Structure-based virtual screening plays a critical role in drug discovery. However, numerous
docking programs, such as AutoDock Vina and Glide, are time-consuming due to the …

Rational structure-based drug design relies on accurate predictions of protein–ligand
binding affinity from structural molecular information. Although deep learning-based …

A common strategy for virtual screening considers a systematic docking of a large library of
organic compounds into the target sites in protein receptors with promising leads selected …

Predicting how a drug-like molecule binds to a specific protein target is a core problem in
drug discovery. An extremely fast computational binding method would enable key …

Conspectus Molecular docking, also termed ligand docking (LD), is a pivotal element of
structure-based virtual screening (SBVS) used to predict the binding conformations and …

Drug-target affinity (DTA) prediction is critical in drug development. Accurate prediction of
drug-target interactions can accelerate the development of new drugs and improve drug …

Protein-ligand binding prediction has extensive biological significance. Binding affinity helps
in understanding the degree of protein-ligand interactions and is a useful measure in drug …

Protein–ligand interaction prediction presents a significant challenge in drug design.
Numerous machine learning and deep learning (DL) models have been developed to …

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

The DockThor-VS platform (https://dockthor. lncc. br/v2/) is a free protein–ligand docking
server conceptualized to facilitate and assist drug discovery projects to perform docking …