Navigating into the Chemical Space of Monoamine Oxidase Inhibitors by Artificial Intelligence and Cheminformatics Approach
Sunil Kumar, Aathira Sujathan Nair, Vaishnav Bhashkar, Sachithra Thazhathuveedu Sudevan, Vishal Payyalot Koyiparambath, Ahmed Khames, Mohamed A. Abdelgawad, Bijo Mathew
Abstract
-chromen-2-one scaffold. This scaffold showed a polypharmacological effect. R-group disintegration and automatic structure-activity relationship (SAR) study resulted in identification of substructures responsible for the inhibitory bioactivity of the MAO-A and MAO-B enzymes. Moreover, with activity cliff analysis, significant biological activity was detected by simple molecular conversion in the chemical compound structure. In addition, we used the machine learning tool to generate a hypothesis wherein pyrazole, benzene ring, and amide containing structural functionalities can exhibit potential biological activities. This hypothesis revealed that CNS target drugs, C4155, C13390, C21265, C43862, C31524, C24810, C37100, C42075, and C43644, could be repurposed as valuable candidates for the MAO-B enzyme. For researchers, this study will bring new perceptions in the discovery and development of MAOIs and direct lead and hit optimization for the progress of small molecules beneficial for MAO-targeting associated diseases.