{"id":223,"date":"2019-03-08T00:08:47","date_gmt":"2019-03-08T00:08:47","guid":{"rendered":"https:\/\/ccsb.scripps.edu\/adcpv11\/?page_id=223"},"modified":"2024-01-18T02:59:25","modified_gmt":"2024-01-18T02:59:25","slug":"documentation","status":"publish","type":"page","link":"https:\/\/ccsb.scripps.edu\/adcpv11\/documentation\/","title":{"rendered":"Documentation"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-one-full fusion-column-first fusion-column-last\" style=\"--awb-bg-size:cover;--awb-margin-bottom:0px;\"><div class=\"fusion-column-wrapper fusion-flex-column-wrapper-legacy\"><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-one\" style=\"--awb-margin-top-small:10px;--awb-margin-right-small:0px;--awb-margin-bottom-small:10px;--awb-margin-left-small:0px;\"><h1 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\"><h3>ADCP v1.1<\/h3><\/h1><\/div><div class=\"fusion-text fusion-text-1\"><p>This page is under construction and currently only provides a few examples of running the software illustrating the new capabilities.<\/p>\n<p>To run these examples you should download a <a href=\"https:\/\/ccsb.scripps.edu\/adcpv11\/download\/436\/\">receptor<\/a> and <a href=\"https:\/\/ccsb.scripps.edu\/adcpv11\/download\/441\/\">ligand<\/a> for 3Q47<\/p>\n<\/div><div class=\"fusion-tabs fusion-tabs-1 clean vertical-tabs icon-position-left mobile-mode-accordion\" style=\"--awb-title-border-radius-top-left:0px;--awb-title-border-radius-top-right:0px;--awb-title-border-radius-bottom-right:0px;--awb-title-border-radius-bottom-left:0px;--awb-inactive-color:#ffffff;--awb-background-color:#03a9f4;--awb-border-color:#ebeaea;--awb-active-border-color:#779ff4;\"><div class=\"nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li class=\"active\" role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-725a7a2758279dd2a89\" aria-selected=\"true\" id=\"fusion-tab-createatargetfile\" href=\"#tab-725a7a2758279dd2a89\"><h4 class=\"fusion-tab-heading\">create a target file<\/h4><\/a><\/li><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-aef4482ffa3642d8fe6\" aria-selected=\"false\" tabindex=\"-1\" id=\"fusion-tab-runadcp\" href=\"#tab-aef4482ffa3642d8fe6\"><h4 class=\"fusion-tab-heading\">run ADCP<\/h4><\/a><\/li><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-06867b694dd84c03586\" aria-selected=\"false\" tabindex=\"-1\" id=\"fusion-tab-openmmminimization\" href=\"#tab-06867b694dd84c03586\"><h4 class=\"fusion-tab-heading\">OpenMM minimization<\/h4><\/a><\/li><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-45cbd8c6fd81b715f6c\" aria-selected=\"false\" tabindex=\"-1\" id=\"fusion-tab-non-canonicalamino-acid\" href=\"#tab-45cbd8c6fd81b715f6c\"><h4 class=\"fusion-tab-heading\">Non-canonical amino-acid<\/h4><\/a><\/li><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-31a04be6bd09c2c39f2\" aria-selected=\"false\" tabindex=\"-1\" id=\"fusion-tab-tutorialtogeneratelibfileforannst\" href=\"#tab-31a04be6bd09c2c39f2\"><h4 class=\"fusion-tab-heading\">Tutorial To Generate Lib file for an NST<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-content\"><div class=\"nav fusion-mobile-tab-nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li class=\"active\" role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-725a7a2758279dd2a89\" aria-selected=\"true\" id=\"mobile-fusion-tab-createatargetfile\" href=\"#tab-725a7a2758279dd2a89\"><h4 class=\"fusion-tab-heading\">create a target file<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-pane fade fusion-clearfix in active\" role=\"tabpanel\" tabindex=\"0\" aria-labelledby=\"fusion-tab-createatargetfile\" id=\"tab-725a7a2758279dd2a89\">\n<p>the following command will compute the 3Q47.trg target file<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-1 > .CodeMirror, .fusion-syntax-highlighter-1 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-1 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_1\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_1\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_1\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/x-sh\">\nagfr -r 3Q47_recH.pdbqt -l 3Q47_pepH.pdbqt -asv 1.1 -o 3Q47\n\n<\/textarea><\/div><div class=\"fusion-sep-clear\"><\/div><div class=\"fusion-separator fusion-full-width-sep\" style=\"margin-left: auto;margin-right: auto;margin-top:15px;margin-bottom:15px;width:100%;\"><div class=\"fusion-separator-border sep-double sep-solid\" style=\"--awb-height:20px;--awb-amount:20px;border-color:#e0dede;border-top-width:2px;border-bottom-width:2px;\"><\/div><\/div><div class=\"fusion-sep-clear\"><\/div>\n<p>agfr runs AutoGridFr which computes target files.<\/p>\n<p>-r specified the receptor and here we provide the pdbqt file<br \/>\n-l specifies the ligand and here we provide the crystallographic peptide. When a ligand is provided, agfr will use it to defined the docking box as the ligand&#8217;s bounding box with 4 Angstroms padding.