A Fuzzy System Classification Approach for QSAR Modeling of α-Amylase and α-Glucosidase Inhibitors

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A Fuzzy System Classification Approach for QSAR Modeling of α-Amylase and α-Glucosidase Inhibitors

Publicated to:Current Computer-Aided Drug Design. 18 (7): 469-479 - 2022-12-01 18(7), DOI: 10.2174/1573409918666220929124820

Authors: Dieguez-Santana, Karel; Puris, Amilkar; Rivera-Borroto, Oscar M; Casanola-Martin, Gerardo M; Rasulev, Bakhtiyor; Gonzalez-Diaz, Humberto

Affiliations

Basque Center for Biophysics CSIC-UPVEH, University of Basque Country UPV/EHU, 48940 Leioa, Spain. - Author

Basque Fdn Sci, Ikerbasque, Bilbao 48011, Biscay, Spain - Author

Departamento de Química Física Aplicada, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain. - Author

Department of Coatings and Polymer Materials, North Dakota State University, Fargo, North Dakota, 58102, USA. - Author

Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND, 58102, USA. - Author

Department of Mathematics, Houston Community College-West Loop Campus, Houston TX, 77081, USA. - Author

Department of Mathematics, Lone Star College-CyFair Campus, Houston, TX, 77433, USA. - Author

Department of Organic and Inorganic Chemistry, University of the Basque Country UPV/EHU, 48940, Leioa, Spain. - Author

Facultad de Ciencias de La Ingeniería, Universidad Técnica Estatal de Quevedo, Ecuador. - Author

Houston Community Coll, Dept Math, West Loop Campus, Houston, TX 77081 USA - Author

IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Biscay, Spain. - Author

Lone Star Coll, Dept Math, CyFair Campus, Houston, TX 77433 USA - Author

North Dakota State Univ, Dept Coatings & Polymer Mat, Fargo, ND 58102 USA - Author

Univ Autonoma Madrid, Fac Ciencias, Dept Quim Fis Aplicada, Madrid 28049, Spain - Author

Univ Basque Country UPV EHU, Basque Ctr Biophys CSIC UPVEH, Leioa 48940, Spain - Author

Univ Basque Country UPV EHU, Dept Organ & Inorgan Chem, Leioa 48940, Spain - Author

Univ Reg Amazon IKIAM, Tena 150150, Napo, Ecuador - Author

Univ Tecn Estatal Quevedo, Fac Ciencias Ingn, Quevedo, Ecuador - Author

Universidad Regional Amazónica IKIAM, Tena, Napo 150150, Ecuador. - Author

Abstract

Introduction This report proposes the application of a new Machine Learning algorithm called Fuzzy Unordered Rules Induction Algorithm (FURIA)-C in the classification of drug-like compounds with antidiabetic inhibitory ability toward the main two pharmacological targets: α-amylase and α-glucosidase. Methods The two obtained QSAR models were tested for classification capability, achieving satisfactory accuracy scores of 94.5% and 96.5%, respectively. Another important outcome was to achieve various α-amylase and α-glucosidase fuzzy rules with high Certainty Factor values. Fuzzy-Rules derived from the training series and active classification rules were interpreted. An important external validation step, comparing our method with those previously reported, was also included. Results The Holm's test comparison showed significant differences (p-value<0.05) between FURIA-C, Linear Discriminating Analysis (LDA), and Bayesian Networks, the former beating the two latter ones according to the relative ranking score of the Holm's test. Conclusion From these results, the FURIA-C algorithm could be used as a cutting-edge technique to predict (classify or screen) the α-amylase and α-glucosidase inhibitory activity of new compounds and hence speed up the discovery of new potent multi-target antidiabetic agents.Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Keywords

algorithmsfuriafuria-cinduction ruleldamachine-learning techniquespredictionqsarxanthoneAnti-diabetic agentsDerivativesFuria-cInduction ruleLdaMachine-learning techniquesQsar

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The work has been published in the journal Current Computer-Aided Drug Design, and although the journal is classified in the quartile Q4 (Agencia WoS (JCR)), its regional focus and specialization in Chemistry, Medicinal, give it significant recognition in a specific niche of scientific knowledge at an international level.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-05-26:

WoS: 2
Scopus: 3
OpenCitations: 2

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This work has been carried out with international collaboration, specifically with researchers from: Ecuador; United States of America.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (GONZALEZ ARJONA, DAVID).

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