Dataset Information

Li2021 - HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors

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. Model Type: Predictive machine learning model. Model Relevance: Probability that the molecule is a HDAC3 inhibitor Model Encoded by: Sarima Chiorlu (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos1n4b

SUBMITTER: Zainab Ashimiyu-Abdusalam