Dataset Information
Li2021 - HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors
Ontology highlight
ABSTRACT: The model predicts the inhibitory potential of small molecules against Histone deacetylase 3 (HDAC3), a relevant human target for cancer, inflammation, neurodegenerative diseases and diabetes. The authors have used a dataset of 1098 compounds from ChEMBL and validated the model using the benchmark MUBD-HDAC3. Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos1n4b
ORGANISM(S): Homo sapiens
SUBMITTER: Amina Mardiyyah Rufai
PROVIDER: MODEL2406210001 | biostudies-other |
SECONDARY ACCESSION(S): 33067876
REPOSITORIES: biostudies-other
Publications
HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors.
Molecular informatics 20201123 3
Histone deacetylase 3 (HDAC3) is a potential drug target for treatment of human diseases such as cancer, chronic inflammation, neurodegenerative diseases and diabetes. Machine learning (ML) as an essential cheminformatics approach has been widely used for QSAR modeling. However, none of them has been applied to HDAC3. To this end, we carefully compiled a set of 1098 compounds from the ChEMBL database that have been assayed against HDAC3 and calculated three different sets of molecular features f ...[more]
