Computational studies on structurally diverse dipeptidyl peptidase IV inhibitors: an approach for new antidiabetic drug development

Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management

Dipeptidyl peptidase-4 (DPP-4) inhibitors belong to a prominent group of pharmaceutical agents that are used in the governance of type 2 diabetes mellitus (T2DM). They exert their antidiabetic effects by inhibiting the incretin hormones like glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide which, play a pivotal role in the regulation of blood glucose homoeostasis in our body. DPP-4 inhibitors have emerged as an important class of oral antidiabetic drugs for the treatment of T2DM. Surprisingly, only a few 2D-QSAR studies have been reported on DPP-4 inhibitors. Here, fragment-based QSAR (Laplacian-modified Bayesian modelling and Recursive partitioning (RP) approaches have been utilized on a dataset of 108 DPP-4 inhibitors to achieve a deeper understanding of the association among their molecular structures. The Bayesian analysis demonstrated satisfactory ROC values for the training as well as the test sets. Meanwhile, the RP analysis resulted in decision tree 3 with 2 leaves (Tree 3: 2 leaves). This present study is an effort to get an insight into the pivotal fragments modulating DPP-4 inhibition.

A review upon medicinal perspective and designing rationale of DPP-4 inhibitors

Type 2 Diabetes Mellitus (T2DM) is one of the highly prevalence disorder and increasing day by day worldwidely. T2DM is a metabolic disorder, which is characterized by deficiency in insulin or resistance to insulin and thus increases the glucose levels in the blood. Various approaches are there to treat diabetes but still there is no cure for this disease. DPP-4 inhibitor is a privileged target in the field of drug discovery and provides various opportunities in exploring this target for development of molecules as antidiabetic agents. DPP-4 acts by inhibiting the incretin action and thus decreases the level of blood glucose by imparting minimal side effects. Sitagliptin, vildagliptin, linagliptin etc. are the different DPP-4 based drugs approved throughout the world for the treatment of diabetes mellitus. Cyanopyrrolidines, triazolopiperazine amide, pyrrolidines are basic core nucleus present in various DPP-4 inhibitors and has potential effects. In the past few years, researchers had applied various approaches to synthesize potent DPP-4 inhibitors as antidiabetic agent without side effects like weight gain, cardiovascular risks, retinopathy etc. This review will also emphasize the recent strategies and rationale utilized by researchers for the development of DPP-4 inhibitors. This review also reveals about the various other approaches like molecular modelling, ligand based drug designing, high throughput screening etc. are used by the various research group for the development of potential DPP-4 inhibitors.

In silico analysis of a potential antidiabetic phytochemical erythrin against therapeutic targets of diabetes

Diabetes mellitus is a multifactorial disorder characterized by a chronic elevation in blood glucose levels. Currently, antidiabetic drugs are available to counteract the associated pathologies. Their concomitant effects necessitate the investigation for an effective and safe drug aimed to diminish blood glucose levels with fewer side effects. Several researchers are taking new initiatives to explore plant sources as they are known to contain a wide variety of active agents. Hence, the present study was undertaken to study the role of natural products using in silico interaction studies. Erythrin a compound present in lichens was selected as a potential anti-diabetic agent. Molecular docking studies were carried out with 14 target proteins to evaluate its antidiabetic potential. Molecular docking analysis resulted in favourable binding energy of interaction ranging as low as - 119.676 to - 92.9545 kcal/mol for erythrin, Analogue showed the highest interactions with 3C45 (- 119.676 kcal/mol) followed by 2Q5S (- 118.398 kcal/mol), 1XU7 (- 117.341 kcal/mol), 3K35 (- 114.267 kcal/mol). Erythrin was found to fare better than the three clinically used antidiabetic compounds, metformin, repaglinide and sitagliptin. Further, the molecular interactions between erythrin and the diabetes related target proteins was established by analysing the interactions with associated amino acids. In silico pharmacokinetics and toxicity profile of erythrin using admetSAR software predicted erythrin as non-carcinogenic and non-mutagenic. The drug-likeliness was calculated using molsoft software respecting Lipinski's rule of five. The compound was found to comply with Lipinksi rules violating only one filter criterion. The study suggested that erythrin could be a potential anti-diabetic agent.

Combined Ligand-Based and Structure-Based Virtual Screening Approach for Identification of New Dipeptidyl Peptidase 4 Inhibitors

BACKGROUND

Dipeptidyl Peptidase 4 (DPP 4) enzyme cleaves an incretin-based glucoregulatory hormone Glucagon Like Peptide -1 from N-terminal where penultimate amino acid is either alanine or proline. Several DPP 4 inhibitors, "gliptins", are approved for the management of Type 2 Diabetes or are under clinical trial. In the present study, combined pharmacophore and docking-based virtual screening protocol were used for the identification of new hits from the Specs Database, which would inhibit DPP 4.

