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针对模型腔位点重新评分对接命中列表:预测与实验测试。

Rescoring docking hit lists for model cavity sites: predictions and experimental testing.

作者信息

Graves Alan P, Shivakumar Devleena M, Boyce Sarah E, Jacobson Matthew P, Case David A, Shoichet Brian K

机构信息

Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th Street, San Francisco, CA 94158-2330, USA.

出版信息

J Mol Biol. 2008 Mar 28;377(3):914-34. doi: 10.1016/j.jmb.2008.01.049. Epub 2008 Jan 30.

Abstract

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 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.

摘要

分子对接通过计算机针对蛋白质结构筛选数千到数百万个有机分子,寻找具有互补契合度的分子。该过程采用了许多近似方法,常常导致“命中率”较低。克服这些近似方法的一种策略是使用一种更好但更慢的方法对排名靠前的对接分子重新评分。分子力学广义玻恩表面积(MM - GBSA)技术就是这样一种方法。与大多数对接程序相比,这些更符合物理实际的方法在溶剂化、静电相互作用和构象变化方面具有改进的模型。为了研究MM - GBSA重新评分,我们在三个小的埋藏位点对对接命中列表进行了重新排序:一个结合非极性配体的疏水腔、一个结合芳基和氢键配体的稍带极性的腔以及一个结合阳离子配体的阴离子腔。这些位点很简单;因此,错误的预测可以归因于方法中的特定误差,并且实际上可以测试许多可能的配体。在回顾性计算中,与仅进行对接计算相比,采用结合位点最小化的MM - GBSA技术能更好地将每个腔的已知配体与已知诱饵区分开来。这鼓励我们对对接排名较差但经MM - GBSA重新评分后排名较好的分子进行前瞻性重新评分测试。总共对33个在三个腔中经MM - GBSA高度排名的分子进行了实验测试。其中,观察到有23个分子能结合——这些是通过重新评分挽救的对接假阴性分子。其余10个分子对接时为真阴性,经MM - GBSA重新评分后为假阳性。对这23个分子中的21个确定了X射线晶体结构。在许多情况下,MM - GBSA的几何结构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,重新评分后的几何结构未能捕捉到蛋白质中的大构象变化。有趣的是,重新评分不仅挽救了对接假阳性分子,还在排名靠前的分子中引入了几个新的假阳性分子。我们考虑了在这些模型腔位点中MM - GBSA重新评分成功与失败的原因以及在生物学相关靶点中重新评分的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e28/2752715/33648685e30f/nihms132333f1.jpg

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