Deep learning methods, which can predict the binding affinity of a drug–target protein
interaction, reduce the time and cost of drug discovery. In this study, we propose a novel …

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 …

Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient
and successful rational drug design. Therefore, many binding affinity prediction methods …

Motivation Accurate and rapid prediction of protein–ligand binding affinity is a great
challenge currently encountered in drug discovery. Recent advances have manifested a …

Computational drug discovery provides an efficient tool for helping large-scale lead
molecule screening. One of the major tasks of lead discovery is identifying molecules with …

Accurate prediction of binding affinity between protein and ligand is a very important step in
the field of drug discovery. Although there are many methods based on different …

Motivation The capability to predict the potential drug binding affinity against a protein target
has always been a fundamental challenge in silico drug discovery. The traditional …

The binding affinity of small molecules to receptor proteins is essential to drug discovery and
drug repositioning. Chemical methods are often time-consuming and costly, and models for …

Evaluating the protein–ligand binding affinity is a substantial part of the computer-aided drug
discovery process. Most of the proposed computational methods predict protein–ligand …

Applying deep learning concepts from image detection and graph theory has greatly
advanced protein–ligand binding affinity prediction, a challenge with enormous ramifications …