<br \/>\n-asv 1.1 specifies that we want to compute preferred starting ligand position in the docking box using version 1.1 of AutoSite rather than 1.0 which is for small molecules<br \/>\n-o 3Q47 specifies the name of target file to write (e.g. 3Q47.trg)<\/p>\n<p>This command should generate the following output in the console and write the 3D47.trg target file<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-2 > .CodeMirror, .fusion-syntax-highlighter-2 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-2 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><label for=\"fusion_syntax_highlighter_2\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_2\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/diff\">processing: 3Q47_recH.pdbqt\nloading ligand: 3Q47_pepH.pdbqt\n\nset box using ligand\n    Box center:    16.052     9.415     5.617\n    Box length:    20.250    21.000    21.000\n    Box size  :        54        56        56\n    padding   :     4.000\n    spacing   :     0.375\n\nidentifying pockets using AutoSite ....\nScanning at: -0.36 -0.792 -0.6\n0 #: 0\nScanning at: -0.315 -0.6930000000000001 -0.525\nclust.| Energy| # of |Rad. of | energy |   bns    |score   |\nnumber|       |points|gyration|per vol.|buriedness|v*b^2\/rg|\n------+-------+------+--------+--------+----------+--------|\n    1   -33.10    59    2.50    -0.56     0.729     12.54 \nScanning at: -0.27 -0.5940000000000001 -0.44999999999999996\nclust.| Energy| # of |Rad. of | energy |   bns    |score   |\nnumber|       |points|gyration|per vol.|buriedness|v*b^2\/rg|\n------+-------+------+--------+--------+----------+--------|\n    1   -46.45    88    2.95    -0.53     0.772     17.78 \n    2   -34.12    68    2.32    -0.50     0.756     16.79 \n    3   -46.16    84    2.74    -0.55     0.715     15.65 \nScanning at: -0.22499999999999998 -0.495 -0.375\nclust.| Energy| # of |Rad. of | energy |   bns    |score   |\nnumber|       |points|gyration|per vol.|buriedness|v*b^2\/rg|\n------+-------+------+--------+--------+----------+--------|\n    1   -86.02   169    3.58    -0.51     0.741     25.87 \n    2   -66.14   140    3.26    -0.47     0.664     18.92 \n    3   -73.08   162    4.53    -0.45     0.689     16.97 \n    found 3 pocket(s)\n\n    pocket|  energy | # of |Rad. of | energy |   bns    | score  \n    number|         |points|gyration|per vol.|buriedness|v*b^2\/rg\n    ------+---------+------+--------+--------+----------+---------\n        1   -102.22   260    4.15     -0.39      0.82      41.58\n        2    -83.99   236    4.02     -0.36      0.77      34.84\n        3    -92.58   265    4.92     -0.35      0.78      32.82\n    merging clusters ...\ndone. got 107 fill Points, in 1.80 (sec)\n\nsetting map types using: all to ['H', 'HD', 'HS', 'C', 'A', 'G', 'GA', 'J', 'Q', 'N', 'NA', 'NS', 'OA', 'OS', 'SA', 'S', 'P', 'F', 'Cl', 'Br', 'I', 'Mg', 'Ca', 'Mn', 'Fe', 'Zn', 'Z']\n\ncomputing maps for center=(16.052 9.415 5.617) size=(20.250 21.000 21.000) dims=(54 56 56) ...\n    106 points inside the box\n\n    maps computed in 1.93 (sec)\nmaking target file 3Q47.trg ...done.\n    done. 4.30 (sec)\n<\/textarea><\/div>\n<pre><\/pre>\n<\/div><div class=\"nav fusion-mobile-tab-nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-aef4482ffa3642d8fe6\" aria-selected=\"false\" tabindex=\"-1\" id=\"mobile-fusion-tab-runadcp\" href=\"#tab-aef4482ffa3642d8fe6\"><h4 class=\"fusion-tab-heading\">run ADCP<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-pane fade fusion-clearfix\" role=\"tabpanel\" tabindex=\"0\" aria-labelledby=\"fusion-tab-runadcp\" id=\"tab-aef4482ffa3642d8fe6\">\n<p>the following command will run ADCP with modified aminoacids<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-3 > .CodeMirror, .fusion-syntax-highlighter-3 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-3 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_3\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_3\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_3\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/x-sh\">adcp -T 3Q47.trg -s \"n<BHD>pis&dvd\" -N 2 -n 2000 -L swiss -w testDir -o testNSAAandD<\/textarea><\/div>\n<p>In version 1.1 of ADCP the peptide sequence allows the specification of non-natural amino acids using the following syntax &#8220;<em><strong>[&amp;]x<\/strong><\/em>&#8221; .<\/p>\n<p>The optional &amp; will make the amino acid Dextro instead of the default L Chirality.<\/p>\n<p>The &#8216;<em><strong>x<\/strong><\/em>&#8216; character specifies the coarse bead used to represent the sidechain. Currently all single letter code for natural amino acids can be used in this position.<\/p>\n<p>The name of the modified sidechain is specified between chevrons i.e. &lt;&gt;. In the example above, the first amino acid will be represented as an asparagine in the coarse model and an asparagine derivative sidechain (BHD) from the Swiss sidechain library will be used for the full atom representation. The peptide will also contain a D-Aspartic acid in position 5.<\/p>\n<p>NOTE: the modified side chain will be loaded from a library file. In this case the Swiss library specified with -L swiss<\/p>\n<p>Here we perform only 2 MC searches (-N 2) each allotted (2000 evals) as the purpose is mainly to run the command quickly rather than finding real docked poses. the command will produce the output shown below and create 2 files: a multi model PDB file called testNSAAandD_out.pdb and a summary file called testNSAAandD_summary.dlg in the working directory (-w) testDir.