Docking-based 3D-QSAR study for selectivity of DPP4, DPP8, and DPP9 inhibitors

Kang, Nam Sook; Ahn, Jin Hee; Kim, Sung Soo; Chae, Chong Hak; Yoo, Sung‐Eun

doi:10.1016/j.bmcl.2007.04.031

Cited by 25 publications

(23 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The S3 pocket of DPP-IV consists of Ser209, Arg358, and Phe357 [21]. The outside position of the S3 pocket in DPP-IV allows larger groups access to the site; on the other hand, the inside position of the S3 pocket favors smaller groups [28]. The four most potent compounds, resveratrol, luteolin, apigenin and flavone, had low K i values to inhibit DPP-IV, which indicated that they had high affinity to the active sites of DPP-IV.…”

Section: Discussionmentioning

confidence: 99%

Berry and Citrus Phenolic Compounds Inhibit Dipeptidyl Peptidase IV: Implications in Diabetes Management

Fan

Johnson

Lila

et al. 2013

Evidence-Based Complementary and Alternative Medicine

143

148

View full text Add to dashboard Cite

Beneficial health effects of fruits and vegetables in the diet have been attributed to their high flavonoid content. Dipeptidyl peptidase IV (DPP-IV) is a serine aminopeptidase that is a novel target for type 2 diabetes therapy due to its incretin hormone regulatory effects. In this study, well-characterized anthocyanins (ANC) isolated from berry wine blends and twenty-seven other phenolic compounds commonly present in citrus, berry, grape, and soybean, were individually investigated for their inhibitory effects on DPP-IV by using a luminescence assay and computational modeling. ANC from blueberry-blackberry wine blends strongly inhibited DPP-IV activity (IC50, 0.07 ± 0.02 to >300 μM). Of the twenty-seven phenolics tested, the most potent DPP-IV inhibitors were resveratrol (IC50, 0.6 ± 0.4 nM), luteolin (0.12 ± 0.01 μM), apigenin (0.14 ± 0.02 μM), and flavone (0.17 ± 0.01 μM), with IC50 values lower than diprotin A (4.21 ± 2.01 μM), a reference standard inhibitory compound. Analyses of computational modeling showed that resveratrol and flavone were competitive inhibitors which could dock directly into all three active sites of DPP-IV, while luteolin and apigenin docked in a noncompetitive manner. Hydrogen bonding was the main binding mode of all tested phenolic compounds with DPP-IV. These results indicate that flavonoids, particularly luteolin, apigenin, and flavone, and the stilbenoid resveratrol can act as naturally occurring DPP-IV inhibitors.

show abstract

Section: Discussionmentioning

confidence: 99%

Berry and Citrus Phenolic Compounds Inhibit Dipeptidyl Peptidase IV: Implications in Diabetes Management

Fan

Johnson

Lila

et al. 2013

Evidence-Based Complementary and Alternative Medicine

143

148

View full text Add to dashboard Cite

show abstract

“…The S3 site is greatly different for each isoenzyme. The S3 site in DPP4 is acceptable to less bulky groups that DPP8 and DPP9 [11].…”

Section: Dipeptidyl Peptidase-4mentioning

confidence: 97%

“…According to this study, the interaction of the inhibitors with the S3 site and S1' site in DPP4 should be carefully considered in order to obtain selective DPP4 inhibitors compared to the isoenzymes. Newly synthesised compounds (KR64300 and KR64301) interact well with these sites and seem to be selective [11].…”

Section: Dpp4 Inhibitorsmentioning

confidence: 99%

“…The monomeric form of DPP4 has no enzyme activity. Because DPP4 as a homodimer is a fully active enzyme, activity regulation has to be realised at the level of gene expression, protein synthesis and substrate selection [8][9][10][11][14][15][16][17]. Interferons and retinoic acid upregulated DPP4 gene expression through the signalling pathway involving the signal transducer and activator of transcription Stat1 , which binds consensus sequences known as GAS motifs, to activate CD26 gene promoters [14].…”

