EventsMOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Published
This submission belongs to the session 05. NICE.XSM-08: North-Ibero-America Congress on Exp. & Simul. Methods, Valencia, Spain-Miami, USA, 2022 of the event MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Published date
25 Aug, 2022
Academic Editor
author-avatarHumbert G. Díaz
Citation
Juan Carlos Polo, Raisa Mangas, Luis Torres, A QSAR model for the prediction of the pharmacological activity of the compounds present in the species clusia minor l., in Proceedings of MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed., 1 January–15 January 2023, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-08-12879
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A QSAR model for the prediction of the pharmacological activity of the compounds present in the species clusia minor l.

Raisa Mangas 2
1. Centro de Ingeniería Genética y Biotecnología (CIGB). La Habana, Cuba
2. Instituto de Farmacia y Alimentos, Universidad de La Habana, Cuba
Abstract

The species Clusia minor L., family Clusiaceae, belongs to a group of higher plants of high research interest due to their uses in traditional medicine. In the literature, it has been reported that the metabolites present in the species have various properties such as anti-inflammatory, antirheumatic, antiviral, antitumor and antioxidant, among others. However, few studies on its chemical and pharmacological composition can justify its potential use. For this reason, the present work aims to classify theoretically the possible anti-inflammatory, antitumor and/or antiviral activity of the compounds present in the extract of its leaves. To achieve this objective, a training series made up of 597 compounds classified according to the aforementioned pharmacological activities and a test series with the 53 compounds identified in the plant were built, which formed the basis for obtaining, by means of Linear Discriminant Analysis, of a Quantitative Structure-Activity Relationship model that achieves a 52.9 % adequate classification of the compounds included in the training series. The model obtained was considered viable taking into account the limitations of the classification according to belonging to a single group of pharmacological activity. Finally, the pharmacological classification of the compounds present in the extract of the leaves of the species Clusia minor L. was carried out, which presented, for the most part, anti-inflammatory (64.2 %) and antiviral (28.3 %) activity.

Keywords
QSAR models
phytopharmaceuticals
Manuscript
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