Machine-learning methods for ligand–protein molecular docking

K Crampon, A Giorkallos, M Deldossi, S Baud… - Drug discovery today, 2022 - Elsevier
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 …

[HTML][HTML] Deep learning in virtual screening: recent applications and developments

TB Kimber, Y Chen, A Volkamer - International journal of molecular …, 2021 - mdpi.com
Drug discovery is a cost and time-intensive process that is often assisted by computational
methods, such as virtual screening, to speed up and guide the design of new compounds …

Rapid identification of potential inhibitors of SARS‐CoV‐2 main protease by deep docking of 1.3 billion compounds

AT Ton, F Gentile, M Hsing, F Ban… - Molecular …, 2020 - Wiley Online Library
Abstract The recently emerged 2019 Novel Coronavirus (SARS‐CoV‐2) and associated
COVID‐19 disease cause serious or even fatal respiratory tract infection and yet no …

On the frustration to predict binding affinities from protein–ligand structures with deep neural networks

M Volkov, JA Turk, N Drizard, N Martin… - Journal of medicinal …, 2022 - ACS Publications
Accurate prediction of binding affinities from protein–ligand atomic coordinates remains a
major challenge in early stages of drug discovery. Using modular message passing graph …

Improved protein–ligand binding affinity prediction with structure-based deep fusion inference

D Jones, H Kim, X Zhang, A Zemla… - Journal of chemical …, 2021 - ACS Publications
Predicting accurate protein–ligand binding affinities is an important task in drug discovery
but remains a challenge even with computationally expensive biophysics-based energy …

Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term

L Zheng, J Meng, K Jiang, H Lan, Z Wang… - Briefings in …, 2022 - academic.oup.com
Scoring functions are important components in molecular docking for structure-based drug
discovery. Traditional scoring functions, generally empirical-or force field-based, are robust …

[HTML][HTML] Deep learning based drug screening for novel coronavirus 2019-nCov

H Zhang, KM Saravanan, Y Yang, MT Hossain… - Interdisciplinary …, 2020 - Springer
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of
China, and now is spreading across China and other parts of the world. Although there are …

Artificial intelligence in virtual screening: Models versus experiments

NA Murugan, GR Priya, GN Sastry, S Markidis - Drug Discovery Today, 2022 - Elsevier
A typical drug discovery project involves identifying active compounds with significant
binding potential for selected disease-specific targets. Experimental high-throughput …

Deep learning model for efficient protein–ligand docking with implicit side-chain flexibility

MR Masters, AH Mahmoud, Y Wei… - Journal of Chemical …, 2023 - ACS Publications
Protein–ligand docking is an essential tool in structure-based drug design with applications
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …

[HTML][HTML] AK-score: accurate protein-ligand binding affinity prediction using an ensemble of 3D-convolutional neural networks

Y Kwon, WH Shin, J Ko, J Lee - International journal of molecular …, 2020 - mdpi.com
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient
and successful rational drug design. Therefore, many binding affinity prediction methods …