Biomolecular recognition between ligand and protein plays an essential role in drug
discovery and development. However, it is extremely time and resource consuming to …

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

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 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 …

Modeling the interaction between proteins and ligands and accurately predicting their
binding structures is a critical yet challenging task in drug discovery. Recent advancements …

Computational drug design relies on the calculation of binding strength between two
biological counterparts especially a chemical compound, ie, a ligand, and a protein …

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 …

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

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: Prediction of the interaction affinity between proteins and compounds is a major
challenge in the drug discovery process. WideDTA is a deep-learning based prediction …