<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-4 > .CodeMirror, .fusion-syntax-highlighter-4 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-4 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><label for=\"fusion_syntax_highlighter_4\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_4\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/diff\">Inflating target file 3Q47.trg\nperforming MC searches with: \/home\/xxxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/site-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1 \ntarget data from file: 3Q47.trg\njob name: testNSAAandD, summary file testNSAAandD_summary.dlg, docked poses: testNSAAandD_out.pdb\nDetected 8 cores, using 8 cores.\nusing system rotamer libraries swiss from \/home\/xxxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/site-packages\/ADCP\/data\/rotamers\nPerforming 2 MC searches using 2000 evals each using a random seed.\nPerforming search (2 ADCP runs with 2000 steps each) ...\n0%   10   20   30   40   50   60   70   80   90   100%\n|----|----|----|----|----|----|----|----|----|----|\nDocking performed in 2.03 seconds, i.e. 0 hours 00 minutes 02.030427 seconds \nbestEnergies [12.8321, 11.8518] \nbestEnergy in run 2 11.851800 (0)\nAnalyzing results ....\nconcatenating trajectories for run with best energy < 31.851800\nconcatenated 2 trajectories\nClustering MC trajectories based in contacts using cutoff: 0.800000\nfinished calculating neighbors for 22 poses with 0.0 seconds\nmode |  affinity  | ref. | clust. | rmsd | energy | best |\n     | (kcal\/mol) | fnc  |  size  | stdv |  stdv  | run  |\n-----+------------+------+--------+------+--------+------+\n   1          7.0      0.0       2      NA      NA    015 \n   2          7.6      0.0       2      NA      NA    008 \n   3         12.5      0.0       1      NA      NA    009 \nCalculations completed 2.12 seconds, i.e. 0 hours 00 minutes 02.030427 seconds \nMC search command: cd testDir\/testNSAAandD; \/home\/xxxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/site-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1 -t 2 \"n<BHD>pis&dvd\" -L swiss -T \/home\/xxxxxxx\/ADCP_examples\/testDir\/testNSAAandD\/3Q47 -r 1x2000 -p Bias=NULL,external=5,constrains,1.0,1.0,Opt=1,0.25,0.75,0.0 -s 930583 -o run_1.pdb  \nseed: []\nremoving working folder testDir\/testNSAAandD<\/textarea><\/div>\n<p>After the calculation the testDir folder contains the following files<\/p>\n<p>testNSAAandD_out.pdb ; a multi model PDB file with the docked poses<\/p>\n<p>testNSAAandD_summary.dlg: the docking log files<\/p>\n<\/div><div class=\"nav fusion-mobile-tab-nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-06867b694dd84c03586\" aria-selected=\"false\" tabindex=\"-1\" id=\"mobile-fusion-tab-openmmminimization\" href=\"#tab-06867b694dd84c03586\"><h4 class=\"fusion-tab-heading\">OpenMM minimization<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-pane fade fusion-clearfix\" role=\"tabpanel\" tabindex=\"0\" aria-labelledby=\"fusion-tab-openmmminimization\" id=\"tab-06867b694dd84c03586\">\n<p>ADCP v1.1 supports OpenMM based minimization and re-ranking of docked poses. In this document, we provide examples to use of this feature. For all these examples, we assume that user is already aware of using ADCP with standard options (flags).<\/p>\n<p><strong>OpenMM based re-ranking of ADCP docked poses containing standard amino acids :<\/strong><\/p>\n<p>The option \u201c-nmin\u201d activates the OpenMM-based minimization of poses followed by reranking. The following example will dock a peptide (sequence: \u201cgrctksicfpd\u201d) with the protein receptor ( from 3Q47.trg ) and minimize the top 5 docked solution using openMM.<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-5 > .CodeMirror, .fusion-syntax-highlighter-5 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}.fusion-syntax-highlighter-5 > .CodeMirror .CodeMirror-gutters { background-color: var(--awb-color2); }.fusion-syntax-highlighter-5 > .CodeMirror .CodeMirror-linenumber { color: var(--awb-color8); }<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-5 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_5\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_5\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_5\" data-readOnly=\"nocursor\" data-lineNumbers=\"1\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/x-sh\">adcp -O -T 3Q47.trg -s \"grctksicfpd\" -cyc -N 5 -n 100000 -w testDir1 -o example1 -nmin 5<\/textarea><\/div>\n<p>This command will generate on-screen output like:<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-6 > .CodeMirror, .fusion-syntax-highlighter-6 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-6 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><label for=\"fusion_syntax_highlighter_6\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_6\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/diff\">------------------------------------------------------------------\nOpenMM minimization flag detected. This step takes more time than non-minimization calculations.