The algebraic extended atom-type graph-based model for precise ligand–receptor binding affinity prediction

The algebraic extended atom-type graph-based model for precise ligand–receptor binding affinity prediction

Abstract Accurate prediction of ligand-receptor binding affinity is crucial in structure-based drug design, significantly impacting the development of effective drugs. Recent advances in machine learning (ML)–based scoring functions have improved these predictions, yet challenges remain in modeling...

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Bibliographic Details
Main Authors: Farjana Tasnim Mukta, Md Masud Rana, Avery Meyer, Sally Ellingson, Duc D. Nguyen
Format: Article
Language:English
Published: BMC 2025-01-01
Series:Journal of Cheminformatics
Subjects:
Algebraic graph learning
Extended atom type
Similarity computation
Non-redundant training sets
Protein-ligand interactions
Binding affinity predictions
Online Access:https://doi.org/10.1186/s13321-025-00955-z
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