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 …
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 …
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
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 …
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
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 …
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
Predicting accurate protein–ligand binding affinities is an important task in drug discovery
but remains a challenge even with computationally expensive biophysics-based energy …
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
Scoring functions are important components in molecular docking for structure-based drug
discovery. Traditional scoring functions, generally empirical-or force field-based, are robust …
discovery. Traditional scoring functions, generally empirical-or force field-based, are robust …
[HTML][HTML] Deep learning based drug screening for novel coronavirus 2019-nCov
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 …
China, and now is spreading across China and other parts of the world. Although there are …
Artificial intelligence in virtual screening: Models versus experiments
A typical drug discovery project involves identifying active compounds with significant
binding potential for selected disease-specific targets. Experimental high-throughput …
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 …
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
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 …
and successful rational drug design. Therefore, many binding affinity prediction methods …