A new paradigm for applying deep learning to protein–ligand interaction prediction
Protein–ligand interaction prediction presents a significant challenge in drug design.
Numerous machine learning and deep learning (DL) models have been developed to …
Numerous machine learning and deep learning (DL) models have been developed to …
Improving the accuracy of protein-ligand binding affinity prediction by deep learning models: benchmark and model
Introduction: The ability to discriminate among ligands binding to the same protein target in
terms of their relative binding affinity lies at the heart of structure-based drug design. Any …
terms of their relative binding affinity lies at the heart of structure-based drug design. Any …
Deep learning in drug design: protein-ligand binding affinity prediction
Computational drug design relies on the calculation of binding strength between two
biological counterparts especially a chemical compound, ie, a ligand, and a protein …
biological counterparts especially a chemical compound, ie, a ligand, and a protein …
Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions
Background Accurate prediction of protein–ligand binding affinity is important for lowering
the overall cost of drug discovery in structure-based drug design. For accurate predictions …
the overall cost of drug discovery in structure-based drug design. For accurate predictions …
Prediction of protein–ligand binding affinity via deep learning models
H Wang - Briefings in Bioinformatics, 2024 - academic.oup.com
Accurately predicting the binding affinity between proteins and ligands is crucial in drug
screening and optimization, but it is still a challenge in computer-aided drug design. The …
screening and optimization, but it is still a challenge in computer-aided drug design. The …
A versatile deep learning-based protein-ligand interaction prediction model for accurate binding affinity scoring and virtual screening
Protein--ligand interaction (PLI) prediction is critical in drug discovery, aiding the
identification and enhancement of molecules that effectively bind to target proteins. Despite …
identification and enhancement of molecules that effectively bind to target proteins. Despite …
DeepAtom: A framework for protein-ligand binding affinity prediction
The cornerstone of computational drug design is the calculation of binding affinity between
two biological counterparts especially a chemical compound, ie a ligand, and a protein …
two biological counterparts especially a chemical compound, ie a ligand, and a protein …
[HTML][HTML] Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: A review
The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, several deep learning …
affinities has the potential to transform drug discovery. In recent years, several deep learning …
FABind: Fast and accurate protein-ligand binding
Modeling the interaction between proteins and ligands and accurately predicting their
binding structures is a critical yet challenging task in drug discovery. Recent advancements …
binding structures is a critical yet challenging task in drug discovery. Recent advancements …
DEELIG: A deep learning approach to predict protein-ligand binding affinity
Protein-ligand binding prediction has extensive biological significance. Binding affinity helps
in understanding the degree of protein-ligand interactions and is a useful measure in drug …
in understanding the degree of protein-ligand interactions and is a useful measure in drug …