Key topics in molecular docking for drug design

PHM Torres, ACR Sodero, P Jofily… - International journal of …, 2019 - mdpi.com
Molecular docking has been widely employed as a fast and inexpensive technique in the
past decades, both in academic and industrial settings. Although this discipline has now had …

Structure-based virtual screening for ligands of G protein–coupled receptors: what can molecular docking do for you?

F Ballante, AJ Kooistra, S Kampen, C de Graaf… - Pharmacological …, 2021 - ASPET
G protein–coupled receptors (GPCRs) constitute the largest family of membrane proteins in
the human genome and are important therapeutic targets. During the last decade, the …

GNINA 1.0: molecular docking with deep learning

AT McNutt, P Francoeur, R Aggarwal, T Masuda… - Journal of …, 2021 - Springer
Molecular docking computationally predicts the conformation of a small molecule when
binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline …

Comparative assessment of scoring functions: the CASF-2016 update

M Su, Q Yang, Y Du, G Feng, Z Liu, Y Li… - Journal of chemical …, 2018 - ACS Publications
In structure-based drug design, scoring functions are often employed to evaluate protein–
ligand interactions. A variety of scoring functions have been developed so far, and thus …

Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity

S Li, J Zhou, T Xu, L Huang, F Wang, H Xiong… - Proceedings of the 27th …, 2021 - dl.acm.org
Drug discovery often relies on the successful prediction of protein-ligand binding affinity.
Recent advances have shown great promise in applying graph neural networks (GNNs) for …

Computational evaluation of major components from plant essential oils as potent inhibitors of SARS-CoV-2 spike protein

SA Kulkarni, SK Nagarajan, V Ramesh… - Journal of Molecular …, 2020 - Elsevier
Abstract COVID-19, caused by SARS-CoV-2 has recently emerged as a global pandemic.
Intense efforts are ongoing to find a vaccine or a drug to control the disease across the …

DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks

M Karimi, D Wu, Z Wang, Y Shen - Bioinformatics, 2019 - academic.oup.com
Motivation Drug discovery demands rapid quantification of compound–protein interaction
(CPI). However, there is a lack of methods that can predict compound–protein affinity from …

Comprehensive evaluation of ten docking programs on a diverse set of protein–ligand complexes: the prediction accuracy of sampling power and scoring power

Z Wang, H Sun, X Yao, D Li, L Xu, Y Li… - Physical Chemistry …, 2016 - pubs.rsc.org
As one of the most popular computational approaches in modern structure-based drug
design, molecular docking can be used not only to identify the correct conformation of a …

Evaluation of AutoDock and AutoDock Vina on the CASF-2013 benchmark

T Gaillard - Journal of chemical information and modeling, 2018 - ACS Publications
Computer-aided protein–ligand binding predictions are a valuable help in drug discovery.
Protein–ligand docking programs generally consist of two main components: a scoring …

AI-based protein structure prediction in drug discovery: impacts and challenges

M Schauperl, RA Denny - Journal of Chemical Information and …, 2022 - ACS Publications
Proteins are the molecular machinery of the human body, and their malfunctioning is often
responsible for diseases, making them crucial targets for drug discovery. The three …