the batch system of your cluster. -Two batch systems are currently supported: `slurm` and `torque` (defined by the `batch_type` parameter). In the configuration file you will -have to define the `queue` name and the maximum number of concurrent jobs sent to the queue (`queue_limit`). Since HADDOCK3 single model -calculations are quite fast, it is recommended to calculate multiple models within one job submitted to the batch system. -The number of model per job is defined by the `concat` parameter in the configuration file. -You want to avoid sending thousands of very short jobs to the batch system if you want to remain friend with your system administrators... -An example of the relevant parameters to be defined in the first section of the config file is: +
-mmodel md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq cluster-id cluster-ranking model-cluster-ranking air angles bonds bsa cdih coup dani desolv dihe elec improper rdcs rg total vdw vean xpcs -../6_emref/emref_11.pdb - 1 -151.136 1.261 0.741 2.673 2.192 0.746 2 1 1 79.990 0.000 0.000 2072.710 0.000 0.000 0.000 9.960 0.000 -598.859 0.000 0.000 0.000 -568.192 -49.323 0.000 0.000 -../6_emref/emref_15.pdb - 2 -137.252 1.237 0.845 2.713 2.253 0.783 2 1 2 83.274 0.000 0.000 2058.800 0.000 0.000 0.000 12.576 0.000 -584.402 0.000 0.000 0.000 -542.402 -41.275 0.000 0.000 -../6_emref/emref_19.pdb - 3 -136.527 1.550 0.621 4.283 3.353 0.634 2 1 3 200.318 0.000 0.000 1879.180 0.000 0.000 0.000 11.023 0.000 -704.878 0.000 0.000 0.000 -531.166 -26.606 0.000 0.000 -../6_emref/emref_14.pdb - 4 -131.142 1.658 0.776 3.271 3.005 0.699 2 1 4 163.724 0.000 0.000 2000.350 0.000 0.000 0.000 0.028 0.000 -449.205 0.000 0.000 0.000 -343.183 -57.702 0.000 0.000 -../6_emref/emref_1.pdb - 5 -128.501 14.936 0.069 22.861 21.984 0.067 3 2 1 159.850 0.000 0.000 1975.260 0.000 0.000 0.000 7.691 0.000 -451.593 0.000 0.000 0.000 -353.602 -61.859 0.000 0.000 -.... -+
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 2 10 - -139.014 7.386 1.426 0.182 0.746 0.081 3.235 0.650 0.715 0.056 131.826 51.848 2002.760 76.340 8.397 4.920 -584.336 90.832 -496.236 89.379 -43.727 11.464 1 -2 3 10 - -120.115 6.139 14.964 0.018 0.069 0.000 23.390 0.342 0.065 0.001 189.120 18.758 1998.883 56.075 4.601 5.111 -426.788 71.303 -295.939 64.795 -58.270 8.018 2 -3 1 19 - -86.814 2.027 8.747 0.451 0.112 0.019 16.725 0.548 0.115 0.010 203.898 11.457 1554.495 32.501 7.527 1.994 -355.098 23.298 -194.910 27.573 -43.710 4.911 3 -... -+source /vol0601/data/hp240465/Materials/Life_Science/20250312_Bonvin/haddock3/.venv/bin/activate +haddock3 ./workflows/docking-antibody-antigen.cfg -In this file you find the cluster rank, the cluster ID (which is related to the size of the cluster, 1 being always the largest cluster), the number of models (n) in the cluster and the corresponding statistics (averages + standard deviations). The corresponding cluster PDB files will be found in the processing `X_seletopclusts` directory. +{% endhighlight %} -
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 12 20 - -148.831 5.410 1.678 0.214 0.733 0.106 3.865 0.862 0.669 0.076 185.424 46.938 2111.405 29.031 7.232 1.046 -570.066 22.622 -445.234 30.130 -60.592 5.236 1 -2 18 18 - -123.766 3.115 13.094 0.125 0.000 0.000 21.834 0.146 0.048 0.001 183.704 11.225 2181.110 90.094 -10.254 2.067 -332.751 46.979 -214.379 31.846 -65.332 7.781 2 -3 88 10 - -123.360 3.041 9.176 0.141 0.017 0.000 21.413 0.684 0.060 0.003 121.738 16.249 1813.925 34.884 -5.384 0.512 -436.619 11.830 -357.708 16.713 -42.827 3.868 3 -4 13 20 - -118.282 5.208 10.944 0.299 0.120 0.021 21.415 0.619 0.092 0.006 152.420 10.986 1808.007 32.866 6.465 1.325 -496.468 28.628 -384.743 24.947 -40.696 2.465 4 -5 89 10 - -116.454 3.801 14.020 0.134 0.017 0.000 24.744 0.187 0.045 0.001 195.446 27.781 1889.682 79.773 -4.616 1.591 -417.563 20.307 -269.986 30.222 -47.870 1.270 5 -6 61 10 - -115.229 3.326 5.378 0.020 0.069 0.012 16.802 0.629 0.115 0.005 88.131 9.931 1852.945 23.752 6.616 0.785 -369.303 8.252 -337.969 11.465 -56.798 1.243 6 -7 3 27 - -114.186 5.971 13.496 0.080 0.000 0.000 20.665 0.102 0.052 0.001 165.852 1.993 1707.362 39.298 -3.782 2.991 -376.041 22.069 -261.970 27.164 -51.781 5.373 7 -8 72 10 - -112.872 6.827 13.981 0.020 0.000 0.000 21.801 0.126 0.048 0.000 132.974 16.434 1966.793 52.013 2.544 3.066 -294.085 43.518 -231.007 42.693 -69.896 9.485 8 -9 1 36 - -109.409 4.762 14.617 0.071 0.000 0.000 23.183 0.063 0.043 0.000 197.155 20.227 1744.597 41.866 2.528 2.065 -328.410 33.521 -197.225 28.906 -65.970 1.565 9 -10 17 18 - -108.195 7.362 11.031 0.082 0.000 0.000 20.012 0.260 0.057 0.001 164.234 10.186 1831.495 37.648 1.541 1.670 -396.469 47.982 -279.100 40.077 -46.865 5.102 10 -11 96 10 - -107.334 2.166 10.667 0.151 0.000 0.000 21.692 0.437 0.051 0.002 142.746 7.402 1610.415 71.508 -1.450 3.091 -388.339 21.616 -288.084 14.372 -42.491 6.894 11 -12 14 20 - -107.155 1.167 13.907 0.198 0.000 0.000 23.257 0.230 0.043 0.001 177.685 34.304 1817.573 49.504 -3.932 4.818 -359.962 72.737 -231.276 34.880 -48.999 7.524 12 -13 58 10 - -105.459 2.853 9.418 0.041 0.017 0.000 14.704 0.253 0.098 0.002 142.162 20.088 1801.787 41.822 7.304 1.091 -390.603 6.402 -297.299 14.909 -48.858 1.289 13 -14 7 22 - -104.950 8.949 12.591 0.206 0.000 0.000 21.517 0.421 0.050 0.002 137.010 17.810 1981.173 62.496 3.391 2.312 -294.790 53.286 -220.864 60.327 -63.084 12.713 14 -15 110 8 - -104.523 5.407 15.786 0.141 0.000 0.000 24.742 0.292 0.038 0.001 188.247 28.369 1656.015 29.305 -7.098 2.026 -309.368 15.169 -175.498 17.510 -54.376 4.423 15 -16 90 10 - -102.191 10.542 14.905 0.036 0.060 0.009 23.103 0.131 0.064 0.003 216.193 11.357 1942.820 85.100 5.473 2.317 -341.726 40.261 -186.471 38.069 -60.938 6.555 16 -17 104 9 - -102.002 3.200 14.681 0.078 0.095 0.009 23.567 0.190 0.074 0.003 282.735 23.431 1944.375 30.920 5.480 0.963 -406.682 30.081 -178.366 9.480 -54.419 6.790 17 -18 100 10 - -101.698 3.868 14.309 0.064 0.000 0.000 23.266 0.038 0.043 0.000 199.056 7.430 1988.773 23.017 -8.379 2.438 -240.464 33.134 -106.540 25.499 -65.132 4.179 18 -19 98 10 - -100.603 4.480 12.350 0.118 0.000 0.000 21.122 0.363 0.051 0.001 252.315 14.795 1677.152 43.166 -3.298 0.773 -394.031 29.076 -185.446 16.087 -43.730 1.316 19 -20 102 10 - -100.156 1.566 13.879 0.194 0.000 0.000 22.984 0.407 0.044 0.001 251.103 18.039 1770.800 64.193 -11.348 2.940 -282.111 7.081 -88.504 22.525 -57.496 2.031 20 -21 16 19 - -100.048 2.675 12.712 0.077 0.000 0.000 21.116 0.748 0.051 0.003 141.121 20.656 1614.205 84.277 -7.610 2.379 -245.708 28.106 -161.995 21.053 -57.408 1.913 21 -22 95 10 - -97.056 5.290 12.727 0.079 0.000 0.000 20.681 0.123 0.053 0.000 174.836 11.509 1808.197 27.762 7.899 2.831 -370.697 37.713 -244.160 41.611 -48.299 8.029 22 -23 40 10 - -96.143 7.294 3.996 0.063 0.151 0.023 7.960 0.413 0.269 0.007 268.064 6.044 1733.595 64.045 5.918 1.741 -440.012 18.438 -212.812 23.620 -40.865 2.978 23 -24 87 10 - -95.919 10.319 10.335 0.290 0.073 0.026 18.886 0.434 0.087 0.011 214.010 12.675 1786.825 65.807 -0.359 4.436 -345.955 25.147 -179.715 31.282 -47.770 4.496 24 -25 29 13 - -94.903 5.148 11.976 0.456 0.000 0.000 20.189 0.481 0.056 0.002 180.302 16.905 1590.420 71.694 3.421 0.674 -407.384 36.274 -261.960 42.426 -34.878 4.826 25 -26 82 10 - -94.568 1.367 13.254 0.087 0.021 0.007 23.375 0.213 0.050 0.002 139.468 19.278 1733.650 35.788 -7.849 1.524 -244.905 20.819 -157.122 27.990 -51.684 5.303 26 -27 74 10 - -93.734 3.985 11.956 0.081 0.099 0.007 22.498 0.236 0.080 0.002 301.590 4.206 1764.012 79.875 -3.076 3.370 -299.142 56.102 -58.541 44.764 -60.989 9.410 27 -28 19 17 - -92.956 3.507 13.908 0.268 0.026 0.015 23.921 0.385 0.050 0.004 266.721 14.416 1827.332 46.565 -0.139 2.193 -381.233 53.830 -157.755 45.492 -43.242 7.955 28 -29 122 6 - -92.745 8.304 12.279 0.037 0.000 0.000 19.752 0.060 0.057 0.000 181.589 15.741 1752.342 47.374 1.028 1.586 -279.507 47.440 -153.948 58.429 -56.030 3.553 29 -30 6 22 - -90.730 14.656 15.634 0.186 0.000 0.000 24.460 0.283 0.039 0.001 184.504 30.414 1646.735 13.700 -4.965 3.284 -279.679 35.172 -143.454 66.675 -48.279 4.415 30 -31 9 20 - -90.251 2.575 13.154 0.202 0.017 0.000 20.607 0.234 0.058 0.001 245.319 26.351 1504.862 38.200 10.189 2.033 -416.678 30.459 -212.996 51.332 -41.636 4.161 31 -32 22 16 - -90.038 7.776 13.627 0.190 0.021 0.014 24.214 0.496 0.048 0.006 184.562 6.921 1689.253 49.205 -3.136 2.159 -268.492 14.412 -135.590 22.903 -51.660 5.142 32 -33 26 14 - -89.241 3.176 12.877 0.056 0.073 0.014 20.812 0.219 0.077 0.005 219.898 7.800 1397.388 66.657 9.547 1.503 -442.622 29.172 -254.977 24.167 -32.253 2.642 33 -34 115 7 - -88.870 18.331 12.362 0.132 0.000 0.000 18.819 0.127 0.061 0.001 204.335 46.807 1699.523 139.984 12.768 1.118 -465.403 38.996 -290.059 88.987 -28.991 5.403 34 -35 31 13 - -88.274 9.696 11.822 0.027 0.000 0.000 20.745 0.055 0.053 0.000 212.259 7.756 1703.915 75.126 7.349 1.187 -401.980 29.718 -226.174 34.586 -36.453 5.963 35 -36 51 10 - -88.060 5.613 14.394 0.033 0.013 0.007 23.261 0.216 0.047 0.003 186.626 10.473 1530.995 13.755 -0.823 1.396 -285.016 40.961 -147.287 46.363 -48.896 3.714 36 -37 4 27 - -87.381 3.159 14.366 0.075 0.000 0.000 23.345 0.143 0.043 0.000 262.042 8.675 1685.735 33.973 2.679 1.701 -375.458 19.104 -154.588 19.121 -41.172 3.024 37 -38 66 10 - -86.618 5.301 14.360 0.065 0.065 0.007 22.073 0.117 0.068 0.002 175.771 18.244 1654.713 31.971 9.575 0.751 -391.041 27.344 -250.832 30.637 -35.561 2.215 38 -39 105 9 - -86.351 7.447 12.441 0.119 0.000 0.000 21.061 0.886 0.052 0.003 203.393 38.498 1621.940 67.036 11.485 4.238 -397.087 49.285 -232.452 34.907 -38.758 6.513 39 -40 2 28 - -85.386 3.721 8.292 0.100 0.060 0.009 14.033 0.238 0.120 0.004 223.683 20.263 1444.425 18.443 16.980 1.268 -531.053 52.923 -325.894 45.805 -18.524 8.161 40 -41 99 10 - -85.318 3.371 14.167 0.142 0.000 0.000 23.073 0.125 0.044 0.000 210.252 30.361 1688.745 36.455 -3.802 1.262 -232.285 17.646 -78.117 29.587 -56.084 2.159 41 -42 103 10 - -84.777 7.347 9.713 0.045 0.000 0.000 15.319 0.158 0.086 0.001 211.814 17.902 1762.062 62.020 -2.237 1.474 -302.213 19.881 -133.678 10.735 -43.278 8.354 42 -43 11 20 - -84.755 3.002 10.202 0.038 0.000 0.000 16.040 0.210 0.080 0.001 242.024 11.938 1664.300 32.341 -1.048 2.058 -320.478 20.571 -122.268 20.568 -43.814 3.539 43 -44 27 14 - -84.385 4.142 14.452 0.099 0.000 0.000 22.747 0.072 0.044 0.001 192.791 15.745 1680.112 60.521 8.681 0.414 -322.106 22.136 -177.239 23.588 -47.924 4.456 44 -45 30 13 - -83.349 7.710 12.527 0.328 0.000 0.000 20.534 1.002 0.054 0.004 205.630 34.703 1630.215 82.132 0.730 2.859 -288.909 10.434 -130.138 41.408 -46.861 4.465 45 -46 15 19 - -82.368 3.129 13.418 0.325 0.043 0.009 23.280 0.386 0.058 0.004 242.751 6.286 1658.195 38.410 5.431 0.414 -341.193 32.419 -142.278 23.070 -43.836 6.151 46 -47 20 16 - -81.607 6.919 12.495 0.107 0.000 0.000 19.252 0.363 0.059 0.002 266.161 42.181 1672.205 55.410 5.343 4.413 -414.589 26.369 -179.076 49.862 -30.648 5.816 47 -48 76 10 - -81.449 9.534 13.188 0.037 0.000 0.000 21.421 0.074 0.050 0.001 218.734 15.090 1736.692 89.208 -0.001 1.199 -290.595 36.010 -117.063 50.613 -45.203 3.614 48 -49 8 20 - -81.182 4.279 10.455 0.122 0.000 0.000 16.979 0.225 0.073 0.002 202.172 4.326 1751.410 32.215 6.297 1.591 -296.855 38.493 -143.008 36.221 -48.325 6.151 49 -50 83 10 - -80.925 4.370 12.827 0.095 0.000 0.000 18.830 0.175 0.061 0.001 178.048 13.548 1484.358 38.444 5.855 0.509 -387.956 12.917 -236.901 11.192 -26.994 3.744 50 -51 80 10 - -80.920 1.233 8.605 0.110 0.000 0.000 14.204 0.254 0.098 0.003 263.125 9.132 1680.088 44.302 -2.533 1.044 -276.380 9.676 -62.678 11.913 -49.423 2.206 51 -52 65 10 - -80.630 3.310 14.620 0.066 0.000 0.000 22.569 0.112 0.045 0.000 288.688 2.621 1667.402 19.562 6.148 0.292 -359.050 7.320 -114.200 9.850 -43.837 2.804 52 -53 78 10 - -80.553 1.319 15.253 0.064 0.000 0.000 23.967 0.193 0.041 0.001 243.820 10.141 1722.265 32.414 -6.757 0.875 -233.628 32.754 -41.260 21.926 -51.452 6.462 53 -54 91 10 - -80.434 7.690 12.606 0.433 0.065 0.007 22.027 0.766 0.070 0.005 239.985 31.342 1715.950 113.990 -2.244 1.763 -276.599 35.568 -83.483 44.904 -46.869 5.835 54 -55 86 10 - -79.938 1.932 14.133 0.054 0.000 0.000 21.594 0.090 0.049 0.001 234.653 13.341 1560.172 37.779 -2.434 3.230 -216.869 17.452 -39.812 24.206 -57.595 0.798 55 -56 94 10 - -79.785 3.074 14.163 0.044 0.000 0.000 23.755 0.224 0.042 0.001 233.620 10.459 1617.775 27.712 -4.985 3.008 -246.368 23.556 -61.636 15.735 -48.888 3.624 56 -57 57 10 - -79.647 3.136 14.334 0.035 0.000 0.000 22.584 0.139 0.045 0.001 206.786 21.758 1752.880 43.951 4.484 1.474 -292.769 26.191 -132.238 35.347 -46.255 2.074 57 -58 109 8 - -79.637 4.090 14.374 0.029 0.000 0.000 23.226 0.171 0.043 0.001 179.447 18.968 1587.280 48.041 -6.736 4.312 -216.970 21.146 -84.975 34.722 -47.452 4.918 58 -59 125 4 - -79.181 3.093 13.707 0.110 0.013 0.007 25.049 0.264 0.043 0.002 208.704 5.337 1603.477 18.923 0.803 3.084 -320.220 17.996 -148.327 16.357 -36.811 2.829 59 -60 75 10 - -79.050 2.188 9.582 0.072 0.013 0.007 17.607 0.404 0.075 0.002 255.051 11.542 1487.710 19.121 -3.626 3.331 -272.006 25.775 -63.483 15.928 -46.528 1.228 60 -61 21 16 - -78.910 7.107 12.204 0.791 0.000 0.000 19.571 0.565 0.058 0.003 265.529 23.762 1628.423 100.079 -7.391 2.450 -259.371 19.026 -40.040 31.465 -46.198 2.505 61 -62 119 6 - -78.891 12.708 12.225 0.073 0.000 0.000 21.918 0.277 0.049 0.001 183.873 60.583 1612.245 43.225 5.173 2.252 -342.645 40.522 -192.694 94.271 -33.921 1.601 62 -63 32 12 - -78.111 4.787 11.640 0.490 0.030 0.007 19.381 0.419 0.070 0.005 224.618 24.572 1458.675 59.540 12.585 2.659 -404.922 39.771 -212.478 43.741 -32.174 7.745 63 -64 93 10 - -75.558 0.893 15.617 0.035 0.000 0.000 25.553 0.142 0.036 0.001 234.040 18.302 1612.077 87.261 -2.881 1.880 -222.506 13.334 -40.046 22.117 -51.580 3.451 64 -65 53 10 - -74.878 0.925 11.095 0.055 0.000 0.000 19.669 0.309 0.058 0.001 217.684 13.625 1737.645 54.714 4.811 2.265 -267.514 39.563 -97.784 28.401 -47.954 8.106 65 -66 50 10 - -74.229 3.215 9.398 0.118 0.000 0.000 15.157 0.226 0.088 0.002 201.585 13.616 1307.077 34.282 7.107 1.138 -346.429 18.226 -177.052 16.240 -32.209 2.692 66 -67 46 10 - -74.057 6.696 13.393 0.171 0.038 0.008 20.998 0.234 0.064 0.004 182.613 28.046 1532.910 44.960 11.778 4.762 -283.146 29.545 -148.000 30.970 -47.467 2.189 67 -68 10 20 - -73.940 3.036 10.540 0.046 0.017 0.000 19.176 0.153 0.067 0.001 356.795 15.142 1492.230 74.353 15.509 2.170 -510.698 9.877 -176.892 19.108 -22.989 0.857 68 -69 44 10 - -73.811 2.120 13.513 0.025 0.000 0.000 20.546 0.111 0.052 0.001 210.162 18.014 1370.822 23.324 5.688 1.348 -373.221 16.893 -188.930 22.084 -25.871 3.664 69 -70 101 10 - -73.605 5.664 7.585 0.291 0.194 0.007 15.971 0.612 0.151 0.003 239.400 28.980 1437.820 17.631 2.496 1.252 -306.286 30.593 -105.669 8.236 -38.784 7.589 70 -71 73 10 - -73.330 14.683 8.421 0.080 0.142 0.022 16.234 0.195 0.129 0.007 291.068 13.141 1524.905 74.286 7.236 1.570 -318.544 28.529 -73.439 41.719 -45.964 8.000 71 -72 79 10 - -72.710 2.560 11.891 0.070 0.017 0.000 21.817 0.101 0.055 0.000 267.791 10.125 1643.050 30.536 -1.153 0.712 -316.054 21.622 -83.389 26.219 -35.125 3.184 72 -73 108 8 - -72.053 6.427 14.141 0.080 0.000 0.000 22.606 0.088 0.045 0.000 274.130 28.215 1575.818 26.120 2.867 4.129 -353.149 37.289 -110.722 50.901 -31.703 6.123 73 -74 116 7 - -71.931 3.431 14.263 0.020 0.021 0.007 21.881 0.092 0.055 0.002 239.220 23.289 1488.585 51.307 11.289 2.327 -337.511 20.455 -137.931 34.222 -39.639 2.696 74 -75 23 15 - -71.317 1.735 9.651 0.111 0.000 0.000 15.522 0.401 0.085 0.003 194.466 13.162 1484.050 42.048 9.548 1.288 -290.001 20.663 -137.847 15.853 -42.312 1.866 75 -76 24 15 - -71.030 2.953 16.556 0.115 0.000 0.000 28.355 0.305 0.030 0.000 205.405 8.091 1334.508 11.170 -5.633 2.051 -183.413 17.299 -27.264 20.045 -49.255 2.861 76 -77 28 13 - -70.176 3.460 14.159 0.213 0.004 0.007 22.016 0.254 0.048 0.003 212.614 35.492 1491.645 40.439 8.647 0.432 -294.032 36.700 -122.695 8.604 -41.277 2.477 77 -78 37 11 - -69.964 1.337 15.376 0.133 0.000 0.000 25.078 0.326 0.037 0.001 271.813 14.529 1713.650 51.673 -7.231 2.128 -241.582 17.736 -11.367 27.829 -41.599 3.838 78 -79 123 5 - -69.304 4.503 16.450 0.148 0.000 0.000 27.833 0.537 0.031 0.001 210.556 19.322 1326.200 45.711 -5.965 1.162 -161.157 6.948 -2.764 25.378 -52.163 3.012 79 -80 106 9 - -67.503 6.037 12.789 0.289 0.026 0.015 23.061 1.336 0.053 0.002 296.781 34.983 1620.858 52.591 5.560 2.969 -348.713 38.348 -84.930 63.453 -32.998 4.669 80 -81 120 6 - -67.302 2.532 14.358 0.041 0.000 0.000 22.837 0.023 0.044 0.000 271.706 12.518 1634.723 24.273 0.998 1.097 -227.589 9.829 -5.836 14.119 -49.953 3.620 81 -82 55 10 - -67.097 3.840 6.036 0.861 0.090 0.014 12.039 0.749 0.162 0.019 384.023 42.496 1531.295 87.955 3.794 4.479 -454.914 59.765 -89.202 76.199 -18.311 9.697 82 -83 124 4 - -66.655 5.062 6.249 0.264 0.224 0.012 11.025 0.671 0.217 0.008 235.183 27.050 1650.928 104.661 12.126 3.442 -328.671 31.748 -130.053 21.804 -36.565 3.933 83 -84 34 11 - -66.442 5.053 14.336 0.479 0.056 0.023 24.830 1.011 0.057 0.010 253.232 30.608 1472.758 125.167 2.441 1.679 -290.510 38.258 -73.383 33.664 -36.105 2.888 84 -85 38 10 - -64.966 3.389 12.351 0.042 0.000 0.000 18.220 0.062 0.065 0.001 237.737 22.406 1463.210 47.096 18.877 2.622 -395.482 9.668 -186.266 30.185 -28.521 1.362 85 -86 62 10 - -64.964 5.998 7.746 0.112 0.004 0.007 15.178 0.486 0.093 0.004 271.487 9.093 1577.678 76.023 -0.556 4.196 -206.951 36.880 14.369 36.913 -50.167 1.787 86 -87 25 15 - -64.334 4.335 13.027 0.411 0.021 0.007 23.541 0.557 0.050 0.001 185.122 8.359 1583.560 19.045 -1.219 6.525 -176.576 111.800 -37.766 99.230 -46.312 12.209 87 -88 42 10 - -62.875 14.148 14.485 0.024 0.000 0.000 23.143 0.209 0.043 0.001 179.610 11.087 1721.772 71.776 12.319 3.484 -243.120 35.868 -108.042 47.241 -44.532 3.820 88 -89 84 10 - -62.085 1.306 14.514 0.132 0.000 0.000 22.149 0.316 0.046 0.001 296.997 14.696 1383.428 30.064 1.898 3.669 -292.144 12.479 -30.401 25.823 -35.254 1.893 89 -90 121 6 - -61.957 4.116 12.331 0.311 0.000 0.000 19.451 0.605 0.058 0.003 270.992 23.909 1274.112 82.006 4.029 2.380 -266.295 41.053 -35.130 24.369 -39.827 4.542 90 -91 36 11 - -61.811 2.141 14.445 0.058 0.000 0.000 22.627 0.070 0.045 0.000 270.514 14.399 1609.382 28.876 1.751 1.481 -254.673 33.427 -23.837 34.147 -39.679 5.666 91 -92 77 10 - -61.079 5.725 5.780 0.082 0.039 0.015 10.799 0.259 0.162 0.009 240.534 37.298 1483.005 50.398 -0.002 2.077 -182.518 25.073 9.390 46.237 -48.626 2.883 92 -93 117 6 - -60.777 11.533 9.801 0.191 0.013 0.007 21.006 0.640 0.059 0.004 246.636 8.427 1268.660 71.298 6.936 2.487 -314.050 22.326 -96.981 32.734 -29.567 6.294 93 -94 85 10 - -60.209 2.297 11.213 0.218 0.000 0.000 18.816 0.542 0.062 0.003 381.891 10.325 1459.902 67.889 -2.759 1.863 -266.267 22.682 73.237 24.125 -42.386 2.780 94 -95 126 4 - -59.397 