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 field of machine learning for drug discovery is witnessing an explosion of novel
methods. These methods are often benchmarked on simple physicochemical properties …

Molecular docking tools are regularly used to computationally identify new molecules in
virtual screening for drug discovery. However, docking tools suffer from inaccurate scoring …

Molecular docking remains an important tool for structure-based screening to find new
ligands and chemical probes. As docking ambitions grow to include new scoring function …

Molecular docking is the most practical approach to leverage protein structure for ligand
discovery, but the technique retains important liabilities that make it challenging to deploy on …

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 …

Molecular docking is a widely used technique for leveraging protein structure for ligand
discovery, but it remains difficult to utilize due to limitations that have not been adequately …

In structure-based screens for new ligands, a molecular docking algorithm must rapidly
score many molecules in multiple configurations, accounting for both the ligand's …

Ligand enrichment among top-ranking hits is a key metric of virtual screening. To avoid bias,
decoys should resemble ligands physically, so that enrichment is not attributable to simple …

Structure-based virtual screening relies on scoring the predicted binding modes of
compounds docked into the target. Because the accuracy of this scoring relies on the …