Synergistic application of molecular docking and machine learning for improved binding pose

Synergistic application of molecular docking and machine learning for improved binding pose

Accurate prediction of protein-ligand complex structures is a crucial step in structure-based drug design. Traditional molecular docking methods exhibit limitations in terms of accuracy and sampling space, while relying on machine-learning approaches may lead to invalid conformations. In this study,...

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Bibliographic Details
Main Authors: Li Yaqi, Lin Hongrui, Yang He, Yuan Yannan, Zou Rongfeng, Zhou Gengmo, Zheng Hang
Format: Article
Language:English
Published: Science Press 2024-03-01
Series:National Science Open
Subjects:
binding pose
molecular docking
machine learning
machine learning scoring function
Online Access:https://www.sciengine.com/doi/10.1360/nso/20230058

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https://www.sciengine.com/doi/10.1360/nso/20230058

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