A Multi-perspective Model for Protein –Ligand-Binding Affinity Prediction

AbstractGathering information from multi-perspective graphs is an essential issue for many applications especially for protein –ligand-binding affinity prediction. Most of traditional approaches obtained such information individually with low interpretability. In this paper, we harness the rich information from multi-perspective graphs with a general model, which abstractly represents protein–ligand complexes with bette r interpretability while achieving excellent predictive performance. In addition, we specially analyze the protein–ligand-binding affinity problem, taking into account the heterogeneity of proteins and ligands. Experimental evaluations demonstrate the effectiveness of our data representation strat egy on public datasets by fusing information from different perspectives. All codes are available in thehttps://github.com/Jthy-af/HaPPy.Graphical Abstract

Source: Interdisciplinary Sciences, Computational Life Sciences - October 10, 2023 Category: Bioinformatics Source Type: research