Conformation Search Across Multiple-Level Potential-Energy Surfaces (CSAMP): A Strategy for Accurate Prediction of Protein-Ligand Binding Structures
Conformation Search Across Multiple-Level Potential-Energy Surfaces (CSAMP): A Strategy for Accurate Prediction of Protein-Ligand Binding Structures
复制标题
多级势能面 (CSAMP) 的构象搜索：准确预测蛋白质-配体结合结构的策略
DOI：
10.1021/acs.jctc.8b01150
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发表时间：
2019
影响因子：
5.5
通讯作者：
Wan Jian
中科院分区：
文献类型：
--
作者：
Wei Lin;Chi Bo;Ren Yanliang;Rao Li;Wu Jue;Shang Huan;Liu Jiaqi;Xiao Yiting;Ma Minghui;Xu Xin;Wan Jian
准确的蛋白质结合结构测定对实验和理论都是一个巨大的挑战。在这项工作中，我们提出了一种新的DOX协议，它结合了系综分子对接作为粗水平，结构优化和半经验量子力学方法作为中水平，扩展的ONIOM(XO)计算作为精细水平。DOX协议的基本原理依赖于跨多能级势能面的构象搜索(CSAMP)策略，即从包含数百个候选的漏斗状结构的粗略水平搜索到具有大约10个顶级候选的中等水平，再到具有最终的前1或2个结合模式的精细水平。对由他汀类药物、SDase抑制剂、3HNRase抑制剂和NA抑制剂组成的28个结晶学数据进行了深入的测试，得到了令人满意的结果，几何构型的∼均方根偏差(RMSD)为0.5%，相对结合能的绝对误差∼为0.8千卡/摩尔。在ASTEX测试集(包括85个不同的结构)上进行的进一步更大规模的验证显示了令人印象深刻的性能，RMSD<；2？成功率为99%，这表明DOX是准确预测蛋白质-配体结合结构的一种有前途的计算方法。
Accurate protein binding structure determination presents a great challenge to both experiment and theory. Here, in this work, we propose a new DOX protocol which combines the ensemble molecular Docking as the coarse-level, structure Optimization with the semiempirical quantum mechanics methods as the medium level, and the eXtended ONIOM (XO) calculations as the fine level. The fundamental of the DOX protocol relies on the Conformation Search Across Multiple-level Potential-energy surfaces (CSAMP) strategy, where the conformation spaces of a funnel-like structure are searched from the coarse level with hundreds of candidates to the medium level with around 10 top candidates to the fine level with the final top 1 or 2 binding modes. An in-depth test for the protocol set up against 28 crystallographic data consisting of HMGR-statins, SDase-inhibitors, 3HNRase-inhibitors, and NA-inhibitors yielded a satisfactory result with ∼0.5 Å root-mean-square deviations (RMSDs) on geometries and ∼0.8 kcal/mol absolute error of relative binding energies on average. A further larger scale validation on the Astex test set (including 85 diverse structures) revealed an impressive performance with a RMSD < 2 Å success rate of 99%, suggesting DOX is a promising computational route toward accurate prediction of the protein–ligand binding structures.