3.161 13.514 0.088 0.000 0.000 20.613 0.206 0.052 0.001 340.899 11.341 1457.237 38.500 0.742 1.761 -285.606 3.678 18.186 8.403 -37.107 1.557 95 -96 63 10 - -59.291 7.296 9.014 0.111 0.000 0.000 16.822 0.663 0.077 0.005 280.676 22.422 1318.048 29.172 9.234 1.737 -325.262 28.578 -76.127 49.934 -31.541 1.854 96 -97 70 10 - -58.877 4.462 13.014 0.056 0.000 0.000 22.464 0.254 0.046 0.001 228.543 28.692 1422.508 65.438 -4.012 3.320 -200.927 16.946 -9.918 31.989 -37.534 1.424 97 -98 45 10 - -58.029 6.480 7.814 0.140 0.017 0.000 13.251 0.317 0.115 0.004 229.389 29.836 1404.900 46.790 11.103 1.955 -327.900 39.785 -125.001 51.497 -26.490 2.094 98 -99 68 10 - -55.807 3.727 16.510 0.066 0.000 0.000 25.624 0.263 0.036 0.001 318.869 16.264 1213.652 9.474 -5.589 2.224 -229.506 11.490 53.160 7.966 -36.203 3.035 99 -100 67 10 - -55.715 3.802 14.121 0.078 0.073 0.007 23.021 0.127 0.068 0.003 364.598 7.533 1424.082 38.150 0.216 3.221 -301.127 9.515 31.305 11.925 -32.166 2.426 100 -101 43 10 - -55.357 4.538 13.771 0.174 0.000 0.000 22.382 0.222 0.046 0.001 315.525 17.911 1224.170 95.586 15.578 3.930 -449.307 38.562 -146.408 51.664 -12.626 5.604 101 -102 60 10 - -55.224 0.578 14.483 0.242 0.000 0.000 26.049 0.668 0.036 0.002 237.155 10.847 1474.113 27.846 0.259 1.804 -152.957 35.644 35.591 28.921 -48.607 4.912 102 -103 59 10 - -55.141 2.610 14.717 0.093 0.034 0.000 23.704 0.289 0.053 0.001 298.384 26.262 1406.250 66.647 9.341 3.393 -316.841 23.707 -49.410 30.705 -30.952 4.042 103 -104 112 7 - -54.921 9.461 10.685 0.208 0.073 0.026 18.506 0.476 0.089 0.007 219.840 44.971 1521.922 81.424 5.709 7.046 -214.847 15.424 -34.651 49.783 -39.644 4.737 104 -105 5 22 - -54.314 4.331 12.385 0.086 0.021 0.014 22.595 0.342 0.053 0.006 233.002 17.524 1358.430 35.130 1.471 0.185 -207.591 22.952 -12.155 32.463 -37.567 1.570 105 -106 52 10 - -53.491 15.207 12.353 0.103 0.000 0.000 22.051 0.367 0.048 0.001 233.007 31.498 1414.820 102.212 3.750 1.618 -249.119 20.721 -46.830 57.818 -30.718 7.272 106 -107 111 7 - -53.239 5.226 13.791 0.212 0.000 0.000 23.428 0.626 0.043 0.002 268.166 12.080 1414.135 56.300 7.739 1.257 -222.832 3.164 2.106 14.206 -43.228 4.768 107 -108 54 10 - -52.971 3.488 14.200 0.033 0.000 0.000 23.847 0.087 0.041 0.000 334.087 9.226 1546.130 36.750 -6.005 1.905 -190.261 19.194 101.503 17.352 -42.322 4.900 108 -109 56 10 - -51.490 5.020 13.521 0.052 0.000 0.000 22.416 0.243 0.046 0.001 293.306 19.777 1477.102 25.522 5.609 1.461 -279.596 12.796 -16.800 25.540 -30.510 5.347 109 -110 118 6 - -51.117 4.561 12.365 0.051 0.000 0.000 23.714 0.346 0.043 0.001 278.889 18.649 1432.265 9.470 0.370 2.751 -214.671 17.337 27.776 25.570 -36.442 3.072 110 -111 107 9 - -49.501 5.059 14.835 0.038 0.000 0.000 23.410 0.057 0.042 0.000 344.941 19.284 1343.577 12.807 -3.153 1.679 -264.398 20.388 52.580 29.967 -27.963 9.609 111 -112 35 11 - -49.340 2.447 11.317 0.928 0.039 0.015 20.295 1.572 0.069 0.011 235.385 37.942 1409.605 87.748 4.069 3.360 -185.705 44.350 9.873 43.861 -39.807 8.325 112 -113 33 12 - -46.737 4.308 11.174 0.816 0.000 0.000 19.641 1.416 0.059 0.007 310.128 20.042 1238.068 110.488 4.568 2.574 -256.976 22.111 22.230 37.127 -30.923 2.384 113 -114 113 7 - -45.800 5.982 10.348 0.124 0.000 0.000 18.316 0.481 0.066 0.003 282.571 18.197 1311.367 56.380 4.791 1.847 -211.064 18.902 34.872 19.595 -36.635 3.931 114 -115 81 10 - -45.354 6.929 16.636 0.096 0.000 0.000 25.863 0.726 0.035 0.002 308.236 11.719 1275.400 52.716 -5.692 4.714 -181.522 49.756 92.533 51.322 -34.181 9.503 115 -116 49 10 - -44.705 1.959 10.852 0.035 0.000 0.000 16.845 0.062 0.074 0.000 358.788 5.112 1341.040 72.642 10.412 2.121 -347.849 36.059 -10.488 33.632 -21.427 6.467 116 -117 39 10 - -44.261 4.620 14.087 0.056 0.000 0.000 22.835 0.013 0.044 0.000 295.495 17.162 1234.227 27.363 4.174 3.430 -210.269 16.733 49.294 18.637 -35.931 4.941 117 -118 92 10 - -44.053 1.106 15.813 0.128 0.000 0.000 25.745 0.368 0.036 0.001 283.916 13.486 1275.445 30.036 -6.639 1.857 -143.568 20.594 103.256 10.722 -37.092 1.745 118 -119 114 7 - -43.996 7.676 13.036 0.151 0.000 0.000 21.041 0.248 0.051 0.001 318.293 22.689 1397.472 69.100 6.502 2.294 -242.837 58.413 41.697 35.569 -33.760 4.092 119 -120 127 4 - -42.868 12.804 10.782 0.266 0.021 0.007 18.935 0.277 0.070 0.003 378.484 32.539 1279.013 79.482 -2.333 3.174 -249.324 69.688 100.641 96.319 -28.519 2.196 120 -121 97 10 - -41.988 1.493 15.101 0.025 0.000 0.000 23.745 0.034 0.041 0.000 301.125 3.112 1269.653 33.464 -8.743 1.470 -129.712 11.741 133.997 11.234 -37.416 1.471 121 -122 71 10 - -41.763 0.892 8.507 0.097 0.039 0.015 14.685 0.147 0.107 0.006 239.057 9.121 1327.050 24.875 8.577 4.145 -218.493 30.755 -9.983 30.699 -30.547 4.870 122 -123 47 10 - -36.220 3.928 15.277 0.106 0.000 0.000 23.010 0.110 0.043 0.000 284.950 8.282 1175.388 69.795 5.948 1.847 -213.173 34.270 43.748 38.868 -28.029 3.546 123 -124 41 10 - -32.454 10.820 12.104 0.204 0.000 0.000 20.116 0.705 0.056 0.003 396.786 30.865 1066.531 89.515 12.815 3.725 -377.880 29.248 9.535 54.759 -9.372 2.922 124 -125 64 10 - -27.162 1.992 10.301 0.345 0.000 0.000 18.657 0.861 0.065 0.005 402.122 49.749 1030.695 25.469 4.338 0.861 -257.608 45.825 124.323 22.168 -20.191 4.685 125 -126 48 10 - -14.746 4.336 10.121 0.049 0.000 0.000 18.586 0.361 0.065 0.002 357.317 19.257 1018.395 44.464 1.525 1.784 -147.322 10.412 187.457 30.279 -22.539 2.476 126 -127 69 10 - -13.047 2.110 13.381 0.036 0.000 0.000 23.537 0.088 0.043 0.000 326.021 21.144 1056.715 43.823 -2.112 1.084 -98.899 7.148 203.364 15.655 -23.757 1.618 127 -
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 48 10 - -13.844 0.900 13.404 0.035 0.000 0.000 22.237 0.123 0.046 0.001 1166.617 117.075 1315.115 40.932 -9.803 2.749 -3.493 0.991 1256.845 137.335 93.721 19.507 1 -9 138 10 - -10.454 0.674 13.607 0.000 0.000 0.000 22.064 0.000 0.047 0.000 1204.100 0.000 1665.775 24.438 -3.712 0.820 -2.350 0.000 1224.210 0.000 22.460 0.002 2 -3 11 10 - -10.412 0.432 15.857 0.000 0.000 0.000 24.564 0.000 0.039 0.000 1384.043 0.004 1245.633 13.154 -6.563 0.429 -5.648 0.000 1419.910 0.000 41.513 0.001 3 -2 15 10 - -10.340 0.286 16.017 0.000 0.000 0.000 24.570 0.000 0.039 0.000 1333.983 0.004 1253.492 15.726 -1.585 0.327 -9.873 0.000 1355.403 0.004 31.294 0.002 4 -4 106 10 - -9.829 0.222 15.391 0.000 0.000 0.000 24.525 0.000 0.039 0.000 1552.235 0.005 1383.528 17.921 -7.734 0.159 -4.185 0.000 1588.340 0.000 40.293 0.003 5 -6 69 10 - -9.533 1.575 12.950 0.269 0.000 0.000 20.490 1.095 0.054 0.005 1276.435 67.292 1199.227 109.102 -8.069 0.667 -2.824 1.663 1332.377 61.750 58.763 7.369 6 -5 83 10 - -9.012 0.282 14.254 0.000 0.000 0.000 22.921 0.000 0.044 0.000 1276.120 0.010 1183.360 18.970 -3.152 0.213 -7.525 0.000 1342.325 0.005 73.727 0.006 7 -7 80 10 - -7.775 0.494 9.909 0.113 0.000 0.000 15.681 0.333 0.083 0.002 1542.185 35.608 1324.515 18.563 -4.813 0.320 -5.803 0.471 1602.840 32.869 66.456 2.271 8 -12 146 10 - -7.423 0.848 14.398 0.000 0.000 0.000 23.944 0.000 0.041 0.000 1442.685 0.005 1299.652 32.980 -7.305 1.130 -1.911 0.000 1476.980 0.000 36.202 0.001 9 -8 103 10 - -7.333 0.221 14.981 0.000 0.000 0.000 24.008 0.000 0.040 0.000 1543.658 0.004 1030.420 14.645 -10.900 0.124 -2.262 0.000 1610.960 0.000 69.566 0.001 10 -10 57 10 - -6.935 0.458 14.379 0.000 0.000 0.000 23.639 0.000 0.042 0.000 1222.643 0.004 1453.100 18.107 -6.100 0.353 0.439 0.000 1326.150 0.000 103.066 0.004 11 -19 143 10 - -6.913 0.973 15.057 0.055 0.000 0.000 23.498 0.016 0.042 0.000 1637.182 34.931 1089.412 27.157 -8.432 1.560 -4.361 0.102 1673.073 22.235 40.253 12.796 12 -11 46 10 - -6.612 0.137 7.774 0.000 0.138 0.000 16.369 0.000 0.129 0.000 1427.530 0.000 1264.045 12.113 -2.676 0.088 -6.756 0.000 1539.297 0.004 118.522 0.001 13 -13 74 10 - -6.451 0.515 12.795 0.110 0.000 0.000 21.337 0.231 0.050 0.001 1227.858 0.583 1320.807 16.754 -3.158 0.556 -2.694 0.171 1258.178 3.958 33.012 4.713 14 -14 40 10 - -6.057 0.570 14.552 0.000 0.000 0.000 23.108 0.000 0.043 0.000 1325.322 0.004 1317.838 17.495 -3.007 0.666 -3.439 0.000 1353.310 0.000 31.430 0.001 15 -17 54 10 - -5.998 0.121 12.456 0.000 0.000 0.000 19.696 0.000 0.057 0.000 1314.395 0.005 1310.680 23.796 -1.208 0.317 -5.261 0.000 1352.630 0.000 43.495 0.001 16 -15 32 10 - -5.964 0.425 14.596 0.115 0.000 0.000 23.358 0.122 0.043 0.000 1277.912 7.923 1285.055 82.743 -3.391 0.456 -2.900 0.806 1314.905 3.200 39.893 5.527 17 -16 12 10 - -5.777 0.104 13.551 0.000 0.017 0.000 23.658 0.000 0.048 0.000 1198.952 0.008 1149.155 9.000 -1.300 0.161 -5.170 0.000 1213.340 0.000 19.559 0.004 18 -18 124 10 - -5.691 0.215 14.454 0.000 0.017 0.000 23.355 0.000 0.048 0.000 1416.720 0.007 1374.565 18.449 -4.243 0.272 -2.310 0.000 1458.433 0.004 44.024 0.004 19 -21 56 10 - -5.412 0.747 15.959 0.000 0.000 0.000 25.689 0.001 0.036 0.000 1217.487 0.004 1439.070 19.619 -0.762 0.765 -2.668 0.000 1238.170 0.000 23.352 0.001 20 -29 104 10 - -5.375 0.124 13.872 0.000 0.000 0.000 20.781 0.000 0.052 0.000 1406.888 0.015 1020.282 14.806 -3.770 0.202 -6.285 0.000 1481.987 0.004 81.386 0.009 21 -20 49 10 - -5.250 0.321 15.360 0.000 0.000 0.000 23.819 0.000 0.041 0.000 1494.370 0.000 1010.559 24.070 -8.385 0.381 -2.102 0.000 1532.178 0.004 39.910 0.001 22 -23 14 10 - -4.989 1.157 10.910 0.000 0.000 0.000 21.035 0.000 0.053 0.000 1197.435 0.015 1289.438 22.539 -1.583 1.033 -2.975 0.000 1243.383 0.004 48.924 0.011 23 -24 44 10 - -4.755 0.228 11.912 0.000 0.034 0.000 22.612 0.000 0.058 0.000 1538.758 