\n\nDECLARATION (V1.1.0 build 15):\na: Support for OpenMM Minimization is still under development.\nb: Currently, it supports docking with \"-rmsd 0\" flag.\nc: Current version provides docking supports for peptides containing ~400 (L and D) NSTs and openMM support for 182 (182x2 for D and L) NSTs. \nd: Other unidentified non-standard amino acids can either be replaced by similar amino acids (pdbfixer v1.8), or if pdbfixer does not identify a non-standard amino acid, it can be replaced by ALA.\ne: Added support for external parameter input for non-standard amino acids.(from build 9)\n   \nInflating target file 3Q47.trg\nperforming MC searches with: \/home\/xxxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/site-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1 \ntarget data from file: 3Q47.trg\njob name: example1, summary file example1_summary.dlg, docked poses: example1_out.pdb\nDetected 8 cores, using 8 cores.\nPerforming 5 MC searches using 100000 evals each using a random seed.\nPerforming search (5 ADCP runs with 100000 steps each) ...\n0%   10   20   30   40   50   60   70   80   90   100%\n|----|----|----|----|----|----|----|----|----|----|\nDocking performed in 22.04 seconds, i.e. 0 hours 00 minutes 22.042032 seconds \nbestEnergies [-4.91352, -0.869985, -0.258118, -3.55476, -3.64629] \nbestEnergy in run 1 -4.913520 (0)\nAnalyzing results ....\nconcatenating trajectories for run with best energy < 15.086480\nconcatenated 5 trajectories\nClustering MC trajectories based in contacts using cutoff: 0.800000\nfinished calculating neighbors for 125 poses with 0.6 seconds\nmode |  affinity  | ref. | clust. | rmsd | energy | best |\n     | (kcal\/mol) | fnc  |  size  | stdv |  stdv  | run  |\n-----+------------+------+--------+------+--------+------+\n   1         -2.9      0.0      12      NA      NA    018 \n   2         -2.3      0.0       6      NA      NA    020 \n   3         -2.3      0.0       2      NA      NA    019 \n   4         -2.2      0.0      16      NA      NA    113 \n   5         -2.1      0.0       9      NA      NA    089 \n   6         -1.7      0.0       8      NA      NA    080 \n   7         -1.3      0.0       1      NA      NA    021 \n   8         -1.1      0.0      11      NA      NA    072 \n   9         -1.0      0.0       2      NA      NA    106 \n  10         -0.9      0.0       3      NA      NA    003 \n  11         -0.5      0.0       7      NA      NA    034 \n  12         -0.5      0.0       4      NA      NA    061 \nCalculations completed 22.77 seconds, i.e. 0 hours 00 minutes 22.042032 seconds \nMC search command: cd testDir1\/example1; \/home\/xxxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/site-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1 -t 2 \"grctksicfpd\" -T \/home\/xxxxxxx\/ADCP_examples\/testDir1\/example1\/3Q47 -r 1x100000 -p Bias=NULL,external=5,constrains,1.0,1.0,external2=4,constrains,1.0,1.0,Opt=1,0.25,0.75,0.0 -s 390427 -o run_1.pdb  \nseed: []\nMinimizing docked poses ....\nRescoring clustered poses using OpenMM ..\nOpenMM minimization settings: Environment=\"in-vacuo\"; Max_itr=5\nOpenMM minimization settings: Cyclizing by backbone\nFrom total 44 models, minimizing top 5 ...\n\nOMM Energy: Working on #1 of 5 models\nCyclizing peptide (last chain) by adding a bond between GLY1@N and ASP11@C.\nOMM Energy: E_Complex =  -1201.00; E_Receptor =  -1586.36; E_Peptide  =    441.69\nOMM Energy: dE_Interaction =    -56.33; dE_Complex-Receptor =    385.36\n\nOMM Energy: Working on #2 of 5 models\nCyclizing peptide (last chain) by adding a bond between GLY1@N and ASP11@C.\nOMM Energy: E_Complex =  18295.22; E_Receptor =   1122.39; E_Peptide  =  17239.90\nOMM Energy: dE_Interaction =    -67.07; dE_Complex-Receptor =  17172.83\n\nOMM Energy: Working on #3 of 5 models\nCyclizing peptide (last chain) by adding a bond between GLY1@N and ASP11@C.\nOMM Energy: E_Complex =  -1721.60; E_Receptor =  -1855.51; E_Peptide  =    231.76\nOMM Energy: dE_Interaction =    -97.86; dE_Complex-Receptor =    133.91\n\nOMM Energy: Working on #4 of 5 models\nCyclizing peptide (last chain) by adding a bond between GLY1@N and ASP11@C.\nOMM Energy: E_Complex =  -1387.83; E_Receptor =  -1685.81; E_Peptide  =    327.20\nOMM Energy: dE_Interaction =    -29.22; dE_Complex-Receptor =    297.98\n\nOMM Energy: Working on #5 of 5 models\nCyclizing peptide (last chain) by adding a bond between GLY1@N and ASP11@C.\nOMM Energy: E_Complex =  -1784.56; E_Receptor =  -1940.05; E_Peptide  =    234.73\nOMM Energy: dE_Interaction =    -79.25; dE_Complex-Receptor =    155.48\n\nOMM Ranking:REARRANGING output poses using OpenMM (Ecomplex -Ereceptor) energy\nOMM Ranking:                     +<-------OMMscore-------->+<-----------AutoDock CrankPep Scores-------------->+\nOMM Ranking:-------+------+------+------------+------------+------------+------+--------+------+--------+------+\nOMM Ranking: Model | Rank | Rank | E_Complex  |  E_Complex |  affinity  | ref. | clust. | rmsd | energy | best |\nOMM Ranking: #     |OpenMM| ADCP |-E_Receptor |-E_rec-E_pep| (kcal\/mol) | fnc  |  size  | stdv |  stdv  | run  |\nOMM Ranking:-------+------+------+------------+------------+------------+------+--------+------+--------+------+\nOMM