Opportunities and challenges in application of artificial intelligence in pharmacology

M Kumar, TPN Nguyen, J Kaur, TG Singh, D Soni… - Pharmacological …, 2023 - Springer
Artificial intelligence (AI) is a machine science that can mimic human behaviour like
intelligent analysis of data. AI functions with specialized algorithms and integrates with deep …

Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation

N Kumbhar, S Nimal, S Barale, S Kamble, R Bavi… - Scientific Reports, 2022 - nature.com
In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a
prominent therapeutic target for the design and development of candidate drugs against …

Stack-HDAC3i: A high-precision identification of HDAC3 inhibitors by exploiting a stacked ensemble-learning framework

W Shoombuatong, I Meewan, L Mookdarsanit… - Methods, 2024 - Elsevier
Epigenetics involves reversible modifications in gene expression without altering the genetic
code itself. Among these modifications, histone deacetylases (HDACs) play a key role by …

HDAC3 inhibitors: a patent review of their broad-spectrum applications as therapeutic agents

TB Makgoba, E Kapp, S Egieyeh… - Expert Opinion on …, 2024 - Taylor & Francis
ABSTRACT Introduction Histone deacetylases (HDACs) are a class of zinc-dependent
enzymes. They maintain acetylation homeostasis, with numerous biological functions and …

Machine learning enables accurate and rapid prediction of active molecules against breast cancer cells

S He, D Zhao, Y Ling, H Cai, Y Cai, J Zhang… - Frontiers in …, 2021 - frontiersin.org
Breast cancer (BC) has surpassed lung cancer as the most frequently occurring cancer, and
it is the leading cause of cancer-related death in women. Therefore, there is an urgent need …

Epigenetic target fishing with accurate machine learning models

N Sanchez-Cruz, JL Medina-Franco - Journal of Medicinal …, 2021 - ACS Publications
Epigenetic targets are of significant importance in drug discovery research, as demonstrated
by the eight approved epigenetic drugs for treatment of cancer and the increasing …

A machine learning-integrated stepwise method to discover novel anti-obesity phytochemicals that antagonize the glucocorticoid receptor

SH Shin, G Hur, NR Kim, JHY Park, KW Lee… - Food & Function, 2023 - pubs.rsc.org
As a type of stress hormone, glucocorticoids (GCs) affect numerous physiological pathways
by binding to the glucocorticoid receptor (GR) and regulating the transcription of various …

Chemoinformatics and machine learning approaches for identifying antiviral compounds

L John, Y Soujanya, HJ Mahanta… - Molecular …, 2022 - Wiley Online Library
Current pandemics propelled research efforts in unprecedented fashion, primarily triggering
computational efforts towards new vaccine and drug development as well as drug …

Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors

J Wu, Y Chen, J Wu, D Zhao, J Huang, MJ Lin… - Journal of …, 2024 - Springer
Conventional machine learning (ML) and deep learning (DL) play a key role in the selectivity
prediction of kinase inhibitors. A number of models based on available datasets can be used …

HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors

OV Tinkov, VN Osipov, AV Kolotaev… - SAR and QSAR in …, 2024 - Taylor & Francis
ABSTRACT Histone deacetylase 6 (HDAC6) is a promising drug target for the treatment of
human diseases such as cancer, neurodegenerative diseases (in particular, Alzheimer's …