0.004 1152.660 13.464 -4.545 0.280 -4.549 0.000 1582.030 0.000 47.828 0.000 24 -25 29 10 - -4.750 0.679 10.824 0.420 0.009 0.009 18.404 1.004 0.068 0.006 1371.130 157.122 1214.263 97.267 -3.579 1.850 -3.541 1.647 1447.700 178.555 80.112 41.852 25 -22 23 10 - -4.670 0.217 13.640 0.000 0.000 0.000 20.717 0.000 0.052 0.000 1074.330 0.000 1374.390 4.007 0.869 0.209 -2.729 0.000 1090.750 0.000 19.152 0.001 26 -28 38 10 - 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5.488 0.197 12.076 0.000 0.052 0.000 22.598 0.000 0.064 0.000 1417.480 0.000 1486.365 17.352 4.645 0.302 1.068 0.000 1464.918 0.004 46.366 0.002 97 -95 78 10 - 5.560 0.457 16.706 0.008 0.000 0.000 25.451 0.140 0.036 0.000 1842.725 31.353 944.442 50.103 0.728 0.730 -4.713 0.093 1894.173 29.224 56.160 2.221 98 -94 24 10 - 5.636 0.329 8.495 0.000 0.034 0.000 14.545 0.000 0.106 0.000 1438.640 0.007 1052.645 15.771 1.940 0.237 -0.598 0.000 1481.457 0.004 43.412 0.003 99 -98 82 10 - 5.912 1.108 9.062 0.000 0.000 0.000 15.621 0.000 0.085 0.000 1579.757 0.022 1004.099 15.653 5.426 1.168 -6.184 0.000 1665.025 0.011 91.451 0.016 100 -100 102 10 - 6.178 0.304 7.429 0.009 0.000 0.000 13.326 0.125 0.110 0.002 1579.557 20.718 876.049 15.882 3.925 2.192 -5.419 1.923 1637.915 20.785 63.778 1.855 101 -101 73 10 - 6.491 1.286 5.274 1.121 0.112 0.009 9.331 1.965 0.220 0.043 1572.305 148.870 1132.720 36.265 8.968 1.519 -7.591 0.267 1636.495 138.775 71.783 10.363 102 -97 95 10 - 6.500 0.357 14.891 0.012 0.000 0.000 22.738 0.016 0.044 0.000 1324.383 41.675 1347.323 23.736 7.302 0.979 -1.935 0.308 1458.680 26.090 136.237 15.891 103 -103 16 10 - 6.598 0.717 13.543 0.000 0.000 0.000 25.565 0.000 0.037 0.000 1435.965 0.023 965.739 17.475 4.647 0.755 -3.499 0.000 1507.220 0.007 74.752 0.014 104 -113 131 10 - 6.748 0.706 11.362 0.097 0.000 0.000 21.172 0.035 0.052 0.000 1272.642 14.128 1152.102 20.187 2.181 0.890 2.808 0.199 1330.730 20.670 55.278 6.741 105 -99 26 10 - 6.777 0.221 14.549 0.000 0.034 0.000 22.246 0.000 0.057 0.000 1337.785 0.005 1237.665 9.368 12.623 0.281 -7.317 0.000 1377.372 0.004 46.903 0.001 106 -111 140 10 - 6.779 0.467 13.408 0.000 0.000 0.000 21.842 0.000 0.048 0.000 1701.625 0.009 1130.092 12.459 7.382 0.510 -6.848 0.000 1747.780 0.000 53.005 0.004 107 -102 70 10 - 6.859 0.368 14.104 0.000 0.034 0.000 23.831 0.000 0.053 0.000 1421.310 0.007 1245.168 28.046 7.072 0.205 -2.606 0.000 1481.862 0.004 63.157 0.003 108 -104 128 10 - 6.979 0.272 7.750 0.000 0.000 0.000 15.894 0.000 0.086 0.000 1565.898 0.004 1165.102 17.917 2.422 0.296 0.114 0.000 1609.468 0.004 43.454 0.002 109 -105 37 10 - 7.074 0.273 11.212 0.000 0.017 0.000 19.176 0.000 0.066 0.000 1435.567 0.004 1069.815 30.137 5.507 0.352 -2.716 0.000 1495.420 0.000 62.566 0.003 110 -107 63 10 - 7.255 0.593 12.974 0.000 0.017 0.000 23.438 0.000 0.049 0.000 1090.135 0.005 1330.148 10.453 2.694 0.583 6.481 0.000 1144.622 0.004 48.006 0.003 111 -110 141 10 - 7.577 0.087 14.993 0.000 0.000 0.000 26.718 0.000 0.034 0.000 1348.737 0.004 1125.025 15.059 3.369 0.154 1.314 0.001 1415.803 0.004 65.755 0.004 112 -112 39 10 - 7.717 1.437 13.076 0.000 0.034 0.000 21.292 0.000 0.062 0.000 1418.793 0.004 1031.657 36.860 7.200 1.546 -3.905 0.000 1469.900 0.000 55.008 0.004 113 -115 87 10 - 7.749 0.454 13.090 0.000 0.000 0.000 23.222 0.000 0.044 0.000 1476.158 0.011 1272.345 14.120 8.203 0.331 -3.187 0.001 1542.362 0.004 69.394 0.007 114 -114 19 10 - 8.156 0.557 9.610 0.000 0.000 0.000 14.939 0.000 0.089 0.000 1217.220 0.000 1305.247 14.882 12.752 0.458 -4.164 0.000 1257.840 0.000 44.788 0.001 115 -121 145 10 - 8.234 0.328 10.233 0.000 0.000 0.000 18.503 0.000 0.065 0.000 1947.057 0.004 867.776 31.685 3.537 0.526 -6.582 0.000 1988.970 0.000 48.495 0.001 116 -119 136 10 - 8.348 0.416 14.705 0.000 0.034 0.000 25.924 0.000 0.047 0.000 1386.100 0.007 1184.423 17.051 4.270 0.435 1.673 0.001 1426.608 0.004 38.834 0.003 117 -122 108 10 - 8.381 0.460 14.681 0.085 0.000 0.000 23.063 0.127 0.043 0.001 1232.655 19.625 1256.318 24.006 9.329 0.902 -1.541 0.488 1314.030 2.905 82.916 16.234 118 -118 59 10 - 8.410 0.499 14.607 0.000 0.000 0.000 22.480 0.000 0.045 0.000 1369.202 0.004 1270.800 13.880 9.935 0.543 -3.034 0.000 1418.590 0.000 52.421 0.003 119 -117 6 10 - 8.515 0.753 15.939 0.155 0.000 0.000 24.412 0.259 0.039 0.000 1449.795 8.149 1040.126 30.813 3.445 1.306 -0.055 0.320 1552.490 52.943 102.751 44.470 120 -116 25 10 - 8.519 0.328 14.667 0.000 0.034 0.000 24.106 0.000 0.052 0.000 1754.810 0.000 914.418 13.386 7.544 0.397 -8.388 0.000 1842.332 0.004 95.912 0.001 121 -123 67 10 - 8.816 0.536 10.832 0.000 0.000 0.000 18.596 0.000 0.064 0.000 1463.985 0.005 1034.602 12.469 6.496 0.480 -2.527 0.000 1516.725 0.005 55.269 0.003 122 -120 109 10 - 8.886 0.324 13.897 0.000 0.000 0.000 22.887 0.000 0.044 0.000 1739.505 0.005 1021.742 10.450 10.462 0.263 -9.293 0.000 1784.128 0.004 53.917 0.000 123 -126 116 10 - 9.037 0.868 13.219 0.286 0.000 0.000 25.431 1.049 0.038 0.003 1717.020 26.917 1053.345 24.494 5.122 1.014 -4.705 1.799 1910.625 57.426 198.310 32.310 124 -127 110 10 - 9.102 0.544 12.595 0.000 0.000 0.000 20.109 0.000 0.055 0.000 1458.440 0.000 1326.795 8.218 10.158 0.491 -2.662 0.000 1484.760 0.000 28.977 0.001 125 -128 94 10 - 9.273 0.182 11.377 0.000 0.000 0.000 20.295 0.000 0.055 0.000 1350.680 0.007 1263.432 15.692 4.961 0.186 3.037 0.000 1394.020 0.000 40.300 0.003 126 -124 13 10 - 9.465 0.169 13.992 0.000 0.000 0.000 23.157 0.000 0.043 0.000 1146.433 0.013 1120.465 15.556 10.227 0.270 -1.592 0.000 1201.948 0.004 57.108 0.007 127 -130 45 10 - 9.550 0.386 9.814 0.000 0.017 0.000 16.010 0.001 0.087 0.000 1554.797 0.004 1074.615 29.539 8.300 0.409 -4.112 0.000 1606.680 0.000 55.995 0.002 128 -135 152 10 - 9.610 0.259 15.446 0.000 0.000 0.000 23.011 0.000 0.043 0.000 1665.850 0.000 946.076 8.652 5.728 0.268 -4.098 0.000 1739.930 0.000 78.180 0.001 129 -125 93 10 - 9.689 0.119 13.345 0.366 0.000 0.000 23.264 0.111 0.043 0.000 1423.375 94.377 1040.887 98.513 5.578 0.171 -0.319 2.153 1483.550 109.385 60.492 17.162 130 -133 115 10 - 9.787 0.539 13.502 0.000 0.034 0.000 22.814 0.000 0.056 0.000 1637.325 0.005 1220.587 16.638 9.947 0.458 -4.921 0.001 1691.818 0.004 59.413 0.004 131 -131 114 10 - 9.826 0.114 13.465 0.000 0.000 0.000 20.399 0.000 0.053 0.000 1818.070 0.000 1053.033 18.751 9.771 0.258 -8.246 0.000 1874.900 0.000 65.072 0.001 132 -129 3 10 - 10.018 0.127 14.428 0.000 0.034 0.000 22.032 0.000 0.058 0.000 1549.895 0.005 1118.065 42.148 12.787 0.454 -7.537 0.001 1587.460 0.000 45.103 0.003 133 -132 119 10 - 10.143 0.318 14.591 0.000 0.000 0.000 23.723 0.000 0.041 0.000 2030.400 0.000 983.656 8.263 4.708 0.325 -5.477 0.000 2069.310 0.000 44.387 0.001 134 -136 150 10 - 10.431 0.253 14.509 0.338 0.073 0.007 23.445 0.046 0.067 0.003 2007.825 335.507 1296.773 80.914 10.058 1.357 -7.287 5.448 2055.438 339.336 54.902 9.277 135 -150 137 10 - 10.486 0.981 13.674 0.276 0.026 0.009 21.535 0.203 0.057 0.004 1802.435 67.949 850.777 19.785 5.939 1.057 -6.012 0.908 1900.545 36.937 104.120 32.144 136 -134 96 10 - 10.666 0.361 14.905 0.000 0.000 0.000 23.611 0.000 0.042 0.000 1180.222 0.008 1197.192 20.594 9.497 0.535 0.430 0.001 1271.465 0.005 90.810 0.004 137 -145 130 10 - 10.686 0.215 10.825 0.001 0.069 0.000 18.924 0.000 0.085 0.000 1267.947 0.004 1066.520 11.839 6.859 0.271 0.757 0.000 1374.340 0.000 105.638 0.005 138 -137 97 10 - 10.744 0.356 11.161 0.121 0.000 0.000 17.162 0.102 0.071 0.000 1500.715 119.809 1067.945 5.794 12.386 1.759 -6.461 0.315 1543.383 131.415 49.125 11.293 139 -138 89 10 - 10.796 0.255 8.739 0.000 0.017 0.000 14.675 0.000 0.099 0.000 1540.630 0.000 1060.565 11.528 12.264 0.289 -6.895 0.000 1596.385 0.005 62.650 0.001 140 -141 122 10 - 10.930 0.437 14.198 0.141 0.000 0.000 23.447 0.395 0.043 0.001 1390.735 77.045 1002.527 29.545 8.394 0.193 -1.835 0.884 1437.828 84.728 48.932 8.567 141 -139 50 10 - 10.969 0.619 10.602 0.000 0.000 0.000 18.906 0.000 0.063 0.000 1799.200 0.000 766.240 37.212 1.470 0.550 -1.686 0.000 1882.990 0.000 85.470 0.001 142 -147 120 10 - 11.521 0.159 4.285 0.000 0.121 0.000 8.527 0.000 0.243 0.000 1526.737 0.004 1528.830 15.598 15.387 0.301 -5.049 0.000 1642.110 0.000 120.418 0.003 143 -140 58 10 - 11.638 0.280 11.900 0.000 0.017 0.000 18.863 0.000 0.067 0.000 1899.500 0.000 1081.518 33.994 5.711 0.435 -2.672 0.000 1938.750 0.000 41.925 0.000 144 -142 31 10 - 12.238 0.461 13.303 0.000 0.000 0.000 21.021 0.000 0.051 0.000 1406.755 0.009 1096.230 19.810 11.836 0.584 -3.236 0.000 1456.838 0.004 53.317 0.006 145 -143 151 10 - 12.714 0.279 7.749 0.000 0.000 0.000 13.417 0.000 0.108 0.000 1964.388 0.004 896.694 19.473 6.427 0.348 -4.948 0.001 2015.227 0.004 55.788 0.002 146 -144 129 10 - 12.743 0.384 13.927 0.169 0.000 0.000 20.877 0.157 0.051 0.001 1557.322 37.718 937.363 18.414 7.410 1.237 -1.420 1.619 1611.295 33.980 55.392 2.120 147 -146 132 10 - 12.926 0.195 13.916 0.000 0.000 0.000 22.376 0.000 0.046 0.000 1836.933 0.004 878.615 11.559 11.218 0.259 -8.685 0.000 1909.210 0.000 80.959 0.002 148 -148 99 10 - 13.625 0.374 9.809 0.371 0.000 0.000 21.326 1.560 0.054 0.006 1819.340 7.577 948.136 21.599 10.081 0.705 -5.718 0.542 1868.615 8.389 54.990 1.051 149 -149 86 10 - 14.127 0.142 12.241 0.000 0.000 0.000 20.385 0.001 0.054 0.000 1876.680 0.000 793.395 14.295 7.999 0.164 -5.168 0.000 1917.780 0.000 46.262 0.001 150 -151 139 10 - 14.803 0.643 14.398 0.000 0.000 0.000 22.842 0.000 0.044 0.000 1558.020 0.007 877.430 6.677 7.620 0.660 -0.349 0.000 1630.265 0.005 72.595 0.004 151 -152 92 10 - 16.300 0.353 12.552 0.000 0.000 0.000 18.676 0.000 0.062 0.000 1163.448 0.008 1243.952 7.434 15.781 0.397 1.090 0.000 1187.940 0.000 23.400 0.002 152 --
