Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains
use AI, including molecular simulation for drug discovery. In this review, we provide an …

Molecular docking, given a ligand molecule and a ligand binding site (called``pocket'') on a
protein, predicting the binding mode of the protein-ligand complex, is a widely used …

Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …

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

Predicting the binding structure of a small molecule ligand to a protein--a task known as
molecular docking--is critical to drug design. Recent deep learning methods that treat …

Computational drug design relies on the calculation of binding strength between two
biological counterparts especially a chemical compound, ie, a ligand, and a protein …

The last few years have seen the development of numerous deep learning-based protein–
ligand docking methods. They offer huge promise in terms of speed and accuracy. However …

Background In recent years, since the molecular docking technique can greatly improve the
efficiency and reduce the research cost, it has become a key tool in computer-assisted drug …

Objective The objective of this paper is to highlight the state-of-the-art machine learning (ML)
techniques in computational docking. The use of smart computational methods in the life …

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