Enhanced Molecular Dynamics Method to Efficiently Increase the Discrimination Capability of Computational Protein-Protein Docking

被引：8

作者：

Scafuri, Nicola ^{[1
]}

Soler, Miguel A. ^{[1
]}

Spitaleri, Andrea ^{[1
,2
]}

Rocchia, Walter ^{[1
]}

机构：

[1] Ist Italiano Tecnol IIT, CONCEPT Lab, I-16152 Genoa, Italy

[2] IRCCS San Raffaele Sci Inst, Ctr Omics Sci, Emerging Bacterial Pathogens Unit, Milan, Italy

来源：

JOURNAL OF CHEMICAL THEORY AND COMPUTATION | 2021年 / 17卷 / 11期

关键词：

BINDING; SIMULATION; GROMACS; COMPLEXES; MECHANISM; DOMAIN;

D O I：

10.1021/acs.jctc.1c00789

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

Protein-protein docking typically consists of the generation of putative binding conformations, which are subsequently ranked by fast heuristic scoring functions. The simplicity of these functions allows for computational efficiency but has severe repercussions on their discrimination capabilities. In this work, we show the effectiveness of suitable descriptors calculated along short scaled molecular dynamics runs in recognizing the nearest-native bound conformation among a set of putative structures generated by the HADDOCK tool for eight protein-protein systems.

引用

页码：7271 / 7280

页数：10

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