Section: Catalytic Activitymentioning

confidence: 99%

See 1 more Smart Citation

Dipeptidyl Peptidase-4 (CD26): Knowing the Function before Inhibiting the Enzyme

Matteucci

Giampietro

2009

CMC

174

View full text Add to dashboard Cite

Dipeptidyl peptidase-4 (DPP4) or adenosine deaminase complexing protein 2 (ADCP 2) or T-cell activation antigen CD26 (EC 3.4.14.5.) is a serine exopeptidase belonging to the S9B protein family that cleaves X-proline dipeptides from the N-terminus of polypeptides, such as chemokines, neuropeptides, and peptide hormones. The enzyme is a type II transmembrane glycoprotein, expressed on the surface of many cell types, whose physiological functions are largely unknown. Protein dimerisation should be required for catalytic activity and glycosylation of the enzyme could impact on its physiological functions. The dimeric glycoprotein ADCP has been found linked to adenosine deaminase (ADA) whose relationship with lymphocyte maturation-differentiation is well-established. Since implicated in the regulation of the biological activity of hormones and chemokines, such as glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide, DPP4 inhibition offers a new potential therapeutic approach for type 2 diabetes mellitus, as monotherapy and adjunct therapy to other oral agents. The clinical use of presently available orally active inhibitors of DPP4, however, has been associated with side effects that have been in part attributed to the inhibition of related serine proteases, such as DPP8 and DPP9. Indeed, it is noteworthy that CD26 has a key role in immune regulation as a T cell activation molecule and in immune-mediated disorder. All-cause infections were increased after sitagliptin treatment. It is noteworthy that the effects of DPP4 inhibition on the immune system have not been extensively investigated. So far, only routine laboratory safety variables have been measured in published randomised controlled trials. The review summarises present knowledge in the field and suggests some potential directions of future research.

show abstract

“…The strategy of combining 3D contour maps with the structural environment of the protein (target binding site) has proven useful to investigate important parameters such as affinity and potency, but can also be used to study other pharmacodymanic and pharmacokinetic properties, including selectivity, reactivity and metabolism [71,107,[119][120][121][122][123][124][125][126][127]. Furthermore, considering that the QSAR models may provide useful insights into structural and chemical features related to the property of interest (biological activity parameter), it is possible to envisage that the same general approach can be applied in SBVS for the identification of hits [128][129][130][131].…”

Section: Structure-based Lead Optimizationmentioning

confidence: 99%

Structure-Based Drug Design Strategies in Medicinal Chemistry

Andricopulo¹,

Salum²,

Abraham

2009

CTMC

138

View full text Add to dashboard Cite

A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the development of high quality drug candidates. Structure-based drug design (SBDD) methods are becoming increasingly powerful, versatile and more widely used. This review summarizes current developments in structure-based virtual screening and receptor-based pharmacophores, highlighting achievements as well as challenges, along with the value of structure-based lead optimization, with emphasis on recent examples of successful applications for the identification of novel active compounds.Keywords: Structure-based drug design, medicinal chemistry, virtual screening, QSAR, pharmacophores. STRUCTURE-BASED DRUG DESIGNThe performance of biochemical processes and cell mechanisms are dependent upon complex and multiple noncovalent intermolecular interactions between proteins and small-molecule modulators. The understanding of the structural and chemical binding properties of important drug targets in biologically relevant pathways allows the design of small molecules capable of regulating or modulating specific target functions in the body that are closely linked to human diseases and disorders, through multiple intermolecular interactions within a well-defined binding pocket [1][2][3][4]. In general, the identification of promising hits for further optimization is a major challenge faced by the both pharmaceutical and academic laboratories. Although the trial-anderror nature is inherent in drug research, rational concepts and modern computational methods have become widely employed for lead selection and optimization.The use of three-dimensional (3D) protein structure information in the development of new biologically active molecules, which is termed Structure-Based Drug Design (SBDD), is a well-established, successful and highly attarctive strategy used by academic and pharmaceutical research laboratories worldwide [3][4][5][6][7][8]. As a creative and knowledgedriven approach, an essential requirement for structure-based studies is a substantial understanding of the spatial and energetic aspects that affect the binding affinities of proteinligand complexes. Considering that the shape and chemical nature of the binding site of a specific target protein are known, and the possible intermolecular interactions between ligands and the protein within its active site have been identified, this qualified information can be directly employed for the identification of new ligands and the optimization of lead compounds. This opens new possibilities to boost the search for lead molecules and to limit the number of compounds that need to be evaluated experimentally.Hits can be identified through the docking of smallmolecule ligands (selected from databases of chemical structures) into protein active sites or by using receptorbased pharmacophore models. Furthermore, drug candidates can be designed de novo by improving the complementary binding properties of lead compounds and the r...

show abstract

Docking-based 3D-QSAR study for selectivity of DPP4, DPP8, and DPP9 inhibitors

Cited by 25 publications

References 30 publications

Berry and Citrus Phenolic Compounds Inhibit Dipeptidyl Peptidase IV: Implications in Diabetes Management

Berry and Citrus Phenolic Compounds Inhibit Dipeptidyl Peptidase IV: Implications in Diabetes Management

Dipeptidyl Peptidase-4 (CD26): Knowing the Function before Inhibiting the Enzyme

Structure-Based Drug Design Strategies in Medicinal Chemistry

Contact Info

Product

Resources

About