The interpretability is an important issue for end-to-end learning models. Motivated by
computer vision algorithms, an interpretable noncovalent interaction (NCI) correction …

Small‐molecule drugs are of significant importance to human health. The use of efficient
model‐based de novo drug design method is an option worth considering for expediting the …

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the
pharmaceutical industry, including drug screening, design, and repurposing. However …

Protein-ligand interactions are essential for cellular activities and drug discovery processes.
Appropriately and effectively representing protein features is of vital importance for …

Gathering information from multi-perspective graphs is an essential issue for many
applications especially for protein–ligand-binding affinity prediction. Most of traditional …

The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery.
Computerized virtual screening techniques have been used for DTA prediction, greatly …

The prediction of the drug-target affinity (DTA) plays an important role in evaluating
molecular druggability. Although deep learning-based models for DTA prediction have been …

The ionotropic γ-aminobutyric acid (GABA) receptor (iGABAR) is an important target of
agricultural insecticides. Our previous studies indicated that competitive antagonists (CAs) of …

Accurately identifying drug-target affinity (DTA) plays a significant role in promoting drug
discovery and has attracted increasing attention in recent years. Exploring appropriate …

Drug discovery plays a critical role in advancing human health by developing new
medications and treatments to combat diseases. How to accelerate the pace and reduce the …