- After rigid body docking the first acceptable cluster is at rank 41. After refinement it scores at the top with score significantly better than the second-ranked cluster! -
--============================================== -== ./runs/scenario1-surface//4_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 2 out of 152 -Total number of medium or better clusters: 1 out of 152 -Total number of high quality clusters: 0 out of 152 + # execute + haddock3-+ {% endhighlight %} +
-First acceptable cluster - rank: 43 i-RMSD: 2.535 Fnat: 0.345 DockQ: 0.423 -First medium cluster - rank: 54 i-RMSD: 1.684 Fnat: 0.526 DockQ: 0.622 -Best cluster - rank: 54 i-RMSD: 1.684 Fnat: 0.526 DockQ: 0.622 -============================================== -== ./runs/scenario1-surface//9_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 2 out of 127 -Total number of medium or better clusters: 1 out of 127 -Total number of high quality clusters: 0 out of 127 -First acceptable cluster - rank: 1 i-RMSD: 1.678 Fnat: 0.733 DockQ: 0.669 -First medium cluster - rank: 1 i-RMSD: 1.678 Fnat: 0.733 DockQ: 0.669 -Best cluster - rank: 1 i-RMSD: 1.678 Fnat: 0.733 DockQ: 0.669 -
-============================================== -== ./runs/scenario1-surface/4_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 20 out of 1520 -Total number of medium or better models: 8 out of 1520 -Total number of high quality models: 0 out of 1520 +-+ Exection in MPI mode expand_more +
-First acceptable model - rank: 344 i-RMSD: 2.535 Fnat: 0.345 DockQ: 0.423 -First medium model - rank: 491 i-RMSD: 1.282 Fnat: 0.707 DockQ: 0.738 -Best model - rank: 559 i-RMSD: 1.282 Fnat: 0.707 DockQ: 0.738 -============================================== -== ./runs/scenario1-surface/9_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 22 out of 1475 -Total number of medium or better models: 13 out of 1475 -Total number of high quality models: 0 out of 1475 -First acceptable model - rank: 1 i-RMSD: 1.518 Fnat: 0.810 DockQ: 0.722 -First medium model - rank: 1 i-RMSD: 1.518 Fnat: 0.810 DockQ: 0.722 -Best model - rank: 17 i-RMSD: 1.197 Fnat: 0.879 DockQ: 0.811 -
- In terms of iRMSD values we only observe very small differences in the best models, but the change in ranking is impressive! - The fraction of native contacts and the DockQ scores are however improving much more after flexible refinement. - All this will of course depend on how different are the bound and unbound conformations and the amount of data - used to drive the docking process. In general, from our experience, the more and better data at hand, - the larger the conformational changes that can be induced. -
-- This is clearly not the case. The scoring function is not perfect, but does a reasonable job in ranking models of acceptable or better quality on top in this case. -
+ # go to the run directory + # edit if needed to specify the correct location + cd $HOME/HADDOCK3-antibody-antigen + + # execute + haddock3 \+ model md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq rmsd cluster_id cluster_ranking model-cluster_ranking air angles bonds bsa cdih coup dani desolv dihe elec improper rdcs rg sym total vdw vean xpcs +../09_seletopclusts/cluster_1_model_1.pdb - 1 -140.319 0.908 0.897 2.205 1.451 0.855 1.016 3 1 1 133.760 0.000 0.000 2010.880 0.000 0.000 0.000 7.010 0.000 -605.174 0.000 0.000 0.000 0.000 -511.084 -39.671 0.000 0.000 +../09_seletopclusts/cluster_1_model_2.pdb - 2 -137.507 0.879 0.948 1.951 1.354 0.881 0.989 3 1 2 189.059 0.000 0.000 1913.390 0.000 0.000 0.000 3.243 0.000 -521.143 0.000 0.000 0.000 0.000 -387.512 -55.428 0.000 0.000 +../09_seletopclusts/cluster_1_model_3.pdb - 3 -126.481 1.052 0.914 3.038 1.958 0.824 1.293 3 1 3 127.044 0.000 0.000 1816.780 0.000 0.000 0.000 -2.884 0.000 -426.677 0.000 0.000 0.000 0.000 -350.599 -50.966 0.000 0.000 +../09_seletopclusts/cluster_1_model_4.pdb - 4 -102.227 1.334 0.793 2.331 2.292 0.760 1.341 3 1 4 128.628 0.000 0.000 1837.970 0.000 0.000 0.000 12.344 0.000 -410.669 0.000 0.000 0.000 0.000 -327.341 -45.299 0.000 0.000 +../09_seletopclusts/cluster_2_model_1.pdb - 5 -102.077 14.789 0.103 23.359 22.787 0.077 14.405 2 2 1 163.844 0.000 0.000 1888.310 0.000 0.000 0.000 2.575 0.000 -348.025 0.000 0.000 0.000 0.000 -235.613 -51.431 0.000 0.000 +... ++ +If clustering was performed prior to calling the `caprieval` module, the `capri_ss.tsv` file will also contain information about to which cluster the model belongs to and its ranking within the cluster. + +The relevant statistics are: + +* **score**: *the HADDOCK score (arbitrary units)* +* **irmsd**: *the interface RMSD, calculated over the interfaces the molecules* +* **fnat**: *the fraction of native contacts* +* **lrmsd**: *the ligand RMSD, calculated on the ligand after fitting on the receptor (1st component)* +* **ilrmsd**: *the interface-ligand RMSD, calculated over the interface of the ligand after fitting on the interface of the receptor (more relevant for small ligands for example)* +* **dockq**: *the DockQ score, which is a combination of irmsd, lrmsd and fnat and provides a continuous scale between 1 (exactly equal to reference) and 0* + +Various other terms are also reported including: + +* **bsa**: *the buried surface area (in squared angstroms)* +* **elec**: *the intermolecular electrostatic energy* +* **vdw**: *the intermolecular van der Waals energy* +* **desolv**: *the desolvation energy* + + +The iRMSD, lRMSD and Fnat metrics are the ones used in the blind protein-protein prediction experiment [CAPRI](https://capri.ebi.ac.uk/){:target="_blank"} (Critical PRediction of Interactions). + +In CAPRI the quality of a model is defined as (for protein-protein complexes): + +* **acceptable model**: i-RMSD < 4Å or l-RMSD < 10Å and Fnat > 0.1 (0.23 < DOCKQ < 0.49) +* **medium quality model**: i-RMSD < 2Å or l-RMSD < 5Å and Fnat > 0.3 (0.49 < DOCKQ < 0.8) +* **high quality model**: i-RMSD < 1Å or l-RMSD < 1Å and Fnat > 0.5 (DOCKQ > 0.8) + + +Based on these CAPRI criteria, what is the quality of the best model listed above (_cluster_1_model_1.pdb_)? -Models statistics: +In case where the `caprieval` module is called after a clustering step, an additional `capri_clt.tsv` file will be present in the directory. +This file contains the cluster ranking and score statistics, averaged over the minimum number of models defined for clustering +(4 by default), with their corresponding standard deviations. E.g.: -* [iRMSD versus HADDOCK score](plots/scenario1-surface/irmsd_score.html){:target="_blank"} -* [DockQ versus HADDOCK score](plots/scenario1-surface/dockq_score.html){:target="_blank"} -* [DockQ versus van der Waals energy](plots/scenario1-surface/dockq_vdw.html){:target="_blank"} -* [DockQ versus electrostatic energy](plots/scenario1-surface/dockq_elec.html){:target="_blank"} -* [DockQ versus ambiguous restraints energy](plots/scenario1-surface/dockq_air.html){:target="_blank"} -* [DockQ versus desolvation energy](plots/scenario1-surface/dockq_desolv.html){:target="_blank"} +
+cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std ilrmsd ilrmsd_std rmsd rmsd_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank + 1 3 4 - -126.634 15.010 1.044 0.180 0.888 0.058 2.381 0.403 0.830 0.045 1.764 0.382 1.160 0.159 144.623 25.775 1894.755 76.054 4.928 5.550 -490.916 78.318 -394.134 70.848 -47.841 5.927 1 + 2 2 4 - -98.425 2.624 14.572 0.524 0.095 0.009 23.293 0.233 0.074 0.002 22.593 0.371 14.300 0.194 159.227 8.415 1781.358 114.002 2.706 2.898 -340.312 32.395 -230.077 26.771 -48.992 5.015 2 + 3 1 4 - -91.137 1.918 10.249 0.530 0.056 0.007 19.692 0.505 0.078 0.005 18.190 0.649 10.554 0.495 173.598 42.201 1441.505 77.296 4.873 4.329 -389.212 18.467 -251.141 40.747 -35.527 5.170 3 +... +-Cluster statistics (distributions of values per cluster ordered according to their HADDOCK rank): -* [HADDOCK scores](plots/scenario1-surface/score_clt.html){:target="_blank"} -* [van der Waals energies](plots/scenario1-surface/vdw_clt.html){:target="_blank"} -* [electrostatic energies](plots/scenario1-surface/elec_clt.html){:target="_blank"} -* [ambiguous restraints energies](plots/scenario1-surface/air_clt.html){:target="_blank"} -* [desolvation energies](plots/scenario1-surface/desolv_clt.html){:target="_blank"} +In this file you find the cluster rank (which corresponds to the naming of the clusters in the previous `seletop` directory), the cluster ID (which is related to the size of the cluster, 1 being always the largest cluster), the number of models (n) in the cluster and the corresponding statistics (averages + standard deviations). The corresponding cluster PDB files will be found in the preceeding `09_seletopclusts` directory. +While these simple text files can be easily checked from the command line already, they might be cumbersome to read. +For that reason, we have developed a post-processing analysis that automatically generates html reports for all `caprieval` steps in the workflow. +These are located in the respective `analysis/XX_caprieval` directories and can be viewed using your favorite web browser. -For this antibody-antigen case, which of the score component is correlating best with the quality of the models?.
