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ISSN 2410-955X - An International Biannual Journal
BIOMEDICAL LETTERS
QSAR modeling of novel substituted 4-Phenylisoquinolinones as potent BET bromodomain (BRD4-BD1) inhibitors
Babatunde Samuel Obadawo 1, Oluwatoba Emmanuel Oyeneyin 2*, Mayowa Monday Anifowose 2, Kehinde Henry Fagbohungbe 3, Justinah Solayide Amoko 4

Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria
2 Theoretical and Computational Chemistry Unit, Department of Chemical Sciences, Adekunle Ajasin University, Akungba-Akoko, Ondo, State, Nigeria
3 Department of Chemistry, University of Ibadan, Oyo State, Nigeria
4 Department of Chemistry, Adeyemi College of Education, Ondo, Ondo State, Nigeria

Abstract
Drugs that can combat cancer are very important in the quest to eradicate the scourge, amongst which are the BRD1-BD1 inhibitors. QSAR study was carried out on forty compounds of substituted 4-phenylisoquinolinones in order to predict the ability of some compounds as (BRD4-BD1) inhibitors through mathematical models. Genetic Function Approximation (GFA) method was employed to generate four different models. The first model generated was the best owing to its significance, statistically. The best model has a Coefficient of determination (R2) of 0.93, Cross validation coefficient (Q2ev) of 0.70, Coefficient of determination for Y-randomization (cR2p) of 0.85. Furthermore, the built model was validated externally by R2pred = 0.95 which endorsed its predictive strength. This was further validated by applicability domain to check for outliers and influential compounds and two compounds were detected to be influential as their leverage values were higher than the warning limit (h = 0.54). Due to the reliability, stability and robustness of the built model, some compounds were designed and predicted to have improved activity as potent BET Bromodomain (BRD4-BD1) inhibitors. Thus, these compounds could be useful as anticancer and anti-inflammatory agents.
A R T I CL E  I N F O

Received
October 01, 2019
Revised
November 11, 2019
Accepted
November 15, 2019

*Corresponding Author
Oluwatoba Emmanuel Oyeneyin
E-mail
emmanueltoba90@gmail.com
oluwatoba.oyeneyin@aaua.edu.ng

Keywords
QSAR
BET Bromodomain inhibitors
Y-Randomization
Williams plot
4-Phenylisoquinolinone derivatives
Prevalence
Research article


2019 | Volume 5 | Issue 2