药效团
对接(动物)
计算机科学
工作流程
虚拟筛选
药物发现
分子动力学
蛋白质-配体对接
计算生物学
生化工程
鉴定(生物学)
人工智能
机器学习
最佳实践
数据科学
实施
仿形(计算机编程)
药物设计
组合化学
数据挖掘
化学
数量结构-活动关系
管理科学
力场(虚构)
作者
Juan Manuel Prieto,Jose A.D Cuellar Estrada,Camila Mara Clemente,Marcelo Adrian Marti
标识
DOI:10.1021/acs.jcim.6c00082
摘要
In this work, we present practical recommendations for the setup, analysis, and integration of mixed-solvent molecular dynamics (MixMD), solvent-biased docking (SSBD) workflows and pharmacophore analysis, drawing on more than a decade of accumulated experience in the field from multiple implementations and applications. Rather than providing a comprehensive review of all applications of MixMD, this Perspective focuses specifically on its use as a methodological foundation for deriving solvent sites that inform docking and pharmacophore-based strategies in structure-based drug design. Currently, mixed-solvent simulations and solvent-biased docking constitute a coherent, experimentally validated strategy for identifying and exploiting binding hot spots in proteins, and for translating solvent occupancy patterns into structurally interpretable pharmacophoric features and docking constraints. By standardizing best practices, and synthesizing previously published computational studies into a unified methodological framework, we aim to facilitate broader adoption of these methods within the structure-based drug design community, enabling more reliable identification of functional sites and accelerating rational ligand discovery.
科研通智能强力驱动
Strongly Powered by AbleSci AI