4.6 Article

Exploring African Medicinal Plants for Potential Anti-Diabetic Compounds with the DIA-DB Inverse Virtual Screening Web Server

Journal

MOLECULES
Volume 24, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/molecules24102002

Keywords

diabetes; anti-diabetic; DIA-DB; medicinal plants; in silico; virtual screening

Funding

  1. Spanish Ministry of Economy and Competitiveness [CTQ2017-87974-R]
  2. Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia [20988/PI/18, 20524/PDC/18]
  3. e-infrastructure program of the Research Council of Norway
  4. supercomputing infrastructure of Poznan Supercomputing Center
  5. supercomputer center of UiT-the Arctic University of Norway
  6. supercomputing infrastructure of the NLHPC [ECM-02]
  7. National Research Foundation of South Africa

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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 compoundscrotofoline A, erythraline, henningsiine, nauclefidine, vinburnine, and voaphyllinewere identified as novel potential multi-targeted anti-diabetic compounds, with favorable ADMET properties for further drug development.

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