DOCK 6受体脱溶评分和共价取样的发展:在RAS测试集上评估的方法。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Y Stanley Tan, Mayukh Chakrabarti, Reed M Stein, Lauren E Prentis, Robert C Rizzo, Tom Kurtzman, Marcus Fischer, Trent E Balius
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引用次数: 0

摘要

分子对接方法广泛应用于药物发现工作。RAS蛋白是重要的癌症药物靶点,是评估对接方法的有用系统,包括计算溶剂化效应和共价小分子结合。水在与RAS蛋白结合的小分子过程中往往起着关键作用,而许多抑制剂──包括fda批准的药物──都与致癌的RAS蛋白共价结合。我们组装了一个RAS测试集,包括138个RAS蛋白结构和2个带配体的KRAS DNA结构。在DOCK 6中,我们实现了一个受体解耦评分函数和一个共价对接算法。这些新特征使用测试集进行评估,包括姿态再现、交叉对接和富集计算。我们测试了两种溶剂化方法来生成受体脱溶评分网格:GIST和3D-RISM。使用GIST或3D-RISM的网格,使用高斯加权预先计算水的位移,并使用三线性插值来加速评分计算。为了测试受体脱溶评分,我们为测试集中的所有KRAS系统准备了GIST和3D-RISM网格,并比较了有和没有受体脱溶的富集性能。使用GIST计算受体脱溶提高了51%的系统的富集程度,降低了35%的系统的富集程度,而使用3D-RISM计算受体脱溶提高了44%的系统的富集程度,降低了30%的系统的富集程度。为了更严格地测试使用3D-RISM的受体脱溶,我们比较了有和没有3D-RISM受体脱溶的姿势繁殖。与不使用3D-RISM的对接相比,使用3D-RISM的姿势复制对接成功率提高了1.8±2.41%。考虑到受体的脱溶提供了一个小的,但显著的,在富集和姿势繁殖方面的改进。我们在70个含有共价配体的KRAS系统上测试了共价附着和生长算法,在共价和非共价对接之间获得了相似的姿态繁殖成功率。与非共价对接相比,实验生成的配体构象和smile生成的配体构象的对接成功率分别提高了2.4±3.29%和1.27±3.33%。作为概念验证,我们使用来自Enamine REAL数据库的340万种按需制作丙烯酰胺化合物,针对KRAS的开关II口袋进行了有和没有受体脱溶评分的共价虚拟筛选。平均而言,附着生长算法在屏幕上的每个分子花费大约17.61秒。测试集可在https://github.com/tbalius/teb_docking_test_sets上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Receptor Desolvation Scoring and Covalent Sampling in DOCK 6: Methods Evaluated on a RAS Test Set.

Molecular docking methods are widely used in drug discovery efforts. RAS proteins are important cancer drug targets, and are useful systems for evaluating docking methods, including accounting for solvation effects and covalent small molecule binding. Water often plays a key role in small molecule binding to RAS proteins, and many inhibitors─including FDA-approved drugs─covalently bind to oncogenic RAS proteins. We assembled a RAS test set, consisting of 138 RAS protein structures and 2 structures of KRAS DNA in complex with ligands. In DOCK 6, we have implemented a receptor desolvation scoring function and a covalent docking algorithm. These new features were evaluated using the test set, with pose reproduction, cross-docking, and enrichment calculations. We tested two solvation methods for generating receptor desolvation scoring grids: GIST and 3D-RISM. Using grids from GIST or 3D-RISM, water displacements are precomputed with Gaussian-weighting, and trilinear interpolation is used to speed up this scoring calculation. To test receptor desolvation scoring, we prepared GIST and 3D-RISM grids for all KRAS systems in the test set, and we compare enrichment performance with and without receptor desolvation. Accounting for receptor desolvation using GIST improves enrichment for 51% of systems and worsens enrichment for 35% of systems, while using 3D-RISM improves enrichment for 44% of systems and worsens enrichment for 30% of systems. To more rigorously test accounting for receptor desolvation using 3D-RISM, we compare pose reproduction with and without 3D-RISM receptor desolvation. Pose reproduction docking with 3D-RISM yields a 1.8 ± 2.41% increase in success rate compared to docking without 3D-RISM. Accounting for receptor desolvation provides a small, but significant, improvement in both enrichment and pose reproduction for this set. We tested the covalent attach-and-grow algorithm on 70 KRAS systems containing covalent ligands, obtaining similar pose reproduction success rates between covalent and noncovalent docking. Comparing covalent docking to noncovalent docking, there is a 2.4 ± 3.29% increase and a 1.27 ± 3.33% decline in the success rate when docking with experimental and SMILES-generated ligand conformations, respectively. As a proof-of-concept, we performed covalent virtual screens with and without receptor desolvation scoring, targeting the switch II pocket of KRAS, using 3.4 million make-on-demand acrylamide compounds from the Enamine REAL database. On average, the attach-and-grow algorithm spends approximately 17.61 s per molecule across the screen. The test set is available at https://github.com/tbalius/teb_docking_test_sets.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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