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

被引：7

作者：

Kotelnikov, Sergei ^{[1
,2
,3
]}

Alekseenko, Andrey ^{[1
,2
]}

Liu, Cong ^{[1
,4
]}

Ignatov, Mikhail ^{[1
,2
,5
]}

Padhorny, Dzmitry ^{[1
,2
]}

Brini, Emiliano ^{[1
]}

Lukin, Mark ^{[6
]}

Coutsias, Evangelos ^{[1
,2
]}

Dill, Ken A. ^{[1
,4
,7
]}

Kozakov, Dima ^{[1
,2
,5
]}

机构：

[1] SUNY Stony Brook, Laufer Ctr Phys & Quantitat Biol, Stony Brook, NY 11794 USA

[2] SUNY Stony Brook, Dept Appl Math & Stat, Stony Brook, NY 11794 USA

[3] Innopolis Univ, Innopolis, Russia

[4] SUNY Stony Brook, Dept Chem, Stony Brook, NY 11794 USA

[5] SUNY Stony Brook, Inst Adv Computat Sci, Stony Brook, NY 11794 USA

[6] SUNY Stony Brook, Dept Pharmacol Sci, Stony Brook, NY 11794 USA

[7] SUNY Stony Brook, Dept Phys & Astron, Stony Brook, NY 11794 USA

来源：

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN | 2020年 / 34卷 / 02期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

D3R; Protein-ligand docking; Template-based docking; Macrocycles; BACE-1; PROTEIN DOCKING; SIDE-CHAIN; PERFORMANCE; PREDICTION; MINIMIZATION; PARAMETERS; ACCURACY;

D O I：

10.1007/s10822-019-00257-1

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design Data Resource blind Grand Challenge competition. This method was among the best performers in the competition, giving sub-angstrom prediction quality for the majority of the targets.

引用

页码：179 / 189

页数：11

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