Molecular docking: shifting paradigms in drug discovery

L Pinzi, G Rastelli - International journal of molecular sciences, 2019 - mdpi.com
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 …

An up-to-date overview of computational polypharmacology in modern drug discovery

R Chaudhari, LW Fong, Z Tan, B Huang… - Expert opinion on drug …, 2020 - Taylor & Francis
Introduction In recent years, computational polypharmacology has gained significant
attention to study the promiscuous nature of drugs. Despite tremendous challenges …

Predicting adverse drug reactions through interpretable deep learning framework

S Dey, H Luo, A Fokoue, J Hu, P Zhang - BMC bioinformatics, 2018 - Springer
Abstract Background Adverse drug reactions (ADRs) are unintended and harmful reactions
caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the …

Prediction of adverse drug reactions based on knowledge graph embedding

F Zhang, B Sun, X Diao, W Zhao, T Shu - BMC Medical Informatics and …, 2021 - Springer
Abstract Background Adverse drug reactions (ADRs) are an important concern in the
medication process and can pose a substantial economic burden for patients and hospitals …

Opportunities for drug repositioning from phenome-wide association studies

M Rastegar-Mojarad, Z Ye, JM Kolesar… - Nature …, 2015 - nature.com
To the Editor: Results from large-scale phenome-wide association studies (PheWAS) allow
association of genetic variants with a wide spectrum of human disorders and have provided …

[HTML][HTML] A knowledge graph embedding based approach to predict the adverse drug reactions using a deep neural network

P Joshi, V Masilamani, A Mukherjee - Journal of Biomedical Informatics, 2022 - Elsevier
Abstract Recently Artificial Intelligence (AI) has not only been used to diagnose the disease
but also to cure the disease. Researchers started using AI for drug discovery. Predicting the …

Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects

PA Nguyen, DA Born, AM Deaton, P Nioi… - Nature …, 2019 - nature.com
Only a small fraction of early drug programs progress to the market, due to safety and
efficacy failures, despite extensive efforts to predict safety. Characterizing the effect of …

Impact of binding site comparisons on medicinal chemistry and rational molecular design

C Ehrt, T Brinkjost, O Koch - Journal of medicinal chemistry, 2016 - ACS Publications
Modern rational drug design not only deals with the search for ligands binding to interesting
and promising validated targets but also aims to identify the function and ligands of yet …

Single-domain antibodies and the promise of modular targeting in cancer imaging and treatment

ME Iezzi, L Policastro, S Werbajh, O Podhajcer… - Frontiers in …, 2018 - frontiersin.org
Monoclonal antibodies and their fragments have significantly changed the outcome of
cancer in the clinic, effectively inhibiting tumor cell proliferation, triggering antibody …

An extensive survey on the use of supervised machine learning techniques in the past two decades for prediction of drug side effects

P Das, DH Mazumder - Artificial Intelligence Review, 2023 - Springer
Approved drugs for sale must be effective and safe, implying that the drug's advantages
outweigh its known harmful side effects. Side effects (SE) of drugs are one of the common …