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从粗粒化模拟中探索构象转变途径。

Exploration of conformational transition pathways from coarse-grained simulations.

机构信息

Institute for Research in Biomedicine (IRB Barcelona), Joint IRB-BSC Program in Computational Biology, Baldiri Reixac 10, Barcelona, Spain.

出版信息

Bioinformatics. 2013 Aug 15;29(16):1980-6. doi: 10.1093/bioinformatics/btt324. Epub 2013 Jun 5.

Abstract

MOTIVATION

A new algorithm to trace conformational transitions in proteins is presented. The method uses discrete molecular dynamics as engine to sample protein conformational space. A multiple minima Go-like potential energy function is used in combination with several enhancing sampling strategies, such as metadynamics, Maxwell Demon molecular dynamics and essential dynamics. The method, which shows an unprecedented computational efficiency, is able to trace a wide range of known experimental transitions. Contrary to simpler methods our strategy does not introduce distortions in the chemical structure of the protein and is able to reproduce well complex non-linear conformational transitions. The method, called GOdMD, can easily introduce additional restraints to the transition (presence of ligand, known intermediate, known maintained contacts, …) and is freely distributed to the community through the Spanish National Bioinformatics Institute (http://mmb.irbbarcelona.org/GOdMD).

AVAILABILITY

Freely available on the web at http://mmb.irbbarcelona.org/GOdMD.

摘要

动机

提出了一种新的算法来追踪蛋白质构象转变。该方法使用离散分子动力学作为引擎来采样蛋白质构象空间。使用类似于 Go 的多局部最小势能函数,并结合几种增强采样策略,如元动力学、Maxwell Demon 分子动力学和本征动力学。该方法具有前所未有的计算效率,能够追踪广泛的已知实验转变。与更简单的方法不同,我们的策略不会对蛋白质的化学结构造成扭曲,并能够很好地再现复杂的非线性构象转变。该方法称为 GOdMD,可以轻松地对转变(配体的存在、已知的中间状态、已知的保持接触状态等)引入额外的约束,并通过西班牙国家生物信息学研究所(http://mmb.irbbarcelona.org/GOdMD)免费提供给社区。

可用性

可在网页上免费获得,网址为 http://mmb.irbbarcelona.org/GOdMD。

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