Chemo-structural diversity of anti-obesity compound database.

Anti-obesity database Chemical descriptors Fingerprint diversity Natural compounds Scaffold diversity and molecular properties

Journal

Journal of molecular graphics & modelling
ISSN: 1873-4243
Titre abrégé: J Mol Graph Model
Pays: United States
ID NLM: 9716237

Informations de publication

Date de publication:
05 2023
Historique:
received: 18 08 2022
revised: 28 12 2022
accepted: 12 01 2023
pubmed: 27 1 2023
medline: 25 2 2023
entrez: 26 1 2023
Statut: ppublish

Résumé

Nature plays a major role in the development of new drugs which helps in preventing and treating human diseases. Anti-obesity compound database (AOCD) contains comprehensive information on all published small molecules from natural sources with anti-obesity potential targeting pancreatic lipase (PL), appetite suppressant (AS) and adipogenesis (AD). Presently the database contains 349 compounds isolated from 307 plants, 26 marine and 16 microbial sources. Users can query the AOCD database (https://aocd.swmd.co.in/) in several ways. The database was divided into three datasets (PL, AS and AD) to perform chemoinformatic analysis using Platform for Unified Molecular Analysis (PUMA), which were analyzed based on molecular descriptors, scaffold diversity and structural fingerprint diversity. Chemoinformatics study inferred the PL dataset has the highest diversity of compounds based on the Euclidean distance on molecular properties, scaffold diversity and pairwise similarity on fingerprint diversity. This study would hasten the process of anti-obesity drug discovery.

Identifiants

pubmed: 36702059
pii: S1093-3263(23)00012-8
doi: 10.1016/j.jmgm.2023.108414
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108414

Informations de copyright

Copyright © 2023 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Prabhakar Lavanya (P)

Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India.

Dicky John Davis G (DJ)

Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India. Electronic address: dicky@sriramachandra.edu.in.

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