Background: Diabetes mellitus is a chronic metabolic disease that is a risk factor for epidemic pathologies. Under hyperglycemic conditions, the enzyme aldose reductase catalyzes the formation of sorbitol in the metabolism of glucose via polyols, leading to the development of diabetic complications. Therefore, inhibitors of this enzyme are therapeutic targets for the prophylaxis and treatment of these conditions. Methods: In this study, a generalized linear regression model was developed to analyze flavonoids—obtained from a database—that have been tested as inhibitors of aldose reductase. In this sense, the molecular descriptors implemented in DRAGON and MATLAB software were used to determine the correlation between the chemical structure of the inhibitors and their pharmacological activity. The model was validated according to the Organisation for Economic Co-operation and Development Standards and subsequently used for the virtual screening of the flavonoids identified in Jatropha gossypiifolia L. Results: The proposed model showed a good fit for its statistical parameters (R2 = 0.95). In addition, it showed good predictive power (R2ext = 0.94) and robustness (Q2LOO = 0.92). The experimental chemical space wherein the predictions were reliable (domain of application) was also defined. Finally, the model was used to identify 10 flavonoids from Jatropha gossypiifolia L. as candidates for natural drugs. Compounds with a low probability of oral absorption were identified, among which the elagic acid biflavonoid showed the greatest promise (pIC50 predicted = 9.75). Conclusion: The Jatropha gossypiifolia L. species harbors flavonoids with high potential as inhibitors of the aldose reductase enzyme, in which the biflavonoid ellagic acid was shown to be the most promising inhibitor of the aldose reductase enzyme, suggesting its possible use in the treatment of the late complications of diabetes mellitus.

Yudith Ca?izares-Carmenate;Roberto Díaz-Amador;Mirtha Mayra Gonzalez-Bedia;Tan Tran Quang Nhat;Francisco Torrens;Juan Alberto Castillo-Garit

Unit of Computer-Aided Molecular"Biosilico"Discovery and Bioinformatic Research,Departamento de Farmacia,Facultad de Química-Farmacia,Universidad Central"Marta Abreu"de Las Villas,Santa Clara 54830,Villa Clara,Cuba;Departamento de Ciencias de la Computación,Facultad de Matemática,Física y Computación,Universidad Celara,Cuntral"Marta Abreu"de Las Villas,Santa Clara 54830,Villa Clara,Cuba;Institut Universitari de Ciència Molecular,Universitat de València,Edifici d'Instituts de Paterna,P.O.Box 22085,València,Spain;Unidad de Toxicología Experimental,Universidad de Ciencias Médicas de Villa Clara,Santa Clara 50200,Villa Clara,Cuba.

传统医学研究（英文版）

[1]Yudith Ca?izares-Carmenate;Roberto Díaz-Amador;Mirtha Mayra Gonzalez-Bedia;Tan Tran Quang Nhat;Francisco Torrens;Juan Alberto Castillo-Garit-.Virtual screening of flavonoids from Jatropha gossypiifolia L. as potential drugs for diabetic complications)[J].传统医学研究（英文版）,2022(02):34-42

gossypiifolia,R2ext,elagic,biflavonoid,pIC50

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