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GNINA 1.3: the next increment in molecular docking with deep learning

open access: yesJournal of Cheminformatics
Computer-aided drug design has the potential to significantly reduce the astronomical costs of drug development, and molecular docking plays a prominent role in this process.
Andrew T. McNutt   +4 more
doaj   +2 more sources

Progress in molecular docking [PDF]

open access: yesQuantitative Biology, 2019
BackgroundIn 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 design to predict the binding affinity and analyze the interactive mode.ResultsThis study introduces the key principles, procedures and the widely‐used applications for ...
Le Zhang
exaly   +2 more sources

Integration of Molecular Docking Analysis and Molecular Dynamics Simulations for Studying Food Proteins and Bioactive Peptides

open access: yesJournal of Agricultural and Food Chemistry, 2022
In silico tools, such as molecular docking, are widely applied to study interactions and binding affinity of biological activity of proteins and peptides.
Abraham Vidal-Limon   +2 more
exaly   +2 more sources

Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in diseases management

open access: yesScientific Reports, 2023
Molecular docking is a computational technique that predicts the binding affinity of ligands to receptor proteins. Although it has potential uses in nutraceutical research, it has developed into a formidable tool for drug development.
P. C. Agu   +7 more
doaj   +2 more sources

Molecular Docking: Shifting Paradigms in Drug Discovery

open access: yesInternational Journal of Molecular Sciences, 2019
Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating ...
Luca Pinzi, Giulio Rastelli
exaly   +2 more sources

Assessing molecular docking tools: understanding drug discovery and design

open access: yesFuture Journal of Pharmaceutical Sciences
Background In this twenty-first century, artificial intelligence and computational-based studies, i.e., pharmaceutical biotechnology, are more important in every field, even in the field of drug discovery, design, and development, and they should be for ...
Harendar Kumar Nivatya   +8 more
doaj   +2 more sources

The art and science of molecular docking

open access: yesAnnual Review of Biochemistry
Molecular docking has become an essential part of a structural biologist’s and medicinal chemist’s toolkits. Given a chemical compound and the three-dimensional structure of a molecular target—for example, a protein—docking methods fit the compound into ...
Joseph M. Paggi   +2 more
semanticscholar   +3 more sources

Software for molecular docking: a review [PDF]

open access: yesBiophysical Reviews, 2017
Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery.
N. S. Pagadala, K. Syed, J. Tuszynski
semanticscholar   +3 more sources

Molecular Docking of Aromatase Inhibitors

open access: yesMolecules, 2011
Aromatase is an enzyme that plays a critical role in the development of estrogen receptor positive breast cancer. As aromatase catalyzes the aromatization of androstenedione to estrone, a naturally occurring estrogen, it is a promising drug target for ...
Virapong Prachayasittikul   +3 more
doaj   +3 more sources

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking [PDF]

open access: yesInternational Conference on Learning Representations, 2022
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 docking as a regression problem have decreased runtime compared to ...
Gabriele Corso   +4 more
semanticscholar   +1 more source

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