Institute of Functional Nano & Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University , Suzhou, Jiangsu 215123, China.
J Chem Inf Model. 2013 Oct 28;53(10):2743-56. doi: 10.1021/ci400382r. Epub 2013 Sep 24.
In this study, we developed and evaluated a novel parallel virtual screening strategy by integrating molecular docking and complex-based pharmacophore searching based on multiple protein structures. First, the capacity of molecular docking or pharmacophore searching based on any single structure from nine crystallographic structures of Rho kinase 1 (ROCK1) to distinguish the known ROCK1 inhibitors from noninhibitors was evaluated systematically. Then, the naı̈ve Bayesian classification or recursive partitioning technique was employed to integrate the predictions from molecular docking and complex-based pharmacophore searching based on multiple crystallographic structures of ROCK1, and the integrated protocol yields much better performance than molecular docking or complex-based pharmacophore searching based on any single ROCK1 structure. Finally, the well-validated integrated virtual screening protocol was applied to identify potential inhibitors of ROCK1 from traditional chinese medicine (TCM). The obtained potential active compounds from TCM are structurally novel and diverse compared with the known inhibitors of ROCK1, and they may afford valuable clues for the development of potent ROCK1 inhibitors.
在这项研究中，我们开发并评估了一种新的平行虚拟筛选策略，该策略通过整合基于多个蛋白质结构的分子对接和基于复合物的药效团搜索。首先，系统评估了基于九种 Rho 激酶 1（ROCK1）晶体结构中的任意单一结构的分子对接或药效团搜索，以区分已知的 ROCK1 抑制剂和非抑制剂的能力。然后，采用朴素贝叶斯分类或递归分割技术整合来自 ROCK1 多个晶体结构的分子对接和基于复合物的药效团搜索的预测，与基于任何单个 ROCK1 结构的分子对接或基于复合物的药效团搜索相比，集成方案的性能要好得多。最后，将经过充分验证的集成虚拟筛选方案应用于从中药中鉴定 ROCK1 的潜在抑制剂。与已知的 ROCK1 抑制剂相比，从中药中获得的潜在活性化合物在结构上新颖多样，它们可能为开发有效的 ROCK1 抑制剂提供有价值的线索。
