The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction

The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction

Abstract Structure-based drug design depends on the detailed knowledge of the three-dimensional (3D) structures of protein–ligand binding complexes, but accurate prediction of ligand-binding poses is still a major challenge for molecular docking due to deficiency of scoring functions (SFs) and ignor...

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Bibliographic Details
Main Authors: Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang, Dongsheng Cao, Tingjun Hou
Format: Article
Language:English
Published: BMC 2021-10-01
Series:Journal of Cheminformatics
Subjects:
Scoring function (SF)
Machine learning (ML)
Molecular docking
Protein–ligand binding pose
Cross-docking
Online Access:https://doi.org/10.1186/s13321-021-00560-w

Internet

https://doi.org/10.1186/s13321-021-00560-w

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