Abstract Structure-based virtual screening (SBVS) via docking has been used to discover
active molecules for a range of therapeutic targets. Chemical and protein data sets that …

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, there has been a …

In the present study, chitosan/polyvinyl alcohol (PVA)-based honey hydrogel films were
developed for potential wound healing application. The hydrogel films were developed by a …

Deep learning (DL)-based de novo molecular design has recently gained considerable
traction. Many DL-based generative models have been successfully developed to design …

Applying machine learning algorithms to protein–ligand scoring functions has aroused
widespread attention in recent years due to the high predictive accuracy and affordable …

Taste peptides, as an important component of protein-rich foodstuffs, potentiate the nutrition
and taste of food. Thereinto, umami-and bitter-taste peptides have been ex tensively …

Binding affinity prediction largely determines the discovery efficiency of lead compounds in
drug discovery. Recently, machine learning (ML)-based approaches have attracted much …

Abstract Machine learning-based scoring functions (MLSFs) have shown potential for
improving virtual screening capabilities over classical scoring functions (SFs). Due to the …

Developing new drugs is too expensive and time-consuming. Accurately predicting the
interaction between drugs and targets will likely change how the drug is discovered …

Initially part of the field of artificial intelligence, machine learning (ML) has become a
booming research area since branching out into its own field in the 1990s. After three …