StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction

Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impe...

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Bibliographic Details
Main Authors:	Arjun Kaneriya, Madhav Samudrala, Harrish Ganesh, James Moran, Somanath Dandibhotla, Sivanesan Dakshanamurthy
Format:	Article
Language:	English
Published:	MDPI AG 2025-05-01
Series:	Bioengineering
Subjects:	protein–ligand binding affinity machine learning drug discovery structure-based graph neural network
Online Access:	https://www.mdpi.com/2306-5354/12/5/505
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StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction

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