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Molecules 2017, 22(9), 1563; doi:10.3390/molecules22091563

Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties

1,†
,
2,†
,
3,†
,
4,5,†
and
2,6,*
1
Molecular Genetics and Virology Laboratory, QRC-Qasemi Research Center, Al-Qasemi Academic College, P.O. Box 124, Baka EL-Garbiah 30100, Israel
2
Institute of Applied Research-Galilee Society, P.O. Box 437, Shefa-Amr 20200, Israel
3
Clalit Health Service, Diet and Nutrition Unit, P.O. Box 789, Arara 30026, Israel
4
Eliachar Research Laboratory, Galilee Medical Center, P.O. Box 21, Nahariya 22100, Israel
5
Faculty of Medicine in the Galilee, Bar-Ilan University, Ramat Gan 52900, Israel
6
Drug Discovery Informatics Laboratory, QRC-Qasemi Research Center, Al-Qasemi Academic College, P.O. Box 124, Baka EL-Garbiah 30100, Israel
*
Author to whom correspondence should be addressed.
Received: 13 August 2017 / Revised: 14 September 2017 / Accepted: 14 September 2017 / Published: 17 September 2017
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Abstract

Diabetes mellitus (DM) poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of ‘iterative stochastic elimination’ was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive), 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries. View Full-Text
Keywords: diabetes mellitus; anti-diabetic drugs; drugs analysis; ligand-based screening approach; bioactivity index diabetes mellitus; anti-diabetic drugs; drugs analysis; ligand-based screening approach; bioactivity index
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MDPI and ACS Style

Zeidan, M.; Rayan, M.; Zeidan, N.; Falah, M.; Rayan, A. Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties. Molecules 2017, 22, 1563.

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