Accurate prediction of protein–ligand interactions by combining physical energy functions and graph-neural networks

Accurate prediction of protein–ligand interactions by combining physical energy functions and graph-neural networks

Abstract We introduce an advanced model for predicting protein–ligand interactions. Our approach combines the strengths of graph neural networks with physics-based scoring methods. Existing structure-based machine-learning models for protein–ligand binding prediction often fall short in practical vi...

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Bibliographic Details
Main Authors: Yiyu Hong, Junsu Ha, Jaemin Sim, Chae Jo Lim, Kwang-Seok Oh, Ramakrishnan Chandrasekaran, Bomin Kim, Jieun Choi, Junsu Ko, Woong-Hee Shin, Juyong Lee
Format: Article
Language:English
Published: BMC 2024-11-01
Series:Journal of Cheminformatics
Subjects:
Virtual screening
Protein–ligand binding prediction
Hit discovery
Protein–ligand docking
Graph neural network
Protein–ligand binding pose prediction
Online Access:https://doi.org/10.1186/s13321-024-00912-2

Internet

https://doi.org/10.1186/s13321-024-00912-2

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