摘要
蛋白质-蛋白质相互作用(PPI)在各种生物过程中起着重要的作用,许多PPI被视药物发现的靶点。科学家在制定切实可行的蛋白质对接方法研究中做了很多努力。这些方法大多由两步组成:采样和计分。采样是用来产生一些似是而非的蛋白质-蛋白质结合的构象,计分可以对这些所有构象进行排列。由于结合界面灵活和接合面积大的特点,确定天然结构的在计算上是昂贵的,因此在蛋白质-蛋白质对接时,提高计算效率是最一项具有挑战性的任务。本文对一些既定的对接程序的采样,评分和加速算法的基本概念和实现,以及这些算法的局限性进行了讨论并提出了相关的建议。本文旨在更加深入的了解蛋白质-蛋白质对接,并为优化和改进的可用的方法提供参考。
关键词: 加速,GPU,机器学习,蛋白质对接,排名,评分函数。
图形摘要
Current Drug Targets
Title:Recent Advances in Protein-Protein Docking
Volume: 17 Issue: 14
Author(s): Qian Zhang, Ting Feng, Lei Xu, Huiyong Sun, Peichen Pan, Youyong Li, Dan Li, Tingjun Hou
Affiliation:
关键词: 加速,GPU,机器学习,蛋白质对接,排名,评分函数。
摘要: Protein-protein interactions (PPIs) play important roles in a variety of biological processes, and many PPIs have been regarded as biologically compelling targets for drug discovery. Extensive efforts have been made to develop feasible proteinprotein docking approaches to study PPIs in silico. Most of these approaches are composed of two stages: sampling and scoring. Sampling is used to generate a number of plausible protein-protein binding conformations and scoring can rank all those conformations. Due to large and flexible binding interface of PPI, determination of the near native structures is computationally expensive, and therefore computational efficiency is the most challenging issue in protein-protein docking. Here, we have reviewed the basic concepts and implementations of the sampling, scoring and acceleration algorithms in some established docking programs, and the limitations of these algorithms have been discussed. Then, some suggestions to the future directions for sampling, scoring and acceleration algorithms have been proposed. This review is expected to provide a better understanding of protein-protein docking and give some clues for the optimization and improvement of available approaches.
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Cite this article as:
Qian Zhang, Ting Feng, Lei Xu, Huiyong Sun, Peichen Pan, Youyong Li, Dan Li, Tingjun Hou , Recent Advances in Protein-Protein Docking, Current Drug Targets 2016; 17 (14) . https://dx.doi.org/10.2174/1389450117666160112112640
DOI https://dx.doi.org/10.2174/1389450117666160112112640 |
Print ISSN 1389-4501 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-5592 |
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