Design novel dual agonists for treating type-2 diabetes by targeting peroxisome proliferator-activated receptors with core hopping approach

Structural insights of dipeptidyl peptidase-IV inhibitors through molecular dynamics-guided receptor-dependent 4D-QSAR studies

Dipeptidyl peptidase-IV (DPP-IV) inhibitors are promising antidiabetic agents. Currently, several DPP-IV inhibitors have been approved for therapeutic use in diabetes mellitus. Receptor-dependent 4D-QSAR is comparatively a new approach which uses molecular dynamics simulations to generate conformational ensemble profiles of compounds representing a dynamic state of compounds at a target's binding site. This work describes a receptor-dependent 4D-QSAR study on triazolopiperazine derivatives. QSARINS multiple linear regression method was adopted to generate 4D-QSAR models. A model with 9 variables was found to have better predictive accuracy with [Formula: see text], [Formula: see text] (leave-one-out) = 0.592 and [Formula: see text] predicted = 0.597. The location of these 9 variables at the binding site of DPP-IV revealed the importance of the residues Val711, Tyr662, Tyr666, Val202, Asp200 and Thr199 in making critical interactions with DPP-IV inhibitors. The study of these critical interactions revealed the structural features required in DPP-IV inhibitors. Thus, in this study the importance of a halogen substituent on a phenyl ring, the extent of substitution on the triazolopiperazine ring, the presence of an ionizable amino group and the presence of a hydrophobic substituent that can bind deeper in binding pocket of DPP-IV were revealed.

Small molecular floribundiquinone B derived from medicinal plants inhibits acetylcholinesterase activity

Being a neurodegenerative disorder, Alzheimer's disease (AD) is the one of the most terrible diseases. And acetylcholinesterase (AChE) is considered as an important target for treating AD. Acetylcholinesterase inhibitors (AChEI) are considered to be one of the effective drugs for the treatment of AD. The aim of this study is to find a novel potential AChEI as a drug for the treatment of AD. In this study, instead of using the synthetic compounds, we used those extracted from plants to investigate the interaction between floribundiquinone B (FB) and AChE by means of both the experimental approach such as fluorescence spectra, ultraviolet-visible (UV-vis) absorption spectrometry, circular dichroism (CD) and the theoretical approaches such as molecular docking. The findings reported here have provided many useful clues and hints for designing more effective and less toxic drugs against Alzheimer's disease.

Personalized glucose-insulin model based on signal analysis

Glucose plasma measurements for diabetes patients are generally presented as a glucose concentration-time profile with 15-60min time scale intervals. This limited resolution obscures detailed dynamic events of glucose appearance and metabolism. Measurement intervals of 15min or more could contribute to imperfections in present diabetes treatment. High resolution data from mixed meal tolerance tests (MMTT) for 24 type 1 and type 2 diabetes patients were used in our present modeling. We introduce a model based on the physiological properties of transport, storage and utilization. This logistic approach follows the principles of electrical network analysis and signal processing theory. The method mimics the physiological equivalent of the glucose homeostasis comprising the meal ingestion, absorption via the gastrointestinal tract (GIT) to the endocrine nexus between the liver, pancreatic alpha and beta cells. This model demystifies the metabolic 'black box' by enabling in silico simulations and fitting of individual responses to clinical data. Five-minute intervals MMTT data measured from diabetic subjects result in two independent model parameters that characterize the complete glucose system response at a personalized level. From the individual data measurements, we obtain a model which can be analyzed with a standard electrical network simulator for diagnostics and treatment optimization. The insulin dosing time scale can be accurately adjusted to match the individual requirements of characterized diabetic patients without the physical burden of treatment.

Peroxisome proliferator-activated receptor α ligands and modulators from dietary compounds: Types, screening methods and functions

Peroxisome proliferator-activated receptor α (PPARα) plays a key role in lipid metabolism and glucose homeostasis and a crucial role in the prevention and treatment of metabolic diseases. Natural dietary compounds, including nutrients and phytochemicals, are PPARα ligands or modulators. High-throughput screening assays have been developed to screen for PPARα ligands and modulators in our diet. In the present review, we discuss recent advances in our knowledge of PPARα, including its structure, function, and ligand and modulator screening assays, and summarize the different types of dietary PPARα ligands and modulators.

