Literature DB >> 30421350

Monte Carlo on the manifold and MD refinement for binding pose prediction of protein-ligand complexes: 2017 D3R Grand Challenge.

Mikhail Ignatov1,2,3,4, Cong Liu2, Andrey Alekseenko5,4, Zhuyezi Sun6, Dzmitry Padhorny1,2,3,4, Sergei Kotelnikov1,2,3,7,4, Andrey Kazennov7,4, Ivan Grebenkin5,4, Yaroslav Kholodov5,4, Istvan Kolosvari6, Alberto Perez2, Ken Dill2, Dima Kozakov8,9,10.   

Abstract

Manifold representations of rotational/translational motion and conformational space of a ligand were previously shown to be effective for local energy optimization. In this paper we report the development of the Monte-Carlo energy minimization approach (MCM), which uses the same manifold representation. The approach was integrated into the docking pipeline developed for the current round of D3R experiment, and according to D3R assessment produced high accuracy poses for Cathepsin S ligands. Additionally, we have shown that (MD) refinement further improves docking quality. The code of the Monte-Carlo minimization is freely available at https://bitbucket.org/abc-group/mcm-demo .

Entities:  

Keywords:  Cathepsin S; D3R; MD; Manifold; Minimization; Monte Carlo

Mesh：

Substances：

Year:  2018        PMID： 30421350      PMCID： PMC6816043          DOI： 10.1007/s10822-018-0176-0

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN： 0920-654X            Impact factor:   3.686


  20 in total

1.  Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation.

Authors:  Araz Jakalian; David B Jack; Christopher I Bayly
Journal:  J Comput Chem       Date:  2002-12       Impact factor: 3.376

2.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

3.  Basic local alignment search tool.

Authors:  S F Altschul; W Gish; W Miller; E W Myers; D J Lipman
Journal:  J Mol Biol       Date:  1990-10-05       Impact factor: 5.469

4.  Systematic Parameterization of Monovalent Ions Employing the Nonbonded Model.

Authors:  Pengfei Li; Lin Frank Song; Kenneth M Merz
Journal:  J Chem Theory Comput       Date:  2015-03-13       Impact factor: 6.006

5.  AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

Authors:  Oleg Trott; Arthur J Olson
Journal:  J Comput Chem       Date:  2010-01-30       Impact factor: 3.376

Review 6.  Cathepsin S: therapeutic, diagnostic, and prognostic potential.

Authors:  Richard D A Wilkinson; Rich Williams; Christopher J Scott; Roberta E Burden
Journal:  Biol Chem       Date:  2015-08       Impact factor: 3.915

7.  LIGSIFT: an open-source tool for ligand structural alignment and virtual screening.

Authors:  Ambrish Roy; Jeffrey Skolnick
Journal:  Bioinformatics       Date:  2014-10-21       Impact factor: 6.937

8.  Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation.

Authors:  Sergei Grudinin; Maria Kadukova; Andreas Eisenbarth; Simon Marillet; Frédéric Cazals
Journal:  J Comput Aided Mol Des       Date:  2016-10-07       Impact factor: 3.686

9.  Energy Minimization on Manifolds for Docking Flexible Molecules.

Authors:  Hanieh Mirzaei; Shahrooz Zarbafian; Elizabeth Villar; Scott Mottarella; Dmitri Beglov; Sandor Vajda; Ioannis Ch Paschalidis; Pirooz Vakili; Dima Kozakov
Journal:  J Chem Theory Comput       Date:  2015-03-10       Impact factor: 6.006

10.  Iterative Knowledge-Based Scoring Functions Derived from Rigid and Flexible Decoy Structures: Evaluation with the 2013 and 2014 CSAR Benchmarks.

Authors:  Chengfei Yan; Sam Z Grinter; Benjamin Ryan Merideth; Zhiwei Ma; Xiaoqin Zou
Journal:  J Chem Inf Model       Date:  2015-10-01       Impact factor: 4.956
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  5 in total

1.  Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4.

Authors:  Maria Kadukova; Vladimir Chupin; Sergei Grudinin
Journal:  J Comput Aided Mol Des       Date:  2019-11-29       Impact factor: 3.686

2.  Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4.

Authors:  Sergei Kotelnikov; Andrey Alekseenko; Cong Liu; Mikhail Ignatov; Dzmitry Padhorny; Emiliano Brini; Mark Lukin; Evangelos Coutsias; Ken A Dill; Dima Kozakov
Journal:  J Comput Aided Mol Des       Date:  2019-12-26       Impact factor: 3.686

3.  Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Authors:  Yuwei Yang; Jianing Lu; Chao Yang; Yingkai Zhang
Journal:  J Comput Aided Mol Des       Date:  2019-11-15       Impact factor: 3.686

4.  D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

Authors:  Conor D Parks; Zied Gaieb; Michael Chiu; Huanwang Yang; Chenghua Shao; W Patrick Walters; Johanna M Jansen; Georgia McGaughey; Richard A Lewis; Scott D Bembenek; Michael K Ameriks; Tara Mirzadegan; Stephen K Burley; Rommie E Amaro; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2020-01-23       Impact factor: 3.686

5.  Correlation of cathepsin S with coronary stenosis degree, carotid thickness, blood pressure, glucose and lipid metabolism and vascular endothelial function in atherosclerosis.

Authors:  Shengyang Huang; Yu Cao
Journal:  Exp Ther Med       Date:  2019-11-19       Impact factor: 2.447
  5 in total

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