Ranking:      1      1      3      133.9        -97.9          -2.3      0.0       2      NA      NA    019\nOMM Ranking:      2      2      5      155.5        -79.2          -2.1      0.0       9      NA      NA    089\nOMM Ranking:      3      3      4      298.0        -29.2          -2.2      0.0      16      NA      NA    113\nOMM Ranking:      4      4      1      385.4        -56.3          -2.9      0.0      12      NA      NA    018\nOMM Ranking:      5      5      2    17172.8        -67.1          -2.3      0.0       6      NA      NA    020\nOMM Ranking:-------+------+------+------------+------------+------------+------+--------+------+--------+------+\nremoving working folder testDir1\/example1\n<\/textarea><\/div>\n<p>In addition to the default ADCP output files, this command will also generate \u201cexample1_omm_rescored_out.pdb\u201d containing minimized and reranked top-docked solutions (receptor+peptide) and amber topology and coordinate files for each reranked docked solutions in directory \u201ctestDir1\/example1_omm_amber_parm\u201d that can be used for the further analysis of docked poses and free-energy calculation using Molecular Dynamics (or other Molecular Mechanics) simulation.<\/p>\n<p><strong>Additional options:<\/strong><br \/>\nThe number of minimization iterations (-nitr), solvent environment (-env), and output order of re-ranked solutions (-dr) can also be used to control the openMM-based minimization behavior. For example:<\/p>\n<style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-7 > .CodeMirror, .fusion-syntax-highlighter-7 > .CodeMirror .CodeMirror-gutters {background-color:var(--awb-color1);}.fusion-syntax-highlighter-7 > .CodeMirror .CodeMirror-gutters { background-color: var(--awb-color2); }.fusion-syntax-highlighter-7 > .CodeMirror .CodeMirror-linenumber { color: var(--awb-color8); }<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-7 fusion-syntax-highlighter-theme-light\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:var(--awb-color3);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_7\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_7\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_7\" data-readOnly=\"nocursor\" data-lineNumbers=\"1\" data-lineWrapping=\"\" data-theme=\"default\" data-mode=\"text\/x-sh\">adcp -O -T 3Q47.trg -s \"grctksicfpd\" -cyc -N 5 -n 100000 -w testDir1 -o example1 -nmin 5 -nitr 500 -env implicit -dr -reint<\/textarea><\/div>\n<p>Description of each option:<br \/>\n-nitr 500: Defines 500 minimization steps for each docked pose.<br \/>\n-env implicit: The implicit solvent environment will be used for minimization. The default is minimization in vacuum.<br \/>\n-dr: To report the minimized solutions based on docking score ordered from best to worst. Default order is best to worst openMM-based ranking score.<br \/>\n-reint: To openMM-based ranking by interaction energy (Ecomplex -Ereceptor -Epeptide) rather than (Ecomplex -Ereceptor).<\/p>\n<p><strong>Minimization options for already docked solutions:<br \/>\n<\/strong><span style=\"text-decoration: underline;\">Post Docking Minimization (-pdmin)<\/span> : This option allows you to apply openMM minimization to already docked poses. When selected, ADCP will skip the re-docking step and instead initiate openMM minimization on poses from the previously docked output file. Ensure that you use the same target file (-T), jobName (-o), and sequence (-s) descriptions as you did during the docking process.<\/p>\n<p><span style=\"text-decoration: underline;\">Resume Failed minimization ( -resumemin )<\/span>: This option is used to continue an interrupted openMM minimization and re-ranking process. It can only be employed in conjunction with Post Docking Minimization (-pdmin) and NOT overwriting (-O) modes.<\/p>\n<p><strong>OpenMM-based minimization of ADCP docked poses containing non-standard amino acids:<br \/>\n<\/strong>By default, the force-field parameter set used for openMM-based minimization lacks parameters for most non-standard amino acids. Therefore, ADCP defaults to using the &#8220;sannerlab&#8221; openMM parameter set for 182 non-standard amino acids and the swiss openMM parameter set for 20 non-terminal non-standard amino acids. These parameter sets are specially designed for Swiss non-standard amino acids and require proper licensing obtained from the original developer of the SwissSideChain database. For a comprehensive list of supported non-standard amino acids, refer to the \/ADCP\/data\/openMMff\/AVAILABLE_PARAMETER.dat file.<\/p>\n<p>In cases where an openMM parameter set for a specific non-standard amino acid is unavailable or not provided, ADCP will utilize pdbfixer(v1.8) to substitute non-standard amino acids with standard ones. If pdbfixer cannot replace a non-standard amino acid, it will be mutated to &#8220;ALA&#8221; (alanine) for openMM-based re-ranking.<\/p>\n<p><strong>Other Options for Handling OpenMM-Based Minimization of Non-Standard Amino Acids:<br \/>\n<\/strong>-F: This option is used to specify the utilization of openMM parameter sets (swiss, sannerlab, or none) from the &#8216;ADCP\/data\/openMMff&#8217; directory. The &#8216;none&#8217; option can be chosen to restrict the use of any system default parameter sets.