Molecular dynamics and protein interaction studies of lipopeptide (Iturin A) on α- amylase of Spodoptera litura

The small mottled willow moth (Spodoptera litura) is one of the best-known agricultural pest insects. To understand the insecticidal activity, we have selected iturin A compound produced by Bacillus amyloliquefaciens RHNK22 which showed the strongest and most common inhibitory effect on the Spodoptera litura protein. In this work we have identified the action of iturin A on α- amylase is a major digestive enzyme of Spodoptera litura using docking studies. A 3D model of α- amylase from Spodoptera litura was generated using 2HPH as a template with the help of Modeller7v7. With the aid of the molecular mechanics and molecular dynamics methods, the final model is obtained and is further checked by Procheck and Verify 3D graph programs, which showed that the final refined model is reliable. With this model, a adjustable docking study was performed with iturin A using GOLD software. The results indicated that ARG 18, THR15, LEU42 in α- amylase are important determinant residues in binding as they have strong hydrogen bonding interactions with iturin A. These hydrogen binding interactions play an important role for the stability of the complex.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Identification of Damaging nsSNVs in HumanERCC2 Gene

The hERCC2 gene is an important DNA repair molecule for initiating Cutaneous melanoma (CM). Therefore, it is advisable to study the possible functional SNVs in hERCC2. To achieve this goal, we collected total 2, 253 SNVs in hERCC2from the EMBL website, of which 303 are non-synonymous single nucleotide variants (nsSNVs). Then, SIFT and PolyPhen were used to predict the damaging nsSNVs, and four nsSNVs (rs368866996, rs377739017, rs370819591, and rs121913022) were suggested to be damaging mutations. Since I-Mutant2.0 showed a decrease in stability for the mutants containing each of the four nsSNVs, a 3D protein structure was modeled. Based on the comparison of the energy after minimization, RMSD and stabilizing residues between the native and mutant proteins' structure, rs121913022 was proposed to be the most damaging variant among the nsSNVs in hERCC2 gene by decreasing the stability of protein. The mutant G713R of hERCC2 protein caused by rs121913022 was found to have less expression level than native hERCC2 protein in melanoma cells. These results suggest that rs121913022 may have potentially important clinical and drug target implications.

Identification of CD4+ T-cell epitope and investigation of HLA distribution for the immunogenic proteins of Burkholderia pseudomallei using in silico approaches - A key vaccine development strategy for melioidosis

Melioidosis is a serious infectious diseases affecting multi-organ system in humans with high mortality rate. The disease is caused by the bacterium, Burkholderia pseudomallei and it is intrinsically resistant to many antibiotics. Thus, there is an urgent need for protective vaccine against B. pseudomallei; which may reduce morbidity and mortality in endemic areas. The identification of peptides that bind to major histocompatibility complex II class helps in understanding the nature of immune response and identifying T-cell epitopes for the design of new vaccines. Previous studies indicate that, ompA, bipB, fliC and groEL proteins of B. pseudomallei stimulate CD4+ T-cell immune response and act as protective immunogens. However, the data for CD4+ T-cell epitopes of these immunogenic proteins are very limited. Hence, in this present study we attempted to identify CD4+ T-cell epitopes in B. pseudomallei immunogenic proteins using in silico approaches. We did population coverage analysis for these identified epitopic core sequences to identify individuals in endemic areas expected to respond to a given set of these epitopes on the basis of HLA genotype frequencies. We observed that eight epitopic core sequences, two from each immunogenic protein, were associated with the maximum number of HLA-DR binding alleles. These eight peptides are found to be immunogenic in more than 90% of population in endemic areas considered. Thus, these eight peptides containing epitopic core sequences may act as probable vaccine candidates and they may be considered for the development of epitope-based vaccines for melioidosis.

Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations

Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or equivalently, glucose-binding pockets. In this work, we combine molecular dynamics simulations of HSA and the state-of-art machine learning method Support Vector Machine (SVM) to predict glucose-binding pockets in HSA. SVM uses the three dimensional arrangement of atoms and their chemical properties to predict glucose-binding ability of a pocket. Feature selection reveals that the arrangement of atoms and their chemical properties within the first 4Å from the centroid of the pocket play an important role in the binding of glucose. With a 10-fold cross validation accuracy of 84 percent, our SVM model reveals seven new potential glucose-binding sites in HSA of which two are exposed only during the dynamics of HSA. The predictions are further corroborated using docking studies. These findings can complement studies directed towards the development of HSA as an alternate biomarker for glycemic monitoring.

Folding and binding energy of a calmodulin-binding cell antiproliferative peptide

We carry out a computational study of a calmodulin-binding peptide shown to be effective in reducing cell proliferation. We find several folded states for two short variants of different length of the peptide and determine the location of the binding site on calmodulin, the binding free energy for the different conformers and structural details that play a role in optimal binding. Binding to a hydrophobic pocket in calmodulin occurs via an anchoring phenylalanine residue of the natively disordered peptide, and is enhanced when a neighbouring hydrophobic residue acts as a co-anchor. The shorter sequence possesses better binding to calmodulin, which is encouraging in terms of the development of non-peptide analogues as therapeutic agents.

Role of peroxisome proliferator-activated receptors gene polymorphisms in type 2 diabetes and metabolic syndrome

Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are the serious public health problems worldwide. Moreover, it is estimated that MetS patients have about five-fold greater risk of the T2DM development compared with people without the syndrome. Peroxisome proliferator-activated receptors are a subgroup of the nuclear hormone receptor superfamily of ligand-activated transcription factors which play an important role in the pathogenesis of MetS and T2DM. All three members of the peroxisome proliferator-activated receptor (PPAR) nuclear receptor subfamily, PPARα, PPARβ/δ and PPARγ are critical in regulating insulin sensitivity, adipogenesis, lipid metabolism, and blood pressure. Recently, more and more studies indicated that the gene polymorphism of PPARs, such as Leu¹⁶²Val and Val²²⁷Ala of PPARα, +294T > C of PPARβ/δ, Pro¹²Ala and C1431T of PPARγ, are significantly associated with the onset and progressing of MetS and T2DM in different population worldwide. Furthermore, a large body of evidence demonstrated that the glucose metabolism and lipid metabolism were influenced by gene-gene interaction among PPARs genes. However, given the complexity pathogenesis of metabolic disease, it is unlikely that genetic variation of a single locus would provide an adequate explanation of inter-individual differences which results in diverse clinical syndromes. Thus, gene-gene interactions and gene-environment interactions associated with T2DM and MetS need future comprehensive studies.

In vitro evaluation of dual agonists for PPARγ/β from the flower of Edgeworthia gardneri (wall.) Meisn

ETHNOPHARMACOLOGICAL RELEVANCE

In Tibet, the flower of Edgeworthia gardneri (Wall.) Meisn., locally named "Lvluohua, [symbols: see text]", has been traditionally used to treat diabetes mellitus for many years.

AIM OF THIS STUDY

To evaluate the activity of dual agonists for PPARγ/β from the flower of E.gardneri in vitro.

MATERIALS AND METHODS

HeLa cells were transiently co-transfected with the re-constructed plasmids of pBIND-PPARγ-LBD or pBIND-PPARβ-LBD and rL4.35. The activities of crude extracts, secondary fractions and compounds from the flower of E.gardneri were evaluated with the transfected cells. Rosiglitazone (at 0.5 μg/mL) and L-165041 (at 0.5 μg/mL) were used as the positive controls for PPARγ and PPARβ respectively.

