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基于图形处理器的蛋白质-配体复合物的快速力场优化。

Fast force field-based optimization of protein-ligand complexes with graphics processor.

机构信息

Center for Bioinformatics, University of Hamburg, Bundesstr. 43, 20146 Hamburg, Germany.

出版信息

J Comput Chem. 2012 Dec 15;33(32):2554-65. doi: 10.1002/jcc.23094. Epub 2012 Aug 22.

Abstract

Usually based on molecular mechanics force fields, the post-optimization of ligand poses is typically the most time-consuming step in protein-ligand docking procedures. In return, it bears the potential to overcome the limitations of discretized conformation models. Because of the parallel nature of the problem, recent graphics processing units (GPUs) can be applied to address this dilemma. We present a novel algorithmic approach for parallelizing and thus massively speeding up protein-ligand complex optimizations with GPUs. The method, customized to pose-optimization, performs at least 100 times faster than widely used CPU-based optimization tools. An improvement in Root-Mean-Square Distance (RMSD) compared to the original docking pose of up to 42% can be achieved.

摘要

通常基于分子力学力场,配体构象的后优化是蛋白质-配体对接过程中最耗时的步骤。作为回报,它有可能克服离散构象模型的局限性。由于问题的并行性质,最近的图形处理单元 (GPU) 可用于解决这一难题。我们提出了一种新的算法方法,用于通过 GPU 并行化和大大加快蛋白质-配体复合物优化。该方法针对构象优化进行了定制,其速度至少比广泛使用的基于 CPU 的优化工具快 100 倍。与原始对接构象相比,均方根偏差 (RMSD) 可提高高达 42%。

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