Exploring African medicinal plants for potential anti-diabetic compounds with the DIA-DB inverse virtual screening web server

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dc.contributor.author Pereira, Andreia S.P.
dc.contributor.author Den Haan, Helena
dc.contributor.author Pena-Garcia, Jorge
dc.contributor.author Moreno, Marien M.
dc.contributor.author Perez-Sanchez, Horacio
dc.contributor.author Apostolides, Zeno
dc.date.accessioned 2020-08-13T05:55:55Z
dc.date.available 2020-08-13T05:55:55Z
dc.date.issued 2019-05
dc.description Supplementary Materials: Table S1—SMILES notations of all compounds evaluated in the study. Table S2—Assigned numerical identity of predicted active compounds, their plant sources and predicted targets. Figure S1—Individual predicted active compound–protein target networks. Table S3—Plants having scientific anti-diabetic evidence and evidence of traditional use only identified by virtual screening and their predicted bioactive compounds. Figure S2—Dendrograms of hierarchical clustering analysis. en_ZA
dc.description.abstract Medicinal plants containing complex mixtures of several compounds with various potential beneficial biological effects are attractive treatment interventions for a complex multi-faceted disease like diabetes. In this study, compounds identified from African medicinal plants were evaluated for their potential anti-diabetic activity. A total of 867 compounds identified from over 300 medicinal plants were screened in silico with the DIA-DB web server (http://bio-hpc.eu/software/dia-db/) against 17 known anti-diabetic drug targets. Four hundred and thirty compounds were identified as potential inhibitors, with 184 plants being identified as the sources of these compounds. The plants Argemone ochroleuca, Clivia miniata, Crinum bulbispermum, Danais fragans, Dioscorea dregeana, Dodonaea angustifolia, Eucomis autumnalis, Gnidia kraussiana, Melianthus comosus, Mondia whitei, Pelargonium sidoides, Typha capensis, Vinca minor, Voacanga africana, and Xysmalobium undulatum were identified as new sources rich in compounds with a potential anti-diabetic activity. The major targets identified for the natural compounds were aldose reductase, hydroxysteroid 11-beta dehydrogenase 1, dipeptidyl peptidase 4, and peroxisome proliferator-activated receptor delta. More than 30% of the compounds had five or more potential targets. A hierarchical clustering analysis coupled with a maximum common substructure analysis revealed the importance of the flavonoid backbone for predicting potential activity against aldose reductase and hydroxysteroid 11-beta dehydrogenase 1. Filtering with physiochemical and the absorption, distribution, metabolism, excretion and toxicity (ADMET) descriptors identified 28 compounds with favorable ADMET properties. The six compounds—crotofoline A, erythraline, henningsiine, nauclefidine, vinburnine, and voaphylline—were identified as novel potential multi-targeted anti-diabetic compounds, with favorable ADMET properties for further drug development. en_ZA
dc.description.department Biochemistry en_ZA
dc.description.department Genetics en_ZA
dc.description.department Microbiology and Plant Pathology en_ZA
dc.description.librarian pm2020 en_ZA
dc.description.sponsorship The National Research Foundation of South Africa, the Spanish Ministry of Economy and Competitiveness, Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia, Poznan Supercomputing Center, the Research Council of Norway and Arctic University of Norway. en_ZA
dc.description.uri https://www.mdpi.com/journal/molecules en_ZA
dc.identifier.citation Pereira, A.S.P., Den Haan, H., Pena-Garcia, J. et al, 2019, 'Exploring African medicinal plants for potential anti-diabetic compounds with the DIA-DB inverse virtual screening web server', Molecules, vol. 24, no. 10, art. 2002, pp. 1-30. en_ZA
dc.identifier.issn 1420-3049 (online)
dc.identifier.other 10.3390/molecules24102002
dc.identifier.uri http://hdl.handle.net/2263/75676
dc.language.iso en en_ZA
dc.publisher MDPI en_ZA
dc.rights © 2019 The Authors. Licensee : MDPI, Basel, Switzerland. This article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license 4.0). en_ZA
dc.subject Diabetes en_ZA
dc.subject Anti-diabetic en_ZA
dc.subject DIA-DB en_ZA
dc.subject Medicinal plants en_ZA
dc.subject In silico en_ZA
dc.subject Virtual screening en_ZA
dc.subject Absorption, distribution, metabolism, excretion and toxicity (ADMET) en_ZA
dc.title Exploring African medicinal plants for potential anti-diabetic compounds with the DIA-DB inverse virtual screening web server en_ZA
dc.type Article en_ZA


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