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 7 10 - -138.617 3.623 1.302 0.095 0.759 0.042 3.654 0.845 0.723 0.042 106.923 15.255 2007.338 29.881 4.998 2.064 -535.045 31.312 -475.421 23.968 -47.299 4.337 1 -2 2 17 - -114.732 8.026 14.934 0.048 0.069 0.000 23.085 0.282 0.066 0.001 160.053 15.937 1925.930 68.200 4.355 4.005 -383.893 65.058 -282.153 44.813 -58.313 7.769 2 -3 6 10 - -94.885 3.118 5.158 0.190 0.142 0.014 12.677 0.697 0.177 0.010 195.712 3.139 1678.185 4.775 8.844 0.929 -326.919 4.813 -189.123 5.020 -57.916 4.522 3 -4 1 20 - -85.733 5.280 8.889 0.683 0.116 0.049 17.160 0.949 0.115 0.023 212.853 21.459 1542.527 57.393 6.435 2.591 -328.754 32.768 -163.602 15.475 -47.702 7.750 4 -5 5 10 - -77.835 3.974 4.405 0.344 0.207 0.086 10.394 1.197 0.239 0.050 177.651 29.362 1644.388 54.484 11.269 2.084 -365.089 43.590 -221.289 30.831 -33.852 8.784 5 -6 4 10 - -69.846 2.776 6.854 0.076 0.142 0.007 14.212 0.179 0.150 0.004 305.336 14.743 1491.412 41.939 4.152 1.676 -302.880 31.549 -41.500 23.024 -43.955 4.249 6 -7 3 10 - -52.284 6.453 4.930 0.161 0.125 0.033 12.482 0.704 0.176 0.018 356.568 28.814 1228.580 69.244 5.359 1.823 -299.986 38.202 23.279 48.112 -33.303 2.374 7 --
+-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 1 10 - -7.065 0.204 14.798 0.000 0.069 0.000 23.304 0.000 0.066 0.000 800.213 0.006 1705.220 15.183 3.034 0.336 -1.039 0.001 798.194 0.002 -0.980 0.003 1 -2 4 10 - -4.905 0.322 1.247 0.000 0.690 0.000 2.258 0.000 0.738 0.000 830.946 0.006 1750.490 10.557 12.935 0.295 -8.707 0.001 828.476 0.002 6.237 0.004 2 -3 5 10 - -3.218 0.321 12.988 0.000 0.069 0.000 21.389 0.000 0.073 0.000 1250.720 0.007 1281.875 12.910 -2.070 0.282 -1.521 0.000 1317.727 0.004 68.529 0.003 3 -4 6 10 - -2.754 0.136 5.104 0.000 0.138 0.000 12.428 0.000 0.179 0.000 1109.805 0.005 1381.213 18.673 3.933 0.265 -4.214 0.000 1129.680 0.000 24.088 0.003 4 -5 3 10 - -2.534 0.181 8.639 0.000 0.121 0.000 16.823 0.000 0.118 0.000 1115.398 0.004 1139.723 20.158 4.226 0.286 -6.851 0.000 1141.970 0.000 33.428 0.001 5 -6 2 10 - 0.099 0.314 9.991 0.000 0.052 0.000 18.505 0.001 0.083 0.000 1069.392 0.061 1148.727 27.538 7.879 0.518 -7.227 0.001 1086.138 0.023 23.972 0.039 6 -7 8 10 - 3.994 0.158 4.033 0.001 0.121 0.000 10.360 0.000 0.215 0.000 1343.840 0.000 1164.535 21.845 7.108 0.196 -5.423 0.000 1390.040 0.000 51.623 0.001 7 -8 9 10 - 4.619 0.267 7.100 0.000 0.121 0.000 14.167 0.000 0.143 0.000 1523.870 0.007 1134.912 25.058 6.563 0.123 -6.186 0.000 1552.900 0.000 35.217 0.004 8 -9 7 10 - 10.174 0.445 4.776 0.000 0.086 0.000 11.416 0.000 0.178 0.000 1954.290 0.000 937.232 7.379 10.179 0.376 -10.952 0.000 2021.017 0.004 77.678 0.002 9 --
+- After rigid body docking the first acceptable cluster is at rank 2. After refinement it scores at the top with score significantly better than the second-ranked cluster. -
-
+============================================== -== ./runs/scenario2a-NMR-epitope-pass/4_caprieval/capri_clt.tsv +== runs/run1/02_caprieval/capri_ss.tsv ============================================== -Total number of acceptable or better clusters: 1 out of 9 -Total number of medium or better clusters: 1 out of 9 -Total number of high quality clusters: 0 out of 9 +Total number of acceptable or better models: 25 out of 100 +Total number of medium or better models: 15 out of 100 +Total number of high quality models: 1 out of 100 -First acceptable cluster - rank: 2 i-RMSD: 1.247 Fnat: 0.690 DockQ: 0.738 -First medium cluster - rank: 2 i-RMSD: 1.247 Fnat: 0.690 DockQ: 0.738 -Best cluster - rank: 2 i-RMSD: 1.247 Fnat: 0.690 DockQ: 0.738 +First acceptable model - rank: 1 i-RMSD: 1.196 Fnat: 0.672 DockQ: 0.741 +First medium model - rank: 1 i-RMSD: 1.196 Fnat: 0.672 DockQ: 0.741 +Best model - rank: 17 i-RMSD: 0.982 Fnat: 0.759 DockQ: 0.774 ============================================== -== ./runs/scenario2a-NMR-epitope-pass/9_caprieval/capri_clt.tsv +== runs/run1/05_caprieval/capri_ss.tsv ============================================== -Total number of acceptable or better clusters: 1 out of 7 -Total number of medium or better clusters: 1 out of 7 -Total number of high quality clusters: 0 out of 7 - -First acceptable cluster - rank: 1 i-RMSD: 1.302 Fnat: 0.759 DockQ: 0.723 -First medium cluster - rank: 1 i-RMSD: 1.302 Fnat: 0.759 DockQ: 0.723 -Best cluster - rank: 1 i-RMSD: 1.302 Fnat: 0.759 DockQ: 0.723 --
+First acceptable model - rank: 1 i-RMSD: 0.992 Fnat: 0.897 DockQ: 0.834 +First medium model - rank: 1 i-RMSD: 0.992 Fnat: 0.897 DockQ: 0.834 +Best model - rank: 11 i-RMSD: 0.789 Fnat: 0.776 DockQ: 0.842 ============================================== -== ./runs/scenario2a-NMR-epitope-pass/4_caprieval/capri_ss.tsv +== runs/run1/07_caprieval/capri_ss.tsv ============================================== -Total number of acceptable or better models: 10 out of 90 -Total number of medium or better models: 10 out of 90 -Total number of high quality models: 1 out of 90 +Total number of acceptable or better models: 14 out of 40 +Total number of medium or better models: 14 out of 40 +Total number of high quality models: 3 out of 40 -First acceptable model - rank: 11 i-RMSD: 1.247 Fnat: 0.690 DockQ: 0.738 -First medium model - rank: 11 i-RMSD: 1.247 Fnat: 0.690 DockQ: 0.738 -Best model - rank: 16 i-RMSD: 0.980 Fnat: 0.586 DockQ: 0.726 +First acceptable model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +First medium model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +Best model - rank: 11 i-RMSD: 0.841 Fnat: 0.897 DockQ: 0.875 ============================================== -== ./runs/scenario2a-NMR-epitope-pass/9_caprieval/capri_ss.tsv +== runs/run1/10_caprieval/capri_ss.tsv ============================================== -Total number of acceptable or better models: 12 out of 87 -Total number of medium or better models: 10 out of 87 -Total number of high quality models: 0 out of 87 +Total number of acceptable or better models: 4 out of 12 +Total number of medium or better models: 4 out of 12 +Total number of high quality models: 1 out of 12 -First acceptable model - rank: 1 i-RMSD: 1.300 Fnat: 0.793 DockQ: 0.730 -First medium model - rank: 1 i-RMSD: 1.300 Fnat: 0.793 DockQ: 0.730 -Best model - rank: 5 i-RMSD: 1.029 Fnat: 0.810 DockQ: 0.811 +First acceptable model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +First medium model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +Best model - rank: 3 i-RMSD: 0.908 Fnat: 0.897 DockQ: 0.855
- In terms of iRMSD values we only observe very small differences with a slight increase. - The fraction of native contacts and the DockQ scores are however improving much more after flexible refinement. - All this will of course depend on how different are the bound and unbound conformations and the amount of data - used to drive the docking process. In general, from our experience, the more and better data at hand, - the larger the conformational changes that can be induced. + In terms of iRMSD values, we only observe very small differences in the best model. + The fraction of native contacts and the DockQ scores are however improving much more after flexible refinement but increases again slightly after final minimisation. + All this will of course depend on how different are the bound and unbound conformations and the amount of data used to drive the docking process. + In general, from our experience, the more and better data at hand, the larger the conformational changes that can be induced.
- This is clearly not the case. The scoring function is not perfect, but does a reasonable job in ranking models of acceptable or better quality on top in this case. + This is not the case. The scoring function is not perfect, but does a reasonable job at ranking models of acceptable or better quality on top in this case.
