Diacylglycerol acyltransferase-inhibitory compounds from Erythrina senegalensis

Oh, Won Keun; Lee, Chul‐Ho; Seo, Jee Hee; Chung, Mi Yeon; Cui, Long; Fomum, Zacharias Tanee; Kang, Jong Seong; Lee, Hyun Sun

doi:10.1007/s12272-009-1116-2

Cited by 18 publications

(13 citation statements)

References 23 publications

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“…Isoprenylated flavonoids isolated from Erythrina mildbraedii and prenylflavonoids isolated from the Erythrina senegalensis roots have been described as inhibitors of two other proteins frequently targeted in T2DM treatment ( i.e. , protein tyrosine phosphatase-1B [25], [26] for the former class of molecules and acyl CoA:diacylglycerol acyltransferase [24] for the latter class). All of these flavonoid compounds are chemically related to our hit.…”

Section: Resultsmentioning

confidence: 99%

Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part II): In Silico Prediction in Antidiabetic Extracts

et al. 2012

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BackgroundNatural 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 FindingsUsing 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/SignificanceOur 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.

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Section: Resultsmentioning

confidence: 99%

Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part II): In Silico Prediction in Antidiabetic Extracts

et al. 2012

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“…A number of natural products isolated from microorganisms, plants, and fish oils possess DGAT inhibitory effects with IC 50 values in the μM range (50–200 μM) [333–340]. Eight prenylflavonoids extracted from the bark of Erythrina senegalensis were tested against DGAT activity in vitro and six compounds displayed inhibitory activity (IC 50 from 1.1 to 15 μg/ml) [339]. Four sesquiterpenoids isolated from the flower buds of Tussilago farfara inhibited DGAT1 activity in rat liver and HepG2 microsomes in the mid to high micromolar range (IC 50 from 18 to ~300 μM) [340].…”

Section: Fatty Acyltransferasesmentioning

confidence: 99%

Chemical modulation of glycerolipid signaling and metabolic pathways

Scott

Mathews

Ivanova

et al. 2014

Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biolog

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Thirty years ago, glycerolipids captured the attention of biochemical researchers as novel cellular signaling entities. We now recognize that these biomolecules occupy signaling nodes critical to a number of physiological and pathological processes. Thus, glycerolipid-metabolizing enzymes present attractive targets for new therapies. A number of fields—ranging from neuroscience and cancer to diabetes and obesity—have elucidated the signaling properties of glycerolipids. The biochemical literature teems with newly emerging small molecule inhibitors capable of manipulating glycerolipid metabolism and signaling. This ever-expanding pool of chemical modulators appears daunting to those interested in exploiting glycerolipid-signaling pathways in their model system of choice. This review distills the current body of literature surrounding glycerolipid metabolism into a more approachable format, facilitating the application of small molecule inhibitors to novel systems.

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“…Clustering provides an additional way to partition CSs into a set of nonintersecting subsets that cover the space [161]. Although clustering methods have some advantages over cell-based partitioning, they are difficult to apply to datasets as large as those that can be handled relatively easily using a cell-based approach.…”

Section: Cell-based Cssmentioning

confidence: 99%

“…This is not a problem in the cell-based case since the CS partitioning scheme is effectively compound independent-adding new compounds does not change the partitioning scheme. Moreover, many methods such as k-means clustering require specification of the number of clusters and hierarchical methods produce similarity (or distance)-dependent clusterings [161]. Lastly, because the clustering methods are a vast subject, even when only considered with respect to cheminformatics applications, no further discussion on this topic is provided in this work.…”

Section: Cell-based Cssmentioning

confidence: 99%

Foodinformatics

2014

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Diacylglycerol acyltransferase-inhibitory compounds from Erythrina senegalensis

Cited by 18 publications

References 23 publications

Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part II): In Silico Prediction in Antidiabetic Extracts

Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part II): In Silico Prediction in Antidiabetic Extracts

Chemical modulation of glycerolipid signaling and metabolic pathways

Foodinformatics

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