Virtual screening, which identifies potential drugs from vast compound databases to bind
with a particular protein pocket, is a critical step in AI-assisted drug discovery. Traditional …

Structure-based virtual screening is an important tool in early stage drug discovery that
scores the interactions between a target protein and candidate ligands. As virtual libraries …

Virtual screening—predicting which compounds within a specified compound library bind to
a target molecule, typically a protein—is a fundamental task in the field of drug discovery …

Introduction The discovery of a new drug is a costly and lengthy endeavour. The
computational prediction of which small molecules can bind to a protein target can …

Molecular docking predicts whether and how small molecules bind to a macromolecular
target using a suitable 3D structure. Scoring functions for structure‐based virtual screening …

In structure-based virtual screening (SBVS), a binding site on a protein structure is used to
search for ligands with favorable nonbonded interactions. Because it is computationally …

The core of large-scale drug virtual screening is to select the binders accurately and
efficiently with high affinity from large libraries of small molecules in which non-binders are …

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

Modern day drug discovery is extremely expensive and time consuming. Although
computational approaches help accelerate and decrease the cost of drug discovery, existing …

Current deep learning methods for structure-based virtual screening take the structures of
both the protein and the ligand as input but make little or no use of the protein structure …