Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …

Molecular docking is a structure-based computational method that generates the binding
pose and affinity between ligands and targets. There are many powerful docking programs …

Sequence-based prediction of drug–target interactions has the potential to accelerate drug
discovery by complementing experimental screens. Such computational prediction needs to …

The past few years have witnessed enormous progress toward applying machine learning
approaches to the development of protein–ligand scoring functions. However, the robust …

Traditional drug design requires a great amount of research time and developmental
expense. Booming computational approaches, including computational biology, computer …

The drug discovery process is a rocky path that is full of challenges, with the result that very
few candidates progress from hit compound to a commercially available product, often due …

AlphaFold2 is a promising new tool for researchers to predict protein structures and
generate high‐quality models, with low backbone and global root‐mean‐square deviation …

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

Computationally identifying new targets for existing drugs has drawn much attention in drug
repurposing due to its advantages over de novo drugs, including low risk, low costs, and …

Ethnopharmacology, through the description of the beneficial effects of plants, has provided
an early framework for the therapeutic use of natural compounds. Natural products, either in …