… machine learning (ML) techniques in computational docking. The use of smart computational
… Central to this methodology is the notion of computational docking which is the process of …

… Structure-based inhibitor design approaches often use molecular docking, a computational
procedure that efficiently predicts non-covalent interactions between macromolecules (…

… of machine learning techniques that have recently appeared in the computational chemistry
… In these studies, a set of molecules is computationally docked into a protein active site. The …

… of computational receptor-based docking, ligand-based CoMFA/CoMSIA and Machine learning
… All computational docking, CoMFA/CoMSIA, and ML results from our current study were …

… Molecular docking is a computational technique … docking has two stages: docking molecules
into the target's binding site (pose identification), and predicting how strongly the docked …

… the advances in docking, molecular simulations and machine learning to tackle problems …
computational methods that are routinely used to elucidate different aspects of PPIs: 1) docking…

… docking power using a supervised machine learning approach and a manually curated
database of ligands and cross docking … in a similar docking performance with regard to docking …

… its explicit representation in every docking run implies a high computational cost. Therefore,
a … is the approach known as ensemble docking. Ensemble docking consists of using a set of …

… A comprehensive docking procedure is described in which … the docked conformations using
a supervised machine learning … Computational docking methods, which provide structural …

… Therefore, the incorporation of atomic interaction features into the computational
framework presented in this paper may provide a better model of cooperativity in the future. …