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...

Full description

Saved in:
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
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s13321-025-00955-z

Similar Items