<\/p>\n<p>-f: To specify the use of user-defined (developed) openMM parameter sets for supporting new or unlisted non-standard amino acids. This requires three files containing force-field data, bond definitions, and hydrogen definitions. Ensure that you provide all three files in the same directory with the same initial names. For example, if you use &#8216;-f .\/XXXX_ff.xml&#8217;, the program will expect a force-field file (.\/XXXX_ff.xml), a bond definition file (.\/XXXX_residues.xml), and a hydrogen definition file (.\/XXXX_hydrogen_def.xml), all located in the same directory.<\/p>\n<\/div><div class=\"nav fusion-mobile-tab-nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-45cbd8c6fd81b715f6c\" aria-selected=\"false\" tabindex=\"-1\" id=\"mobile-fusion-tab-non-canonicalamino-acid\" href=\"#tab-45cbd8c6fd81b715f6c\"><h4 class=\"fusion-tab-heading\">Non-canonical amino-acid<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-pane fade fusion-clearfix\" role=\"tabpanel\" tabindex=\"0\" aria-labelledby=\"fusion-tab-non-canonicalamino-acid\" id=\"tab-45cbd8c6fd81b715f6c\">\n<p>ADCP v1.1 supports docking peptides containing non-natural amino acid (NSAA). Each NSAA has a name (e.g. PTR) and the software expects the find parameters for this non-natural sidechain in library files provided on the command line (see -l and -L options). ADCP ships with a library for natural amino acids (always loaded) and a library of fluorinated amino acids. We also developed parameters from all the amino acids from the <a href=\"https:\/\/www.swisssidechain.ch\/index.php\">SwissSideChain.<\/a> The somewhat restrictive license listed on the website will be replaced by a CC-BY 4.0 licence and we ahve been granted the right to distribute the ADCP library for this set of <a href=\"https:\/\/www.swisssidechain.ch\/data\/family_table.pdf\">209 amino acids<\/a> in D- and L- form.<\/p>\n<p>We have assembled a library comprising 182\/209 non-natural amino acids (NNAs) obtained from the SwissSideChain database, encompassing both L- and D-chiralities. This comprehensive library equips the ADCP with the capability to handle all currently existing NNAs found in the Protein Data Bank (PDB). To enable seamless integration of peptides containing NNAs at various positions within the peptide sequence into OpenMM, we undertook the following steps:<\/p>\n<p><strong>i) Partial Charges for NNAs:<\/strong>The partial charges provided by SwissSidechain\u00a0were originally designed for NNAs not situated at the N- or C-terminus of a peptide. Consequently, we calculated partial charges for NNAs in both terminal and non-terminal configurations using the R.E.D. (RESP ESP charge Derive) server, utilizing GAMESS as the backend for partial charge calculations. The process closely follows the steps described here: https:\/\/upjv.q4md-forcefieldtools.org\/Tutorial\/Tutorial-3.php#11. To represent\u00a0terminal and non-terminal configurations of each NNA, we appropriately capped them with ACE and\/or NME chemical groups.<\/p>\n<p><strong>ii) Force-Field Parameters:<\/strong>We utilized parmchk2 from Ambertools\u00a0to identify\u00a0all the necessary amber force-field parameters (including bond, angle, dihedral, improper, electrostatic, and van der Waals) based on the mol2 files generated by the R.E.D. server. These parameters were outputted\u00a0as an frcmod\u00a0file.<\/p>\n<p><strong>iii) FFXML Files:<\/strong>\u00a0We employed parmed\u00a0on the frcmod\u00a0and mol2 files to generate a pair of OpenMM-compatible FFXML format partial force-field files for each NNA variant. Subsequently, we combined the information from each pair of FFXML files into a single FFXML\u00a0file, which comprehensively represents\u00a0all the parameters required\u00a0for the Amber force field. In the end, all these separate FFXML\u00a0files were consolidated\u00a0into a single file, resulting in a complete set of parameters for 184\u00a0NNAs. This consolidated FFXML\u00a0file includes all the essential parameters for the Amber force field and can be loaded by OpenMM. As a result, the latest version of ADCP (v1.1) now supports NNAs and OpenMM.<\/p>\n<p>To efficiently utilize\u00a0this set of parameters in the OpenMM\u00a0engine, we made multiple adjustments during the loading, cleaning, and simulation for each structure:<\/p>\n<ol>\n<li>Preventing the removal or swapping of NSTs by loading the residue definition file in pdbfixer\u00a0and modifying\u00a0the pdbfixer.nonstandardResidues\u00a0list, which is subsequently\u00a0used for swapping.<\/li>\n<li>Introducing &#8216;OXT&#8217; at the C-terminal NSTs, addressing the missing step from pdbfixer. Since pdbfixer\u00a0uses modeler to add missing hydrogen atoms, it correctly handles N-terminal residues but does not accommodate terminal NSTs.<\/li>\n<li>Overriding the default hydrogen definition file reloading to incorporate NST-specific definitions or to apply specific parameter sets for residues with identical names (e.g., ORN).<\/li>\n<li>Supporting residues with identical molecular structures (e.g., THR and ALO) by providing specific residue templates for amino acids with similar structures.