Performance Evaluation of Docking Programs- Glide, GOLD, AutoDock & SurflexDock, Using Free Energy Perturbation Reference Data: A Case Study of Fructose-1, 6-bisphosphatase-AMP Analogs

自动停靠 对接(动物) 化学 排名(信息检索) 计算机科学 自由能微扰 计算化学 分子动力学 人工智能 生物化学 医学 基因 护理部 生物信息学
作者
K. Kumar Reddy,R.S. Rathore,P. Srujana,Raghunadha Reddy Burri,C. Ravikumar Reddy,Mogili Sumakanth,Pallu Reddanna,M. Rami Reddy
出处
期刊:Mini-reviews in Medicinal Chemistry [Bentham Science Publishers]
卷期号:20 (12): 1179-1187 被引量:11
标识
DOI:10.2174/1389557520666200526183353
摘要

Background: The accurate ranking of analogs of lead molecules with respect to their estimated binding free energies to drug targets remains highly challenging in molecular docking due to small relative differences in their free energy values. Methods: Free energy perturbation (FEP) method, which provides the most accurate relative binding free energy values were earlier used to calculate free energies of many ligands for several important drug targets including Fructose-1,6-BisphosPhatase (FBPase). The availability of abundant structural and experimental binding affinity data for FBPase inhibitors provided an ideal system to evaluate four widely used docking programs, AutoDock, Glide, GOLD and SurflexDock, distinct from earlier comparative evaluation studies. Results: The analyses suggested that, considering various parameters such as docking pose, scoring and ranking accuracy, sensitivity analysis and newly introduced relative ranking score, Glide provided reasonably consistent results in all respects for the system studied in the present work. Whereas GOLD and AutoDock also demonstrated better performance, AutoDock results were found to be significantly superior in terms of scoring accuracy compared to the rest. Conclusion: Present analysis serves as a useful guide for researchers working in the field of lead optimization and for developers in upgradation of the docking programs.
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