Developing a Multi-target Model to Predict the Activity of Monoamine Oxidase A and B Drugs

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Riccardo Concu (Author) FCUP; Gonzalez Durruthy, M (Author) Other; Natalia N D S Cordeiro (Author) FCUP

Journal

Title: Current Topics in Medicinal Chemistry

Vol. 20

Pages: 1593-1600

ISSN: 1568-0266

Publisher: Bentham Science

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00S-NCR

DOI: 10.2174/1568026620666200603121224

Abstract (EN): Introduction: Monoamine oxidase inhibitors (MAOIs) are compounds largely used in the treatment of Parkinson's disease (PD), Alzheimer's disease and other neuropsychiatric disorders since they are closely related to the MAO enzymes activity. The two isoforms of the MAO enzymes, MAO-A and MAO-B, are responsible for the degradation of monoamine neurotransmitters and due to this, relevant efforts have been devoted to finding new compounds with more selectivity and less side effects. One of the most used approaches is based on the use of computational approaches since they are time and money-saving and may allow us to find a more relevant structure-activity relationship. Objective: In this manuscript, we will review the most relevant computational approaches aimed at the prediction and development of new MAO inhibitors. Subsequently, we will also introduce a new multitask model aimed at predicting MAO-A and MAO-B inhibitors. Methods: The QSAR multi-task model herein developed was based on the use of the linear discriminant analysis. This model was developed gathering 5,759 compounds from the public dataset Chembl. The molecular descriptors used was calculated using the Dragon software. Classical statistical tests were performed to check the validity and robustness of the model. Results: The herein proposed model is able to correctly classify all the 5,759 compounds. All the statistical performed tests indicated that this model is robust and reproducible. Conclusion: MAOIs are compounds of large interest since they are largely used in the treatment of very serious illness. These inhibitors may lose efficacy and produce severe side effects. Due to this, the development of selective MAO-A or MAO-B inhibitors is crucial for the treatment of these diseases and their effects. The herein proposed multi-target QSAR model may be a relevant tool in the development of new and more selective MAO inhibitors.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8