RESULTS

The results demonstrated that n-hexane, ethyl acetate and n-butanol extracts from the flower of E.gardneri were able to significantly activate PPARγ and PPARβ respectively, and the activity of ethyl acetate extract was much better. We further observed that, among the 11 secondary fractions of ethyl acetate extract, the fr. 9 could activate PPARγ and PPARβ significantly. Moreover, umbelliferone (from fr.9) and pentadecanoic acid could activate PPARγ and PPARβ at the same time.

CONCLUSIONS

The extracts from the flower of E.gardneri could significantly activate PPARγ and PPARβ. Besides, umbelliferone and pentadecanoic acid isolated from the flower of E.gardneri were the new agonists for PPARγ and PPARβ.

Identification of novel multitargeted PPARα/γ/δ pan agonists by core hopping of rosiglitazone

The thiazolidinedione class peroxisome proliferator-activated receptor gamma (PPARγ) agonists are restricted in clinical use as antidiabetic agents because of side effects such as edema, weight gain, and heart failure. The single and selective agonism of PPARγ is the main cause of these side effects. Multitargeted PPARα/γ/δ pan agonist development is the hot topic in the antidiabetic drug research field. In order to identify PPARα/γ/δ pan agonists, a compound database was established by core hopping of rosiglitazone, which was then docked into a PPARα/γ/δ active site to screen out a number of candidate compounds with a higher docking score and better interaction with the active site. Further, absorption, distribution, metabolism, excretion, and toxicity prediction was done to give eight compounds. Molecular dynamics simulation of the representative Cpd#1 showed more favorable binding conformation for PPARs receptor than the original ligand. Cpd#1 could act as a PPARα/γ/δ pan agonist for novel antidiabetic drug research.

Bioassay directed isolation and biological evaluation of compounds isolated from Rubus fairholmianus Gard

The in vitro and in silico analysis of Rubus fairholmianus acetone extract for antioxidant, antiproliferative, and anti-inflammatory activity led to the isolation of six compounds. Amongst all the six isolated compounds tested, 1-(2-hydroxyphenyl)-4-methylpentan-1-one (compound 1) and 2-[(3-methylbutoxy) carbonyl] benzoic acid (compound 2) were found to be more active in inhibiting BRCA and COX target proteins, which also showed the better results for DPPH and ABTS radical scavenging assays. The promising results of this investigation emphasize the importance of using R. fairholmianus in the treatment of radical generated disorders mainly cancer and other inflammatory diseases.

Sequence-specific flexibility organization of splicing flanking sequence and prediction of splice sites in the human genome

More and more reported results of nucleosome positioning and histone modifications showed that DNA structure play a well-established role in splicing. In this study, a set of DNA geometric flexibility parameters originated from molecular dynamics (MD) simulations were introduced to discuss the structure organization around splice sites at the DNA level. The obtained profiles of specific flexibility/stiffness around splice sites indicated that the DNA physical-geometry deformation could be used as an alternative way to describe the splicing junction region. In combination with structural flexibility as discriminatory parameter, we developed a hybrid computational model for predicting potential splicing sites. And the better prediction performance was achieved when the benchmark dataset evaluated. Our results showed that the mechanical deformability character of a splice junction is closely correlated with both the splice site strength and structural information in its flanking sequences.

iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking

Nuclear receptors (NRs) are closely associated with various major diseases such as cancer, diabetes, inflammatory disease, and osteoporosis. Therefore, NRs have become a frequent target for drug development. During the process of developing drugs against these diseases by targeting NRs, we are often facing a problem: Given a NR and chemical compound, can we identify whether they are really in interaction with each other in a cell? To address this problem, a predictor called “iNR-Drug” was developed. In the predictor, the drug compound concerned was formulated by a 256-D (dimensional) vector derived from its molecular fingerprint, and the NR by a 500-D vector formed by incorporating its sequential evolution information and physicochemical features into the general form of pseudo amino acid composition, and the prediction engine was operated by the SVM (support vector machine) algorithm. Compared with the existing prediction methods in this area, iNR-Drug not only can yield a higher success rate, but is also featured by a user-friendly web-server established at http://www.jci-bioinfo.cn/iNR-Drug/, which is particularly useful for most experimental scientists to obtain their desired data in a timely manner. It is anticipated that the iNR-Drug server may become a useful high throughput tool for both basic research and drug development, and that the current approach may be easily extended to study the interactions of drug with other targets as well.

