A reinforcement learning approach for protein–ligand binding pose prediction

A reinforcement learning approach for protein–ligand binding pose prediction

Abstract Protein ligand docking is an indispensable tool for computational prediction of protein functions and screening drug candidates. Despite significant progress over the past two decades, it is still a challenging problem, characterized by the still limited understanding of the energetics betw...

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Bibliographic Details
Main Authors: Chenran Wang, Yang Chen, Yuan Zhang, Keqiao Li, Menghan Lin, Feng Pan, Wei Wu, Jinfeng Zhang
Format: Article
Language:English
Published: BMC 2022-09-01
Series:BMC Bioinformatics
Subjects:
Protein ligand docking
Reinforcement learning
A3C
Asynchronous advantage actor-critic model
Protein ligand binding mode prediction
Protein ligand binding
Online Access:https://doi.org/10.1186/s12859-022-04912-7

Internet

https://doi.org/10.1186/s12859-022-04912-7

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