<\/li>\n<li>Overriding the PDB writing process to handle 4-letter NST codes, employing a modified pdbwriter.<\/li>\n<\/ol>\n<\/div><div class=\"nav fusion-mobile-tab-nav\"><ul class=\"nav-tabs\" role=\"tablist\"><li role=\"presentation\"><a class=\"tab-link\" data-toggle=\"tab\" role=\"tab\" aria-controls=\"tab-31a04be6bd09c2c39f2\" aria-selected=\"false\" tabindex=\"-1\" id=\"mobile-fusion-tab-tutorialtogeneratelibfileforannst\" href=\"#tab-31a04be6bd09c2c39f2\"><h4 class=\"fusion-tab-heading\">Tutorial To Generate Lib file for an NST<\/h4><\/a><\/li><\/ul><\/div><div class=\"tab-pane fade fusion-clearfix\" role=\"tabpanel\" tabindex=\"0\" aria-labelledby=\"fusion-tab-tutorialtogeneratelibfileforannst\" id=\"tab-31a04be6bd09c2c39f2\">\n<p>This tutorial explains the steps required to generate a rotamer file for a non-standard amino acid and incorporate it in ADCP to support docking peptides with the non-standarad amino acid.<\/p>\n<p><strong>Step 1:<\/strong><\/p>\n<p>To run this tutorial you need to download <a href=\"https:\/\/ccsb.scripps.edu\/mamba\/examples\/libGenExample.zip\">THIS<\/a> zip file with dummy non-standard amino acids and randomly generated Dunbrack-like rotamer files. First make a directory with your choice of name as I created &#8220;~\/ADCP_examples\/genLib&#8221;\u00a0 then<\/p>\n<p>cd ~\/ADCP_examples\/genLib<\/p>\n<p>Download command: wget https:\/\/ccsb.scripps.edu\/mamba\/examples\/libGenExample.zip<\/p>\n<p>Unzip downloaded\u00a0 file as:<\/p>\n<p>unzip libGenExample.zip<br \/>\nArchive: \u00a0libGenExample.zip<br \/>\ncreating: input\/<br \/>\ninflating: input\/rotamer_details.dat<br \/>\ncreating: input\/pdbfiles\/<br \/>\ncreating: input\/pdbfiles\/D\/<br \/>\ninflating: input\/pdbfiles\/D\/DSOO.pdb<br \/>\ninflating: input\/pdbfiles\/D\/DFOO.pdb<br \/>\ncreating: input\/pdbfiles\/L\/<br \/>\ninflating: input\/pdbfiles\/L\/FOO.pdb<br \/>\ninflating: input\/pdbfiles\/L\/SOO.pdb<br \/>\ncreating: input\/libfiles\/<br \/>\ninflating: input\/libfiles\/FOO_random1.lib<br \/>\ninflating: input\/libfiles\/SOO_random1.lib<br \/>\n&#8221;<\/p>\n<p>The extracted input directory has files arranged as:<\/p>\n<p>input\/<br \/>\n\u251c\u2500\u2500 libfiles<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 FOO_random1.lib<br \/>\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 SOO_random1.lib<br \/>\n\u251c\u2500\u2500 pdbfiles<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 D<br \/>\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u251c\u2500\u2500 DFOO.pdb<br \/>\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u2514\u2500\u2500 DSOO.pdb<br \/>\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 L<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 FOO.pdb<br \/>\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 SOO.pdb<br \/>\n\u2514\u2500\u2500 rotamer_details.dat<\/p>\n<p><strong>Step 2: Extract rotamer information<\/strong><\/p>\n<p>run command : extractRotamerInfo -l input\/libfiles\/ -p input\/pdbfiles\/ -i _random1.lib -r input\/rotamer_details.dat -o rotamerinfo.py<\/p>\n<p><span style=\"text-decoration: underline;\">output:\u00a0<\/span><\/p>\n<p>extractRotamerInfo -l input\/libfiles\/ -p input\/pdbfiles\/ -i _random1.lib -r input\/rotamer_details.dat -o rotamerinfo.py<br \/>\nfile &#8216;rotamerinfo.py&#8217; is created successfully. Run &#8216;makeLibFile&#8217; to generate lib file.<\/p>\n<p><strong>Step 3: generate lib file<\/strong><\/p>\n<p><span style=\"text-decoration: underline;\">run command:<\/span> run command: xxxxxx@xxxxxxx:~\/ADCP_examples\/genLib$ makeLibFile -p input\/pdbfiles -r input\/rotamer_details.dat -t rotamerinfo.py -o my_foo_soo.lib<\/p>\n<p><span style=\"text-decoration: underline;\">output:<\/span><\/p>\n<p>run command: xxxxxx@xxxxxxx:~\/ADCP_examples\/genLib$ makeLibFile -p input\/pdbfiles -r input\/rotamer_details.dat -t rotamerinfo.py -o my_foo_soo.lib<br \/>\nUsing residue list from &#8220;input\/rotamer_details.dat&#8221; for lib file generation!<br \/>\nWorking on AA: FOO<br \/>\nWorking on AA: SOO<br \/>\nWorking on AA: DFOO<br \/>\nWorking on AA: DSOO<br \/>\nADCP acceptable lib file: &#8216;my_foo_soo.lib&#8217; generated successfully<\/p>\n<p><strong>Step 4: Use the newly generated lib file in docking<\/strong><\/p>\n<p>You may need to download example <a href=\"https:\/\/ccsb.scripps.edu\/mamba\/examples\/3Q47.trg\">TRG<\/a> file to use this lib file in docking<\/p>\n<p>mkdir trialRun<\/p>\n<p>cd trialRun<\/p>\n<p>download trg file as:<\/p>\n<p>wget https:\/\/ccsb.scripps.edu\/mamba\/examples\/3Q47.trg<\/p>\n<p>run ADCP as:<\/p>\n<p>adcp -T 3Q47.trg -s &#8220;toto&amp;or&#8221; -w testDir -o myfoo -l ..\/my_foo_soo.lib -O -n 2000 -m 5<\/p>\n<p>output:<\/p>\n<p>xxxxxx@xxxxxxx:~\/ADCP_examples\/genLib\/trialRun$ adcp -T 3Q47.trg<br \/>\n-s &#8220;toto&amp;or&#8221; -w testDir -o myfoo -l ..\/my_foo_soo.lib -O -n 2000 -m<br \/>\n5<br \/>\nWarning: importing &#8216;simtk.openmm&#8217; is deprecated. \u00a0Import &#8216;openmm&#8217; instead.