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 …

Despite advances in molecular biology, genetics, computation, and medicinal chemistry,
infectious disease remains an ominous threat to public health. Addressing the challenges …

Predicting the binding structure of a small molecule ligand to a protein--a task known as
molecular docking--is critical to drug design. Recent deep learning methods that treat …

Proteins are key to all cellular processes and their structure is important in understanding
their function and evolution. Sequence-based predictions of protein structures have …

The discovery of novel structural classes of antibiotics is urgently needed to address the
ongoing antibiotic resistance crisis,,,,,,,–. Deep learning approaches have aided in exploring …

Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …

Three-dimensional protein structure is directly correlated with its function and its
determination is critical to understanding biological processes and addressing human …

The accumulation of senescent cells is associated with aging, inflammation and cellular
dysfunction. Senolytic drugs can alleviate age-related comorbidities by selectively killing …

A crucial component in structure-based drug discovery is the availability of high-quality three-
dimensional structures of the protein target. Whenever experimental structures were not …

Computational prediction of protein structure has been pursued intensely for decades,
motivated largely by the goal of using structural models for drug discovery. Recently …