Deep learning has disrupted nearly every field of research, including those of direct
importance to drug discovery, such as medicinal chemistry and pharmacology. This …

With the recent explosion of chemical libraries beyond a billion molecules, more efficient
virtual screening approaches are needed. The Deep Docking (DD) platform enables up to …

Molecular representation learning (MRL) has gained tremendous attention due to its critical
role in learning from limited supervised data for applications like drug design. In most MRL …

The application of computational approaches in drug discovery has been consolidated in
the last decades. These families of techniques are usually grouped under the common …

AutoDock4 is a widely used program for docking small molecules to macromolecular targets.
It describes ligand–receptor interactions using a physics-inspired scoring function that has …

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced
sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use …

AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark
CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best …

Molecular docking, a structure-based virtual screening method, is a reliable tool to enrich
potential bioactive molecules from molecular databases. With the rapid expansion of …

Cancer management is major concern of health organizations and viral cancers account for
approximately 15.4% of all known human cancers. Due to large number of patients, efficient …

Protein-ligand docking is a computational method for identifying drug leads. The method is
capable of narrowing a vast library of compounds down to a tractable size for downstream …