侧链定位的消息传递方法及其在蛋白质对接优化中的应用。

Mohammad Moghadasi, Dima Kozakov, Artem B Mamonov, Pirooz Vakili, Sandor Vajda, Ioannis Ch Paschalidis
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引用次数: 3

摘要

介绍了一种解决侧链定位(SCP)问题的消息传递算法。SCP是蛋白质对接优化的关键组成部分,而蛋白质对接是计算结构生物学中一类重要问题的关键步骤。我们将SCP建模为一个组合优化问题,并将其表述为最大加权独立集(MWIS)问题。然后,我们采用一种改进的收敛信念传播算法来解决MWIS的松弛问题,并开发了随机估计启发式算法,使用松弛解来获得有效的MWIS可行解。使用一组蛋白质复合物的基准,我们证明了与不解决SCP的基线算法相比,我们的方法可以产生更准确的对接预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement.

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement.

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP.

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