Top-ranked model of the top cluster (cluster1_model_1) superimposed onto the reference crystal structure (in yellow)
+
+ 
+ +########################################################## +# `alascan` results for 4G6M_matched_haddock.pdb +# +# native score = -145.5891 +# +# z_score is calculated with respect to the other residues +########################################################## +chain res ori_resname end_resname score vdw elec desolv bsa delta_score delta_vdw delta_elec delta_desolv delta_bsa z_score +A 212 LYS ALA -136.33 -66.16 -367.66 3.37 1660.53 -9.26 2.52 -75.12 3.24 37.57 -0.48 +A 103 ASP ALA -129.64 -59.93 -365.23 3.34 1677.97 -15.95 -3.71 -77.56 3.27 20.13 -1.41 +A 54 TRP ALA -138.18 -58.34 -435.53 7.27 1690.80 -7.41 -5.30 -7.26 -0.66 7.30 -0.22 +A 32 SER ALA -143.66 -60.55 -447.37 6.36 1691.72 -1.93 -3.09 4.59 0.24 6.38 0.55 +A 58 ASP ALA -121.65 -63.49 -306.77 3.20 1639.20 -23.94 -0.15 -136.01 3.41 58.90 -2.52 +A 33 GLY ALA -148.50 -61.56 -473.22 7.71 1693.18 2.91 -2.08 30.43 -1.10 4.92 1.22 +... ++ + +Can you identify the most enriching/depleting mutation of each chain? +Take a look at _scan_clt_-.tsv_ and open its visualisation _scan_clt_-.html_ in the web browser. + + +You can use an additional script `/scripts/get-alascan-extrema.sh` to check your answer: + +bash scripts/get-alascan-extrema.sh run-energetics-alascan/1_alascan/scan_4G6M_matched_haddock.tsv + + +Mutation of the residue ASP58 turned out to be the most depleting within chain A. +Let us visualise it in PyMol to analyse its contribution to the binding: + +File menu -> Open -> 4G6M_matched.pdb + + +Display ASP58 as sticks and colour it by atom: + +util.cbc
+ 
+ 
++ 4G6K_abb_clean RMSD = 0.428 Å + 4G6K_af2_clean RMSD = 0.765 Å ++
+ 4G6K_abb_clean RMSD = 0.330 Å + 4G6K_af2_clean RMSD = 0.675 Å + 4G6K_clean RMSD = 0.393 Å ++
+============================================== +== run1/10_caprieval/capri_clt.tsv +============================================== +Total number of acceptable or better clusters: 1 out of 3 +Total number of medium or better clusters: 1 out of 3 +Total number of high quality clusters: 0 out of 3 + +First acceptable cluster - rank: 1 i-RMSD: 1.049 Fnat: 0.879 DockQ: 0.815 +First medium cluster - rank: 1 i-RMSD: 1.049 Fnat: 0.879 DockQ: 0.815 +Best cluster - rank: 1 i-RMSD: 1.049 Fnat: 0.879 DockQ: 0.815 + +============================================== +== run1-abb/10_caprieval/capri_clt.tsv +============================================== +Total number of acceptable or better clusters: 1 out of 5 +Total number of medium or better clusters: 1 out of 5 +Total number of high quality clusters: 0 out of 5 + +First acceptable cluster - rank: 1 i-RMSD: 1.134 Fnat: 0.841 DockQ: 0.796 +First medium cluster - rank: 1 i-RMSD: 1.134 Fnat: 0.841 DockQ: 0.796 +Best cluster - rank: 1 i-RMSD: 1.134 Fnat: 0.841 DockQ: 0.796 + +============================================== +== run1-af2/10_caprieval/capri_clt.tsv +============================================== +Total number of acceptable or better clusters: 2 out of 3 +Total number of medium or better clusters: 0 out of 3 +Total number of high quality clusters: 0 out of 3 + +First acceptable cluster - rank: 1 i-RMSD: 3.974 Fnat: 0.289 DockQ: 0.239 +First medium cluster - rank: i-RMSD: Fnat: DockQ: +Best cluster - rank: 3 i-RMSD: 3.305 Fnat: 0.302 DockQ: 0.290 ++
+============================================== +== run1/07_caprieval/capri_ss.tsv +============================================== +... +First acceptable model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +First medium model - rank: 1 i-RMSD: 1.037 Fnat: 0.931 DockQ: 0.841 +Best model - rank: 11 i-RMSD: 0.841 Fnat: 0.897 DockQ: 0.875 + +============================================== +== run1-abb/07_caprieval/capri_ss.tsv +============================================== +... +First acceptable model - rank: 1 i-RMSD: 0.990 Fnat: 0.931 DockQ: 0.860 +First medium model - rank: 1 i-RMSD: 0.990 Fnat: 0.931 DockQ: 0.860 +Best model - rank: 1 i-RMSD: 0.990 Fnat: 0.931 DockQ: 0.860 + +============================================== +== run1-af2/07_caprieval/capri_ss.tsv +============================================== +... +First acceptable model - rank: 1 i-RMSD: 3.246 Fnat: 0.362 DockQ: 0.389 +First medium model - rank: i-RMSD: Fnat: DockQ: +Best model - rank: 21 i-RMSD: 2.474 Fnat: 0.362 DockQ: 0.468 ++
+============================================== +== run1-ens//12_caprieval/capri_clt.tsv +============================================== +Total number of acceptable or better clusters: 3 out of 11 +Total number of medium or better clusters: 1 out of 11 +Total number of high quality clusters: 1 out of 11 + +First acceptable cluster - rank: 1 i-RMSD: 0.981 Fnat: 0.918 DockQ: 0.850 +First medium cluster - rank: 1 i-RMSD: 0.981 Fnat: 0.918 DockQ: 0.850 +Best cluster - rank: 1 i-RMSD: 0.981 Fnat: 0.918 DockQ: 0.850 ++
+============================================== +== run1-ens//02_caprieval/capri_ss.tsv +============================================== +Total number of acceptable or better models: 27 out of 150 +Total number of medium or better models: 11 out of 150 +Total number of high quality models: 1 out of 150 + +First acceptable model - rank: 2 i-RMSD: 1.422 Fnat: 0.586 DockQ: 0.631 +First medium model - rank: 2 i-RMSD: 1.422 Fnat: 0.586 DockQ: 0.631 +Best model - rank: 26 i-RMSD: 0.982 Fnat: 0.759 DockQ: 0.774 +============================================== +== run1-ens//05_caprieval/capri_ss.tsv +============================================== +Total number of acceptable or better models: 16 out of 83 +Total number of medium or better models: 10 out of 83 +Total number of high quality models: 1 out of 83 + +First acceptable model - rank: 2 i-RMSD: 1.422 Fnat: 0.586 DockQ: 0.631 +First medium model - rank: 2 i-RMSD: 1.422 Fnat: 0.586 DockQ: 0.631 +Best model - rank: 24 i-RMSD: 0.982 Fnat: 0.759 DockQ: 0.774 +============================================== +== run1-ens//07_caprieval/capri_ss.tsv +============================================== +Total number of acceptable or better models: 17 out of 83 +Total number of medium or better models: 9 out of 83 +Total number of high quality models: 4 out of 83 + +First acceptable model - rank: 1 i-RMSD: 0.836 Fnat: 0.931 DockQ: 0.878 +First medium model - rank: 1 i-RMSD: 0.836 Fnat: 0.931 DockQ: 0.878 +Best model - rank: 7 i-RMSD: 0.829 Fnat: 0.845 DockQ: 0.854 +============================================== +== run1-ens//09_caprieval/capri_ss.tsv +============================================== +Total number of acceptable or better models: 16 out of 83 +Total number of medium or better models: 9 out of 83 +Total number of high quality models: 3 out of 83 + +First acceptable model - rank: 1 i-RMSD: 0.908 Fnat: 0.897 DockQ: 0.855 +First medium model - rank: 1 i-RMSD: 0.908 Fnat: 0.897 DockQ: 0.855 +Best model - rank: 12 i-RMSD: 0.851 Fnat: 0.845 DockQ: 0.851 +============================================== +== run1-ens//12_caprieval/capri_ss.tsv +============================================== +Total number of acceptable or better models: 10 out of 44 +Total number of medium or better models: 4 out of 44 +Total number of high quality models: 2 out of 44 + +First acceptable model - rank: 1 i-RMSD: 0.908 Fnat: 0.897 DockQ: 0.855 +First medium model - rank: 1 i-RMSD: 0.908 Fnat: 0.897 DockQ: 0.855 +Best model - rank: 2 i-RMSD: 0.879 Fnat: 0.948 DockQ: 0.881 ++
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 1 17 - -151.013 2.855 1.957 0.466 0.642 0.060 4.965 0.721 0.593 0.080 61.922 16.739 1986.370 29.972 6.632 4.202 -596.659 47.783 -579.241 41.814 -44.505 9.407 1 -2 5 10 - -144.671 4.375 15.023 0.056 0.073 0.007 24.092 0.434 0.065 0.003 82.575 31.344 2050.332 52.230 1.109 1.544 -454.861 68.487 -435.350 64.144 -63.065 9.264 2 -3 4 10 - -103.148 2.915 9.859 0.357 0.065 0.025 19.699 0.784 0.082 0.011 118.571 18.485 1422.492 48.831 1.077 3.734 -395.524 36.286 -313.930 36.565 -36.977 2.057 3 -4 2 11 - -101.775 9.988 14.811 0.042 0.082 0.014 23.773 0.258 0.069 0.005 112.762 35.542 1733.245 136.770 5.903 1.639 -369.718 13.140 -301.966 31.881 -45.010 9.758 4 -5 12 4 - -101.717 16.264 2.883 0.465 0.414 0.073 6.588 0.667 0.421 0.039 123.812 49.768 1620.057 171.832 8.321 3.108 -510.810 25.365 -407.254 30.156 -20.257 18.482 5 -6 6 10 - -100.286 5.972 5.029 0.078 0.121 0.012 12.377 0.431 0.175 0.007 81.077 18.925 1527.888 25.942 6.652 1.287 -297.121 20.305 -271.666 30.603 -55.622 4.563 6 -7 3 10 - -98.426 7.151 4.147 0.602 0.341 0.092 8.377 1.144 0.324 0.059 163.456 41.462 1654.400 57.204 -1.567 4.125 -331.139 27.013 -214.660 64.132 -46.976 4.973 7 -8 9 8 - -91.198 8.435 3.061 0.163 0.509 0.029 7.763 0.751 0.417 0.024 95.083 5.502 1636.765 120.832 7.456 2.015 -383.475 21.166 -319.859 23.245 -31.468 7.111 8 -9 10 8 - -89.350 5.243 14.907 0.197 0.095 0.019 24.223 0.525 0.072 0.006 108.123 28.325 1698.345 93.675 4.693 2.411 -294.506 48.615 -232.337 53.247 -45.954 8.366 9 -10 7 10 - -78.992 5.846 7.589 0.167 0.164 0.008 16.501 0.352 0.137 0.002 141.345 58.004 1386.070 33.470 -0.716 1.791 -253.702 31.000 -154.028 33.843 -41.671 4.896 10 -11 11 6 - -77.052 4.065 3.956 0.826 0.341 0.071 8.653 1.743 0.327 0.075 171.334 27.914 1501.757 87.948 6.200 3.838 -329.716 23.812 -192.825 44.069 -34.442 5.191 11 -12 8 8 - -67.688 6.454 14.580 0.019 0.086 0.012 23.018 0.239 0.072 0.005 148.451 30.560 1652.513 97.272 3.496 1.602 -203.546 55.957 -100.415 43.751 -45.320 6.620 12 +* Antibody heavy chain: ++QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDES +YNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS-
+DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPS +RFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK +-What is the rank of the best cluster generated? +* Antigen: +
+VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGL +KEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYI +STSQAENMPVFLGGTKGGQDITDFTMQFVSS ++
+QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDESYNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS:DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPSRFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK:VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGLKEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYISTSQAENMPVFLGGTKGGQDITDFTMQFVSS ++ + + +Define the _jobname_, e.g. Ab-Ag + + + +In the _Advanced settings_ block you can check the option to save the results to your Google Drive (if you have an account) + + + +In the top section of the Colab, click: _Runtime > Run All_ + +(It may give a warning that this is not authored by Google because it is pulling code from GitHub - you can ignore it). -In this run we also had a `caprieval` after the clustering of the rigid body models (step 4 of our workflow). +This will automatically install, configure and run AlphaFold2 for you - leave this window open. +After the prediction completed, you will be asked to download a zip archive with the results (if you configured it to use Google Drive, a result archive will be automatically saved to your Google Drive). + +
