Drug design is a costly and time-consuming process, often taking more than 12 years and
costing up to billions of dollars. The COVID-19 pandemic has signified the urgent need for …

The integration of artificial intelligence (AI) into drug discovery has markedly advanced the
search for effective therapeutics. In our study, we employed a comprehensive computational …

High-quality predicted structures enable structure-based approaches to an expanding
number of drug discovery programs. We propose that by utilizing free energy perturbation …

Cryo-electron microscopy (cryo-EM) is currently the most powerful technique for determining
the structures of large protein complexes and assemblies. Picking single-protein particles …

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting
binding modes and estimating binding affinities. Ideally, a scoring function should be …

Fragment‐based drug design is an emerging technology in pharmaceutical research and
development. One of the key aspects of this technology is the identification and quantitative …

BACKGROUND: Protein-ligand binding affinity is of significant importance in structure-based
drug design. Recently, the development of machine learning techniques has provided an …

Accurately predicting compound-protein binding affinity is a crucial task in drug discovery.
Computational models offer the advantages of short time, low cost and safety compared to …

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step
in the cryo-EM-based structure determination. However, existing methods trained on a …

Recent advances in machine learning have proved effective in the application of drug
discovery by predicting the drugs that are likely to interact with a protein target of a certain …