Publication:
Navigating the chemical space of dipeptidyl peptidase-4 inhibitors

dc.contributor.authorWatshara Shoombuatongen_US
dc.contributor.authorVeda Prachayasittikulen_US
dc.contributor.authorNuttapat Anuwongcharoenen_US
dc.contributor.authorNapat Songtaweeen_US
dc.contributor.authorTeerawat Monnoren_US
dc.contributor.authorSupaluk Prachayasittikulen_US
dc.contributor.authorVirapong Prachayasittikulen_US
dc.contributor.authorChanin Nantasenamaten_US
dc.contributor.otherMahidol University. Faculty of Medical Technology. Center of Data Mining and Biomedical Informaticsen_US
dc.contributor.otherMahidol University. Faculty of Medical Technology. Department of Clinical Microbiology and Applied Technologyen_US
dc.date.accessioned2015-08-11T04:44:00Z
dc.date.accessioned2017-06-20T16:43:09Z
dc.date.available2015-08-11T04:44:00Z
dc.date.available2017-06-20T16:43:09Z
dc.date.issued2015-08-10
dc.description.abstractThis study represents the first large-scale study on the chemical space of inhibitors of dipeptidyl peptidase-4 (DPP4), which is a potential therapeutic protein target for the treatment of diabetes mellitus. Herein, a large set of 2,937 compounds evaluated for their ability to inhibit DPP4 was compiled from the literature. Molecular descriptors were generated from the geometrically optimized low-energy conformers of these compounds at the semiempirical AM1 level. The origins of DPP4 inhibitory activity were elucidated from computed molecular descriptors that accounted for the unique physicochemical properties inherently present in the active and inactive sets of compounds as defined by their respective half maximal inhibitory concentration values of less than 1 µM and greater than 10 µM, respectively. Decision tree analysis revealed the importance of molecular weight, total energy of a molecule, topological polar surface area, lowest unoccupied molecular orbital, and number of hydrogen-bond donors, which correspond to molecular size, energy, surface polarity, electron acceptors, and hydrogen bond donors, respectively. The prediction model was subjected to rigorous independent testing via three external sets. Scaffold and chemical fragment analysis was also performed on these active and inactive sets of compounds to shed light on the distinguishing features of the functional moieties. Docking of representative active DPP4 inhibitors was also performed to unravel key interacting residues. The results of this study are anticipated to be useful in guiding the rational design of novel and robust DPP4 inhibitors for the treatment of diabetes.en_US
dc.identifier.citationDrug Design, Development and Therapy. Vol.9, 2015, 4515-4549en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/2123
dc.language.isoengen_US
dc.subjectQSARen_US
dc.subjectdecision treeen_US
dc.subjectscaffold analysisen_US
dc.subjectfragment analysisen_US
dc.subjectantidiabeticen_US
dc.subjectmolecular dockingen_US
dc.subjectrational drug designen_US
dc.subjectOpen Access articleen_US
dc.titleNavigating the chemical space of dipeptidyl peptidase-4 inhibitorsen_US
dc.typeArticleen_US
dspace.entity.typePublication
mods.location.urlhttp://www.dovepress.com/navigating-the-chemical-space-of-dipeptidyl-peptidase-4-inhibitors-peer-reviewed-article-DDDT

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