Rescoring docking hit lists for model cavity sites: Predictions and experimental testing
Rescoring docking hit lists for model cavity sites: Predictions and experimental testing
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DOI：
10.1016/j.jmb.2008.01.049
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发表时间：
2008-03-28
影响因子：
5.6
通讯作者：
Shoichet, Brian K.
中科院分区：
文献类型：
--
作者：
Graves, Alan P.;Shivakumar, Devleena M.;Shoichet, Brian K.
分子对接通过计算筛选数千至数百万个有机分子与蛋白质结构，寻找具有互补配合的分子。进行了许多近似，通常会导致较低的“命中率”。克服这些近似的策略是使用更好但更慢的方法对排名靠前的对接分子进行重新评分。其中之一是分子力学广义玻恩表面积（MM - GBSA）技术。与大多数对接程序相比，这些更加物理真实的方法改进了溶剂化和静电相互作用以及构象 1 变化的模型。为了研究 MM-GBSA 重新评分，我们对三个小掩埋位点中的对接命中列表进行了重新排序：结合非极性配体的疏水空腔、结合芳基和氢键配体的弱极性空腔以及结合阳离子配体的阴离子空腔。这些网站很简单；因此，不正确的预测可以归因于方法中的特定错误，并且实际上可以测试许多可能的配体。在回顾性计算中，与单独的对接计算相比，结合位点最小化的 MM-GBSA 技术可以更好地区分每个腔的已知配体与已知诱饵。这鼓励我们对通过对接排名较差但在 MM - GBSA 重新评分时排名良好的分子进行前瞻性测试。实验测试了 MM-GBSA 对三个腔体高度排名的总共 33 个分子。其中，23 个被观察到结合 - 这些是通过重新评分挽救的对接假阴性。其余 10 个分子通过对接为真阴性，通过 MM - GBSA 为假阳性。确定了这 23 个分子中 21 个的 X 射线晶体结构。在许多情况下，MM-GBSA 的几何预测改进了初始对接姿势并且更接近晶体学结果；然而在一些情况下，重新记录的几何结构未能捕获蛋白质中较大的构象变化。有趣的是，重新评分不仅挽救了对接假阳性，而且还在排名靠前的分子中引入了一些新的假阳性。我们考虑了在这些模型腔位点中 MM-GBSA 重新评分成功和失败的根源以及在生物学相关目标中重新评分的前景。 (c) 2008 年，爱思唯尔有限公司出版。
Molecular docking computationally screens thousands to millions of organic molecules against protein structures, looking for those with complementary fits. Many approximations are made, often resulting in low "hit rates." A strategy to overcome these approximations is to rescore top-ranked docked molecules using a better but slower method. One such is afforded by molecular mechanics-generalized Born surface area (MM - GBSA) techniques. These more physically realistic methods have improved models for solvation and electrostatic interactions and conformational 1 change compared to most docking programs. To investigate MM - GBSA rescoring, we re-ranked docking hit lists in three small buried sites: a hydrophobic cavity that binds apolar ligands, a slightly polar cavity that binds aryl and hydrogen-bonding ligands, and an anionic cavity that binds cationic ligands. These sites are simple; consequently, incorrect predictions can be attributed to particular errors in the method, and many likely ligands may actually be tested. In retrospective calculations, MM-GBSA techniques with binding-site minimization better distinguished the known ligands for each cavity from the known decoys compared to the docking calculation alone. This encouraged us to test rescoring prospectively on molecules that ranked poorly by docking but that ranked well when rescored by MM - GBSA. A total of 33 molecules highly ranked by MM-GBSA for the three cavities were tested experimentally. Of these, 23 were observed to bind - these are docking false negatives rescued by rescoring. The 10 remaining molecules are true negatives by docking and false positives by MM - GBSA. X-ray crystal structures were determined for 21 of these 23 molecules. In many cases, the geometry prediction by MM-GBSA improved the initial docking pose and more closely resembled the crystallographic result; yet in several cases, the rescored geometry failed to capture large conformational changes in the protein. Intriguingly, rescoring not only rescued docking false positives, but also introduced several new false positives into the top-ranking molecules. We consider the origins of the successes and failures in MM-GBSA rescoring in these model cavity sites and the prospects for rescoring in biologically relevant targets. (c) 2008 Published by Elsevier Ltd.