METHODS

The entire computational studies were performed using the Discovery Studio v. 4.1 software package, Pipeline Pilot v. 9.2 (Accelrys Inc.) and FRED v. 2.2.5 (OpenEye Scientific Software). Common feature pharmacophore model was generated from known DPP 4 inhibitors and validated by Receiver Operating curve analysis and GH-scoring method. Database search of Specs commercial database was performed using validated pharmacophore. Hits obtained from pharmacophore search were further docked into the binding site of DPP 4. Based on the analysis of docked poses of hits, 10 compounds were selected for in- vitro DPP 4 enzyme inhibition assay.

RESULTS

Based on docking studies, virtual hits were predicted to form interaction with essential amino acid residues of DPP 4 and have an almost similar binding orientation as that of the reference molecule. Three compounds having Specs database ID- AN-465/42837213, AP-064/42049348 and AN- 465/43369427 were found to inhibit DPP 4 enzyme moderately.

CONCLUSION

The present study demonstrates a successful utilization of in-silico tools in the identification of new DPP 4 inhibitor, which can serve as a starting point for the development of novel DPP 4 inhibitors.

Mining large databases to find new leads with low similarity to known actives: application to find new DPP-IV inhibitors

Aim: Fragment-based drug design or bioisosteric replacement is used to find new actives with low (or no) similarity to existing ones but requires the synthesis of nonexisting compounds to prove their predicted bioactivity. Protein-ligand docking or pharmacophore screening are alternatives but they can become computationally expensive when applied to very large databases such as ZINC. Therefore, fast strategies are necessary to find new leads in such databases. Materials & methods: We designed a computational strategy to find lead molecules with very low (or no) similarity to existing actives and applied it to DPP-IV. Results: The bioactivity assays confirm that this strategy finds new leads for DPP-IV inhibitors. Conclusion: This computational strategy reduces the time of finding new lead molecules.

Activity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening

The inhibition of dipeptidyl peptidase-IV (DPP-IV) has emerged over the last decade as one of the most effective treatments for type 2 diabetes mellitus, and consequently (a) 11 DPP-IV inhibitors have been on the market since 2006 (three in 2015), and (b) 74 noncovalent complexes involving human DPP-IV and drug-like inhibitors are available at the Protein Data Bank (PDB). The present review aims to (a) explain the most important activity cliffs for DPP-IV noncovalent inhibition according to the binding site structure of DPP-IV, (b) explain the most important selectivity cliffs for DPP-IV noncovalent inhibition in comparison with other related enzymes (i.e., DPP8 and DPP9), and (c) use the information deriving from this activity/selectivity cliff analysis to suggest how virtual screening protocols might be improved to favor the early identification of potent and selective DPP-IV inhibitors in molecular databases (because they have not succeeded in identifying selective DPP-IV inhibitors with IC₅₀ ≤ 100 nM). All these goals are achieved with the help of available homology models for DPP8 and DPP9 and an analysis of the structure-activity studies used to develop the noncovalent inhibitors that form part of some of the complexes with human DPP-IV available at the PDB.

Design, synthesis and anti-diabetic activity of triazolotriazine derivatives as dipeptidyl peptidase-4 (DPP-4) inhibitors

Type 2 diabetes mellitus (T2DM) is one of the major global metabolic disorders characterized by insulin resistance and chronic hyperglycemia. Inhibition of the enzyme, dipeptidyl peptidase-4 (DPP-4) has been proved as successful and safe therapy for the treatment of T2DM since last decade. In order to design novel DPP-4 inhibitors, various in silico studies such as 3D-QSAR, pharmacophore modeling and virtual screening were performed and on the basis of the combined results of them, total 50 triazolo[5,1-c][1,2,4]triazine derivatives were designed and mapped on the best pharmacophore model. From this, best 25 derivatives were docked onto the active site of DPP-4 enzyme and in silico ADMET properties were also predicted. Finally, top 17 derivatives were synthesized and characterized using FT-IR, Mass, ¹H NMR and ¹³C NMR spectroscopy. Purity of compounds was checked using HPLC. These derivatives were then evaluated for in vitro DPP-4 inhibition. The most promising compound 15q showed 28.05μM DPP-4 IC₅₀ with 8-10-fold selectivity over DPP-8 and DPP-9 so selected for further in vivo anti-diabetic evaluation. During OGTT in normal C57BL/6J mice, compound 15q reduced blood glucose excursion in a dose-dependent manner. Chronic treatment for 28days with compound 15q improved the serum glucose levels in type 2 diabetic Sprague Dawley rats wherein diabetes was induced by high fat diet and low dose streptozotocin. This suggested that compound 15q is a moderately potent and selective hit molecule which can be further optimized structurally to increase the efficacy and overall pharmacological profile as DPP-4 inhibitor.