<br \/>\nInflating target file 3Q47.trg<br \/>\nperforming MC searches with: \/home\/xxxxxx\/micromamba\/envs\/adcpsuite\/lib\/python3.7\/s<br \/>\nite-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1<br \/>\ntarget data from file: 3Q47.trg<br \/>\njob name: myfoo, summary file myfoo_summary.dlg, docked poses: myfoo_out.pdb<br \/>\nDetected 8 cores, using 8 cores.<br \/>\nusing user rotamer library ..\/my_foo_soo.lib<br \/>\n\/home\/xxxxxx\/ADCP_examples\/genLib\/my_foo_soo.lib<br \/>\nPerforming 50 MC searches using 2000 evals each using a random seed.<br \/>\nPerforming search (50 ADCP runs with 2000 steps each) &#8230;<br \/>\n0% \u00a0\u00a010 \u00a0\u00a020 \u00a0\u00a030 \u00a0\u00a040 \u00a0\u00a050 \u00a0\u00a060 \u00a0\u00a070 \u00a0\u00a080 \u00a0\u00a090 \u00a0\u00a0100%<br \/>\n|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|&#8212;-|<br \/>\nDocking performed in 17.50 seconds, i.e. 0 hours 00 minutes 17.497510 seconds<br \/>\nbestEnergies [-8.65548, 5.90048, -5.13314, -2.50491, -9.35804, -9.19329, -2.81013, &#8211;<br \/>\n1.74652, 10.6427, -8.70252, 5.33932, -6.51859, -4.53209, -2.26573, -6.50981, 107.556<br \/>\n, -2.19785, 93.4734, -2.83973, 41.595, 1.46017, 21.8029, -5.90187, 5.43427, 57.0555,<br \/>\n-7.2611, 1.32635, -5.67726, 77.4642, 13.9936, -3.42446, -1.72998, -5.50438, 43.6464<br \/>\n, -9.0449, -0.338065, 28.147, 99.3097, -1.75186, 0.0199449, 57.5305, 1.69477, 17.885<br \/>\n4, -7.71046, 6.23085, 44.6776, -2.42758, -7.00984, -3.08003, -2.38094]\nbestEnergy in run 5 -9.358040 (0)<br \/>\nAnalyzing results &#8230;.<br \/>\nconcatenating trajectories for run with best energy &lt; 10.641960<br \/>\nconcatenated 50 trajectories<br \/>\nClustering MC trajectories based in contacts using cutoff: 0.800000<br \/>\nfinished calculating neighbors for 935 poses with 2.5 seconds<br \/>\nmode | \u00a0affinity \u00a0| ref. | clust. | rmsd | energy | best |<br \/>\n| (kcal\/mol) | fnc \u00a0| \u00a0size \u00a0| stdv | \u00a0stdv \u00a0| run \u00a0|<br \/>\n&#8212;&#8211;+&#8212;&#8212;&#8212;&#8212;+&#8212;&#8212;+&#8212;&#8212;&#8211;+&#8212;&#8212;+&#8212;&#8212;&#8211;+&#8212;&#8212;+<br \/>\n1 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0-5.5 \u00a0\u00a0\u00a0\u00a0\u00a00.0 \u00a0\u00a0\u00a0\u00a0\u00a012 \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0131<br \/>\n2 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0-5.4 \u00a0\u00a0\u00a0\u00a0\u00a00.0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a07 \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0155<br \/>\n3 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0-5.4 \u00a0\u00a0\u00a0\u00a0\u00a00.0 \u00a0\u00a0\u00a0\u00a0\u00a013 \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0688<br \/>\n4 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0-5.2 \u00a0\u00a0\u00a0\u00a0\u00a00.0 \u00a0\u00a0\u00a0\u00a0\u00a010 \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0255<br \/>\n5 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0-5.1 \u00a0\u00a0\u00a0\u00a0\u00a00.0 \u00a0\u00a0\u00a0\u00a0\u00a019 \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0\u00a0\u00a0NA \u00a0\u00a0\u00a0038<br \/>\nCalculations completed 20.23 seconds, i.e. 0 hours 00 minutes 17.497510 seconds<br \/>\nMC search command: cd testDir\/myfoo; \/home\/xxxxxx\/micromamba\/envs\/adcpsuite\/lib\/pyt<br \/>\nhon3.7\/site-packages\/ADCP\/CrankiteAD_Linux-x86_64_1.1 -t 2 &#8220;toto&amp;or&#8221;<br \/>\n-l \/home\/xxxxxx\/ADCP_examples\/genLib\/my_foo_soo.lib -T \/home\/xxxxxx\/ADCP_example<br \/>\ns\/genLib\/trialRun\/testDir\/myfoo\/3Q47 -r 1&#215;2000 -p Bias=NULL,external=5,constrains,1.<br \/>\n0,1.0,Opt=1,0.25,0.75,0.0 -s 443707 -o run_1.pdb<br \/>\nseed: [&#8216;184967&#8217;, &#8216;204672&#8217;, &#8216;248667&#8217;, &#8216;104977&#8217;, &#8216;845292&#8217;, &#8216;429831&#8217;, &#8216;870589&#8217;, &#8216;652790<br \/>\n&#8216;, &#8216;719532&#8217;, &#8216;124334&#8217;, &#8216;754509&#8217;, &#8216;373822&#8217;, &#8216;475064&#8217;, &#8216;81804&#8217;, &#8216;437507&#8217;, &#8216;778027&#8217;, &#8216;9<br \/>\n2723&#8217;, &#8216;273272&#8217;, &#8216;107599&#8217;, &#8216;210609&#8217;, &#8216;355627&#8217;, &#8216;291098&#8217;, &#8216;368513&#8217;, &#8216;843115&#8217;, &#8216;161654<br \/>\n&#8216;, &#8216;137867&#8217;, &#8216;302545&#8217;, &#8216;148886&#8217;, &#8216;923061&#8217;, &#8216;909799&#8217;, &#8216;425771&#8217;, &#8216;378073&#8217;, &#8216;147542&#8217;, &#8216;<br \/>\n178035&#8217;, &#8216;120937&#8217;, &#8216;540806&#8217;, &#8216;186303&#8217;, &#8216;843805&#8217;, &#8216;33583&#8217;, &#8216;625700&#8217;, &#8216;111739&#8217;, &#8216;16821<br \/>\n7&#8217;]\nremoving working folder testDir\/myfoo<\/p>\n<\/div><\/div><\/div><div class=\"fusion-clearfix\"><\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-223","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/pages\/223","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/comments?post=223"}],"version-history":[{"count":40,"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/pages\/223\/revisions"}],"predecessor-version":[{"id":450,"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/pages\/223\/revisions\/450"}],"wp:attachment":[{"href":"https:\/\/ccsb.scripps.edu\/adcpv11\/wp-json\/wp\/v2\/media?parent=223"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}