Protein–ligand docking is an essential tool in structure-based drug design with applications
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …

Protein–ligand docking has been playing an important role in modern drug discovery. To
model drug–target binding in real systems, a number of flexible-ligand docking algorithms …

Docking calculations can accelerate drug discovery by predicting the bound poses of
ligands for a targeted protein. However, it is not clear which docking methods work best …

The expertise accumulated in deep neural network-based structure prediction has been
widely transferred to the field of protein–ligand binding pose prediction, thus leading to the …

A handful of molecular docking tools have been extended to enable a covalent docking.
However, all of them face the challenge brought by the covalent bond between proteins and …

Protein–peptide interactions play a crucial role in many cellular and biological functions,
which justify the increasing interest in the development of peptide-based drugs. However …

In the validation of protein− ligand docking protocols, performance is mostly measured
against native protein conformers, ie each ligand is docked into the protein conformation …

An important issue in developing protein–ligand docking methods is how to incorporate
receptor flexibility. Consideration of receptor flexibility using an ensemble of precompiled …

Computational methods for docking ligands have been shown to be remarkably dependent
on precise protein conformation, where acceptable results in pose prediction have been …

Modeling the interaction between proteins and ligands and accurately predicting their
binding structures is a critical yet challenging task in drug discovery. Recent advancements …