EQUIBIND: A geometric deep learning-based protein-ligand binding prediction method
Y Li, L Li, S Wang, X Tang - Drug Discoveries & Therapeutics, 2023 - jstage.jst.go.jp
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 …
docking programs, such as AutoDock Vina and Glide, are time-consuming due to the …
Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning
Rational structure-based drug design relies on accurate predictions of protein–ligand
binding affinity from structural molecular information. Although deep learning-based …
binding affinity from structural molecular information. Although deep learning-based …
Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction
M Brylinski - 2013 - ACS Publications
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 …
organic compounds into the target sites in protein receptors with promising leads selected …
Equibind: Geometric deep learning for drug binding structure prediction
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 …
drug discovery. An extremely fast computational binding method would enable key …
Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening
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 …
structure-based virtual screening (SBVS) used to predict the binding conformations and …
XG-DTA: Drug-Target Affinity Prediction Based on Drug Molecular Graph and Protein Sequence combined with XLNet
H Zhou, X Shi, Y Wang, Z Wen… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
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 …
drug-target interactions can accelerate the development of new drugs and improve drug …
DEELIG: A deep learning approach to predict protein-ligand binding affinity
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 …
in understanding the degree of protein-ligand interactions and is a useful measure in drug …
A new paradigm for applying deep learning to protein–ligand interaction prediction
Protein–ligand interaction prediction presents a significant challenge in drug design.
Numerous machine learning and deep learning (DL) models have been developed to …
Numerous machine learning and deep learning (DL) models have been developed to …
Predicting protein–ligand docking structure with graph neural network
Modern day drug discovery is extremely expensive and time consuming. Although
computational approaches help accelerate and decrease the cost of drug discovery, existing …
computational approaches help accelerate and decrease the cost of drug discovery, existing …
DockThor-VS: A Free Platform for Receptor-Ligand Virtual Screening
IA Guedes, MMP da Silva, M Galheigo… - Journal of Molecular …, 2024 - Elsevier
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 …
server conceptualized to facilitate and assist drug discovery projects to perform docking …