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Locating binding poses in protein-ligand systems using reconnaissance metadynamics

机译:使用侦查元动力学在蛋白质-配体系统中定位结合姿势

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摘要

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin–benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations.
机译:提出了一种基于分子动力学的协议,用于发现和评分蛋白质-配体结合姿势。该协议使用最近开发的侦察超动力学方法,该方法采用自学习算法来构造一个偏见,将系统推离动力陷阱,否则该陷阱会保留下来。用这种算法探索相空间的速度大约是无偏分子动力学速度的六到八倍,并且仅受在蛋白质表面扩散所需时间的限制。我们将这种方法应用于经过深入研究的胰蛋白酶-苯甲m系统,并表明我们能够重新确定从参考EADock盲对接计算中获得的所有姿势。可以根据系统停留在姿势中的时间长度对这些姿势进行评分。或者,可以对输出轨迹执行降维,并获得可用于更昂贵的自由能计算的相空间图。

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