Dataset Information

Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (Part II): in silico prediction in antidiabetic extracts.

ABSTRACT:

Background

Natural extracts play an important role in traditional medicines for the treatment of diabetes mellitus and are also an essential resource for new drug discovery. Dipeptidyl peptidase IV (DPP-IV) inhibitors are potential candidates for the treatment of type 2 diabetes mellitus, and the effectiveness of certain antidiabetic extracts of natural origin could be, at least partially, explained by the inhibition of DPP-IV.

Methodology/principal findings

Using an initial set of 29,779 natural products that are annotated with their natural source and an experimentally validated virtual screening procedure previously developed in our lab (Guasch et al.; 2012) [1], we have predicted 12 potential DPP-IV inhibitors from 12 different plant extracts that are known to have antidiabetic activity. Seven of these molecules are identical or similar to molecules with described antidiabetic activity (although their role as DPP-IV inhibitors has not been suggested as an explanation for their bioactivity). Therefore, it is plausible that these 12 molecules could be responsible, at least in part, for the antidiabetic activity of these extracts through their inhibitory effect on DPP-IV. In addition, we also identified as potential DPP-IV inhibitors 6 molecules from 6 different plants with no described antidiabetic activity but that share the same genus as plants with known antidiabetic properties. Moreover, none of the 18 molecules that we predicted as DPP-IV inhibitors exhibits chemical similarity with a group of 2,342 known DPP-IV inhibitors.

Conclusions/significance

Our study identified 18 potential DPP-IV inhibitors in 18 different plant extracts (12 of these plants have known antidiabetic properties, whereas, for the remaining 6, antidiabetic activity has been reported for other plant species from the same genus). Moreover, none of the 18 molecules exhibits chemical similarity with a large group of known DPP-IV inhibitors.

SUBMITTER: Guasch L

PROVIDER: S-EPMC3448616 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (Part II): in silico prediction in antidiabetic extracts.

Guasch Laura L Sala Esther E Ojeda María José MJ Valls Cristina C Bladé Cinta C Mulero Miquel M Blay Mayte M Ardévol Anna A Garcia-Vallvé Santiago S Pujadas Gerard G

PloS one 20120921 9

<h4>Background</h4>Natural extracts play an important role in traditional medicines for the treatment of diabetes mellitus and are also an essential resource for new drug discovery. Dipeptidyl peptidase IV (DPP-IV) inhibitors are potential candidates for the treatment of type 2 diabetes mellitus, and the effectiveness of certain antidiabetic extracts of natural origin could be, at least partially, explained by the inhibition of DPP-IV.<h4>Methodology/principal findings</h4>Using an initial set o ...[more]

PMID: 23028712

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Project description:BackgroundThere has been great interest in determining whether natural products show biological activity toward protein targets of pharmacological relevance. One target of particular interest is DPP-IV whose most important substrates are incretins that, among other beneficial effects, stimulates insulin biosynthesis and secretion. Incretins have very short half-lives because of their rapid degradation by DPP-IV and, therefore, inhibiting this enzyme improves glucose homeostasis. As a result, DPP-IV inhibitors are of considerable interest to the pharmaceutical industry. The main goals of this study were (a) to develop a virtual screening process to identify potential DPP-IV inhibitors of natural origin; (b) to evaluate the reliability of our virtual-screening protocol by experimentally testing the in vitro activity of selected natural-product hits; and (c) to use the most active hit for predicting derivatives with higher binding affinities for the DPP-IV binding site.Methodology/principal findingsWe predicted that 446 out of the 89,165 molecules present in the natural products subset of the ZINC database would inhibit DPP-IV with good ADMET properties. Notably, when these 446 molecules were merged with 2,342 known DPP-IV inhibitors and the resulting set was classified into 50 clusters according to chemical similarity, there were 12 clusters that contained only natural products for which no DPP-IV inhibitory activity has been previously reported. Nine molecules from 7 of these 12 clusters were then selected for in vitro activity testing and 7 out of the 9 molecules were shown to inhibit DPP-IV (where the remaining two molecules could not be solubilized, preventing the evaluation of their DPP-IV inhibitory activity). Then, the hit with the highest activity was used as a lead compound in the prediction of more potent derivatives.Conclusions/significanceWe have demonstrated that our virtual-screening protocol was successful in identifying novel lead compounds for developing more potent DPP-IV inhibitors.

Project description:BackgroundNatural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and their modes of action.Methodology/principal findingsFrom an initial set of 29,779 natural products that are annotated with their natural source and using a previously developed virtual screening procedure (carefully validated experimentally), we have predicted as potential peroxisome proliferators-activated receptor gamma (PPAR?) partial agonists 12 molecules from 11 extracts known to have antidiabetic activity. Six of these molecules are similar to molecules with described antidiabetic activity but whose mechanism of action is unknown. Therefore, it is plausible that these 12 molecules could be the bioactive molecules responsible, at least in part, for the antidiabetic activity of the extracts containing them. In addition, we have also identified as potential PPAR? partial agonists 10 molecules from 16 plants with undescribed antidiabetic activity but that are related (i.e., they are from the same genus) to plants with known antidiabetic properties. None of the 22 molecules that we predict as PPAR? partial agonists show chemical similarity with a group of 211 known PPAR? partial agonists obtained from the literature.Conclusions/significanceOur results provide a new hypothesis about the active molecules of natural extracts with antidiabetic properties and their mode of action. We also suggest plants with undescribed antidiabetic activity that may contain PPAR? partial agonists. These plants represent a new source of potential antidiabetic extracts. Consequently, our work opens the door to the discovery of new antidiabetic extracts and molecules that can be of use, for instance, in the design of new antidiabetic drugs or functional foods focused towards the prevention/treatment of type 2 Diabetes Mellitus.

Dataset Information

Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (Part II): in silico prediction in antidiabetic extracts.

Background

Methodology/principal findings

Conclusions/significance

Publications

Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (Part II): in silico prediction in antidiabetic extracts.

Similar Datasets

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