DeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction

DeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction

Abstract Predicting protein-ligand binding affinity is essential for understanding protein-ligand interactions and advancing drug discovery. Recent research has demonstrated the advantages of sequence-based models and graph-based models. In this study, we present a novel hybrid multimodal approach,...

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Bibliographic Details
Main Authors: Guishen Wang, Hangchen Zhang, Mengting Shao, Yuncong Feng, Chen Cao, Xiaowen Hu
Format: Article
Language:English
Published: BMC 2024-12-01
Series:Journal of Cheminformatics
Subjects:
Protein-ligand binding affinity prediction
Transformer
Graph isomorphism network
Multimodal
Online Access:https://doi.org/10.1186/s13321-024-00938-6
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