AI in drug discovery and its clinical relevance
The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …
However, the journey from conceptualizing a drug to its eventual implementation in clinical …
Deep learning methods for molecular representation and property prediction
Highlights•The deep learning method could effectively represent the molecular structure and
predict molecular property through diversified models.•One, two, and three-dimensional …
predict molecular property through diversified models.•One, two, and three-dimensional …
Omicron BA. 2 (B. 1.1. 529.2): high potential for becoming the next dominant variant
The Omicron variant has three subvariants: BA. 1 (B. 1.1. 529.1), BA. 2 (B. 1.1. 529.2), and
BA. 3 (B. 1.1. 529.3). BA. 2 is found to be able to alarmingly reinfect patients originally …
BA. 3 (B. 1.1. 529.3). BA. 2 is found to be able to alarmingly reinfect patients originally …
Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions
Accurate quantification of protein–ligand interactions remains a key challenge to structure-
based drug design. However, traditional machine learning (ML)-based methods based on …
based drug design. However, traditional machine learning (ML)-based methods based on …
Mutations strengthened SARS-CoV-2 infectivity
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is a major
concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening …
concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening …
COVID-19 and SARS-CoV-2. Modeling the present, looking at the future
E Estrada - Physics reports, 2020 - Elsevier
Abstract Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2
(SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a …
(SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a …
An overview of scoring functions used for protein–ligand interactions in molecular docking
J Li, A Fu, L Zhang - Interdisciplinary Sciences: Computational Life …, 2019 - Springer
Currently, molecular docking is becoming a key tool in drug discovery and molecular
modeling applications. The reliability of molecular docking depends on the accuracy of the …
modeling applications. The reliability of molecular docking depends on the accuracy of the …
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 …
A practical guide to machine-learning scoring for structure-based virtual screening
Abstract Structure-based virtual screening (SBVS) via docking has been used to discover
active molecules for a range of therapeutic targets. Chemical and protein data sets that …
active molecules for a range of therapeutic targets. Chemical and protein data sets that …
Three-dimensional convolutional neural networks and a cross-docked data set for structure-based drug design
PG Francoeur, T Masuda, J Sunseri, A Jia… - Journal of chemical …, 2020 - ACS Publications
One of the main challenges in drug discovery is predicting protein–ligand binding affinity.
Recently, machine learning approaches have made substantial progress on this task …
Recently, machine learning approaches have made substantial progress on this task …