基于CSAMP策略构建准确预测蛋白-配体结合构象新方法的研究

分子对接是基于结构的药物设计(SBDD)研究领域中最常用的一种分子模拟方法。研究表明虽然某些分子对接方法构造出的蛋白-配体结合构象在全局势能面上的采样空间分布质量尚可，但是主流分子对接方法的打分函数总体上都不能很好地挑选/预测出与蛋白-配体晶体结构相近的最佳结合构象。针对这一科学问题，本项目拟基于CSAMP策略，即从粗略的（coarse）到中间的（medium）再到精细的（fine）理论水平势能面上进行“采样-窜跃-过滤”构建的“漏斗型”构象搜索与优化策略，发展出一种能够准确计算预测蛋白-配体结合构象的复合计算新方法。该方法的发展与完善不仅能为精细理论水平上研究配体参与的生物大分子性质与功能的分子机理提供准确可靠的结构信息，而且还能为SBDD研究领域提供一个现实可行的“精研”策略与方法。

The binding structure for the protein-ligand complex is a basic prerequisite for the structure-based drug design. Nevertheless, accurate protein binding structure determination presents a great challenge on experiment and theory. We propose to develop a new DOX protocol which combines the ensemble molecular Docking as the coarse level, structure Optimization with the semi-empirical 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 a couple of candidates to the fine level with the final top 1 binding mode. We expect DOX to be a promising computational route toward accurate prediction of the protein-ligand binding structures,and provides a refined tool for computer-aided drug design research.