-cluster_rank cluster_id n under_eval score score_std irmsd irmsd_std fnat fnat_std lrmsd lrmsd_std dockq dockq_std air air_std bsa bsa_std desolv desolv_std elec elec_std total total_std vdw vdw_std caprieval_rank -1 6 10 - -14.099 0.485 2.534 0.060 0.328 0.000 6.091 0.186 0.416 0.006 497.929 84.662 1549.405 36.228 12.766 0.474 -16.378 0.493 484.394 89.658 2.844 5.623 1 -2 5 10 - -13.662 1.131 7.797 0.008 0.138 0.000 16.855 0.109 0.126 0.001 728.546 171.645 1173.928 15.754 -3.900 0.575 -5.855 0.132 777.477 174.737 54.786 8.386 2 -3 1 10 - -11.313 0.323 1.048 0.090 0.737 0.026 2.716 0.487 0.772 0.017 393.784 59.151 1658.795 79.415 11.225 0.683 -9.950 0.631 390.030 72.124 6.196 17.950 3 -4 3 10 - -9.839 0.266 5.023 0.016 0.168 0.007 12.101 0.046 0.194 0.003 408.853 105.262 1349.137 18.104 5.414 0.889 -5.624 0.400 380.563 108.924 -22.667 6.196 4 -5 4 10 - -9.326 1.678 14.812 0.010 0.069 0.000 23.503 0.056 0.065 0.000 380.995 98.521 1677.188 22.301 5.271 1.050 -1.377 0.204 353.849 106.067 -25.768 7.771 5 -7 11 10 - -9.256 0.749 4.689 0.384 0.237 0.019 10.175 0.794 0.248 0.021 997.843 119.928 1262.298 9.238 -4.968 0.214 -1.769 1.706 1008.617 125.287 12.542 8.265 6 -6 2 10 - -8.233 0.486 10.223 0.245 0.026 0.015 21.128 0.934 0.062 0.009 581.415 155.264 1036.009 53.300 1.424 0.492 -5.174 1.459 582.590 159.417 6.348 8.379 7 -8 7 10 - -3.262 0.604 14.741 0.012 0.069 0.000 23.565 0.052 0.065 0.000 676.043 49.459 1149.500 14.839 9.827 0.292 -8.472 0.095 679.402 52.646 11.831 3.553 8 -10 8 10 - -2.096 1.711 3.685 0.709 0.272 0.041 8.101 1.996 0.321 0.068 708.926 377.133 1167.398 7.469 11.135 1.233 -8.820 2.498 717.466 390.544 17.360 15.407 9 -9 9 10 - -1.996 0.489 3.210 0.084 0.332 0.026 8.203 0.501 0.343 0.009 398.137 131.501 1060.155 56.080 12.793 0.944 -8.149 1.179 387.985 134.607 -2.003 5.126 10 -12 10 10 - -1.280 2.048 14.353 0.513 0.038 0.008 22.816 0.551 0.057 0.003 869.164 86.949 1255.027 53.327 6.427 3.491 -4.390 2.183 918.969 91.260 54.194 7.974 11 -11 12 10 - -1.104 3.228 14.742 0.077 0.052 0.000 24.131 0.342 0.058 0.001 574.145 40.525 1146.227 48.875 4.858 2.295 -0.342 0.112 583.846 49.827 10.042 11.138 12 + ++ See the confidence statistics for the five generated models +
+ ++ Model1: pLDDT=90.4 pTM=0.654 ipTM=0.525 + Model2: pLDDT=88.0 pTM=0.65 ipTM=0.522 + Model3: pLDDT=88.2 pTM=0.647 ipTM=0.52 + Model4: pLDDT=88.0 pTM=0.644 ipTM=0.516 + Model5: pLDDT=88.1 pTM=0.641 ipTM=0.512+
+Note that if you performed a fresh run your results might well differ from those shown here. +
- After rigid body docking the first acceptable cluster is at rank 1 and the same is true after refinement, but the iRMSD values have improved. -
+
+ -============================================== -== runs/scenario2b-NMR-epitope-act//4_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 4 out of 12 -Total number of medium or better clusters: 1 out of 12 -Total number of high quality clusters: 0 out of 12 +File menu -> Open -> select abagtest_2d03e_unrelaxed_rank_001_alphafold2_multimer_v3_model_3_seed_000.pdb -First acceptable cluster - rank: 1 i-RMSD: 2.534 Fnat: 0.328 DockQ: 0.416 -First medium cluster - rank: 3 i-RMSD: 1.048 Fnat: 0.737 DockQ: 0.772 -Best cluster - rank: 3 i-RMSD: 1.048 Fnat: 0.737 DockQ: 0.772 -============================================== -== runs/scenario2b-NMR-epitope-act//9_caprieval/capri_clt.tsv -============================================== -Total number of acceptable or better clusters: 4 out of 12 -Total number of medium or better clusters: 1 out of 12 -Total number of high quality clusters: 0 out of 12 +Repeat this for each model (`abagtest_2d03e_unrelaxed_rank_X_alphafold2_multimer_v3_model_X_seed_000.pdb` or whatever the naming of your model is). -First acceptable cluster - rank: 1 i-RMSD: 1.957 Fnat: 0.642 DockQ: 0.593 -First medium cluster - rank: 1 i-RMSD: 1.957 Fnat: 0.642 DockQ: 0.593 -Best cluster - rank: 1 i-RMSD: 1.957 Fnat: 0.642 DockQ: 0.593 --
-============================================== -== runs/scenario2b-NMR-epitope-act//4_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 34 out of 120 -Total number of medium or better models: 10 out of 120 -Total number of high quality models: 2 out of 120 +**Note:** You can turn on and off a model by clicking on its name in the right panel of the PyMOL window. -First acceptable model - rank: 2 i-RMSD: 2.533 Fnat: 0.328 DockQ: 0.416 -First medium model - rank: 11 i-RMSD: 1.035 Fnat: 0.724 DockQ: 0.757 -Best model - rank: 19 i-RMSD: 0.978 Fnat: 0.741 DockQ: 0.779 -============================================== -== runs/scenario2b-NMR-epitope-act//9_caprieval/capri_ss.tsv -============================================== -Total number of acceptable or better models: 35 out of 112 -Total number of medium or better models: 11 out of 112 -Total number of high quality models: 4 out of 112 +--First acceptable model - rank: 1 i-RMSD: 2.431 Fnat: 0.586 DockQ: 0.515 -First medium model - rank: 3 i-RMSD: 1.922 Fnat: 0.638 DockQ: 0.597 -Best model - rank: 10 i-RMSD: 0.758 Fnat: 0.845 DockQ: 0.871 -
- In this case we observe a small improvement in terms of iRMSD values and quite some large improvement in - the fraction of native contacts and the DockQ scores. Also the single model rankings have improved, but the top ranked model is not the best one. -
+
+ - This is clearly not the case. The scoring function is not perfect, but does a reasonable job in ranking models of acceptable or better quality on top in this case. -
+
+ 
+ 
+ + model md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq rmsd cluster_id cluster_ranking model-cluster_ranking air angles bonds bsa cdih coup dani desolv dihe elec improper rdcs rg sym total vdw vean xpcs +../1_emscoring/emscoring_82.pdb - 1 -157.149 0.910 0.897 2.201 1.456 0.855 1.016 3 1 1 0.000 0.000 0.000 2000.130 0.000 0.000 0.000 7.345 0.000 -599.183 0.000 0.000 0.000 0.000 -643.841 -44.658 0.000 0.000 +../1_emscoring/emscoring_2.pdb - 2 -156.452 0.880 0.948 1.949 1.355 0.881 0.989 3 1 2 0.000 0.000 0.000 1914.860 0.000 0.000 0.000 3.125 0.000 -504.372 0.000 0.000 0.000 0.000 -563.075 -58.703 0.000 0.000 +../1_emscoring/emscoring_64.pdb - 3 -138.214 1.052 0.914 3.039 1.955 0.824 1.294 3 1 3 0.000 0.000 0.000 1784.350 0.000 0.000 0.000 -2.359 0.000 -424.542 0.000 0.000 0.000 0.000 -475.489 -50.947 0.000 0.000 +../1_emscoring/emscoring_40.pdb - 4 -135.230 1.085 0.897 1.866 1.756 0.836 1.144 3 1 4 0.000 0.000 0.000 1875.210 0.000 0.000 0.000 3.490 0.000 -429.067 0.000 0.000 0.000 0.000 -481.973 -52.906 0.000 0.000 +../1_emscoring/emscoring_37.pdb - 5 -134.569 13.624 0.069 22.589 21.764 0.068 13.881 5 2 1 0.000 0.000 0.000 1802.890 0.000 0.000 0.000 6.081 0.000 -426.815 0.000 0.000 0.000 0.000 -482.102 -55.287 0.000 0.000 - -show cartoon - - -util.cbc - - -color yellow, 4G6M_matched - +... +-Let us then superimpose all models on the reference structure: + +Did the HADDOCK scoring do a good job at putting the best models on top (consider for example the DockQ score)? + +The `emscoring` module renames all models, which makes it difficult to know what was the original model. +You can however trace back a model to its original file by looking into the `traceback/traceback.tsv` file: - -alignto 4G6M_matched - +
+00_topoaa 1_emscoring 1_emscoring_rank +emref_9_from_haddock3-ens-emref-ensemble_83_haddock.psf emscoring_82.pdb 1 +emref_10_from_haddock3-ens-emref-ensemble_2_haddock.psf emscoring_2.pdb 2 +emref_7_from_haddock3-ens-emref-ensemble_67_haddock.psf emscoring_64.pdb 3 +emref_5_from_haddock3-ens-emref-ensemble_45_haddock.psf emscoring_40.pdb 4 +... +-How close are the top4 models to the reference? Did HADDOCK do a good job at ranking the best in the top? +Try to locate the AlphaFold2 and AlphaFold3 models (their filenames start with _abag_test_ and _af3server_, respectively) -Let’s now check if the active residues which we have defined (the paratope and epitope) are actually part of the interface. In the PyMOL command window type: +A simple way to extra this information is to use `grep`: - -select paratope, (resi 31+32+33+34+35+52+54+55+56+100+101+102+103+104+105+106+1031+1032+1049+1050+1053+1091+1092+1093+1094+1096 and chain A) - - -color red, paratope + +grep abag traceback.tsv - -select epitope, (resi 72+73+74+75+81+83+84+89+90+92+94+96+97+98+115+116+117 and chain B) + +
+> grep abag traceback.tsv +abagtest_2d03e_unrelaxed_rank_001_alphafold2_multimer_v3_model_3_seed_000_from_af2-models_1_haddock.psf emscoring_84.pdb 86 +abagtest_2d03e_unrelaxed_rank_005_alphafold2_multimer_v3_model_2_seed_000_from_af2-models_5_haddock.psf emscoring_88.pdb 90 +abagtest_2d03e_unrelaxed_rank_004_alphafold2_multimer_v3_model_4_seed_000_from_af2-models_4_haddock.psf emscoring_87.pdb 91 +abagtest_2d03e_unrelaxed_rank_003_alphafold2_multimer_v3_model_1_seed_000_from_af2-models_3_haddock.psf emscoring_86.pdb 92 +abagtest_2d03e_unrelaxed_rank_002_alphafold2_multimer_v3_model_5_seed_000_from_af2-models_2_haddock.psf emscoring_85.pdb 93 ++
+> grep abag traceback.tsv +af3server_15052024_2_ready_from_af3-models_2_haddock.psf emscoring_90.pdb 40 +af3server_15052024_1_ready_from_af3-models_1_haddock.psf emscoring_89.pdb 81 +af3server_15052024_4_ready_from_af3-models_4_haddock.psf emscoring_92.pdb 87 +af3server_15052024_3_ready_from_af3-models_3_haddock.psf emscoring_91.pdb 88 +af3server_15052024_5_ready_from_af3-models_5_haddock.psf emscoring_93.pdb 89 ++
Top4 models of the top cluster of scenario2a superimposed onto the reference crystal structure (in yellow)
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- The bottom eight models (the worst ranking ones) are all AlphaFold3/2 models. Looking at the componenents of the score + (some were left out in the table below for simplicity) one can see that it is mainly the van der Waals energy that causes the high scores, + which is indicative of clashes in the models.
++model md5 caprieval_rank score irmsd fnat lrmsd ilrmsd dockq rmsd bsa desolv elec vdw vean xpcs +... +../1_emscoring/emscoring_84.pdb - 86 -67.914 11.123 0.000 22.413 18.626 0.048 12.213 3535.520 -67.537 -150.913 29.806 +../1_emscoring/emscoring_92.pdb - 87 -63.263 11.426 0.000 22.104 21.035 0.049 11.048 1383.920 -9.924 -88.656 -35.607 +../1_emscoring/emscoring_91.pdb - 88 -50.990 13.665 0.000 23.793 22.150 0.042 13.796 1492.150 -8.962 -167.236 -8.581 +../1_emscoring/emscoring_93.pdb - 89 -46.871 6.644 0.000 10.617 11.333 0.146 6.455 1740.990 -8.906 -35.623 -30.841 +../1_emscoring/emscoring_88.pdb - 90 48.283 12.919 0.000 20.484 19.885 0.053 14.706 3914.250 -68.786 -129.461 142.961 +../1_emscoring/emscoring_87.pdb - 91 180.468 12.447 0.000 22.153 19.299 0.048 14.160 3639.430 -66.857 -240.130 295.351 +../1_emscoring/emscoring_86.pdb - 92 240.307 12.572 0.000 21.662 19.799 0.049 14.187 3535.820 -69.380 -154.703 340.628 +../1_emscoring/emscoring_85.pdb - 93 781.210 15.174 0.000 23.497 24.993 0.042 17.151 3278.340 -61.261 -86.026 859.677 +
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1 32 33 34 35 52 54 55 56 100 101 102 103 104 105 106 151 152 169 170 173 211 212 213 214 216-* For the antigen we will use the NMR-identified epitope as active and the surface neighbors as passive. The corresponding file can be found in the `restraints` directory as `antigen-NMR-epitope.act-pass`: +* For the antigen we will use the NMR-identified epitope as active and the surface neighbors as passive. +The corresponding file can be found in the `restraints` directory as `antigen-NMR-epitope.act-pass`:
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HADDOCK3
***H*****igh *A*mbiguity *D*riven biomolecular *DOCK*ing**.
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