Molecular docking of Glyceroneogenesis pathway intermediates with Peroxisome Proliferator- Activated Receptor-Alpha (PPAR-α)

Peroxisome proliferator-activated receptor alpha (PPAR-α) belongs to the nuclear receptor superfamily of proteins. It is one of the principle regulators of metabolism and lipid homeostasis whose malfunction leads to complications including obesity and type 2 diabetes. In the adipose tissue, glyceroneogenesis is a unique pathway through which pyruvate is converted into glycerol-3- phosphate (G3P) in a multistep process. Previous findings demonstrated that glyceroneogenesis regulates triacylglycerol synthesis and adipogenesis. This led us to hypothesize that one of the pathway intermediate is physiologically relevant PPAR-α ligand. In the present study using in silico docking, we proved that glycerate, dihydroxy acetone phosphate, glyceraldehyde-3-phosphate, and G3P are key glyceroneogenesis pathway intermediates which bind to PPAR-α. They bind PPAR-α with comparable binding energy and docking score to that of (2s)-2-ethoxy-3-[4-(2-{4-[(methylsulfonyl)oxy]phenyl}ethoxy)phenyl]propanoic acid(AZ-2), a synthetic high affinity ligand of PPAR-α. These intermediates could be studied further as potential physiologically relevant activators of PPAR-α in vitro and in vivo.

Design, synthesis, biological activity and molecular dynamics studies of specific protein tyrosine phosphatase 1B inhibitors over SHP-2

Over expressing in PTPN1 (encoding Protein tyrosine phosphatase 1B, PTP1B), a protein tyrosine phosphatase (PTP) that plays an overall positive role in insulin signaling, is linked to the pathogenesis of diabetes and obesity. The relationship between PTP1B and human diseases exhibits PTP1B as the target to treat these diseases. In this article, small weight molecules of the imidazolidine series were screened from databases and optimized on silicon as the inhibitors of PTP1B based on the steric conformation and electronic configuration of thiazolidinedione (TZD) compounds. The top three candidates were tested using an in vitro biological assay after synthesis. Finally, we report a novel inhibitor, Compound 13, that specifically inhibits PTP1B over the closely related phosphatase Src homology 2 (SH2) domain-containing phosphatase 2 (SHP-2) at 80 μM. Its IC₅₀ values are reported in this paper as well. This compound was further verified by computer analysis for its ability to combine the catalytic domains of PTP1B and SHP-2 by molecular dynamics (MD) simulations.

Find novel dual-agonist drugs for treating type 2 diabetes by means of cheminformatics

The high prevalence of type 2 diabetes mellitus in the world as well as the increasing reports about the adverse side effects of the existing diabetes treatment drugs have made developing new and effective drugs against the disease a very high priority. In this study, we report ten novel compounds found by targeting peroxisome proliferator-activated receptors (PPARs) using virtual screening and core hopping approaches. PPARs have drawn increasing attention for developing novel drugs to treat diabetes due to their unique functions in regulating glucose, lipid, and cholesterol metabolism. The reported compounds are featured with dual functions, and hence belong to the category of dual agonists. Compared with the single PPAR agonists, the dual PPAR agonists, formed by combining the lipid benefit of PPARα agonists (such as fibrates) and the glycemic advantages of the PPARγ agonists (such as thiazolidinediones), are much more powerful in treating diabetes because they can enhance metabolic effects while minimizing the side effects. This was observed in the studies on molecular dynamics simulations, as well as on absorption, distribution, metabolism, and excretion, that these novel dual agonists not only possessed the same function as ragaglitazar (an investigational drug developed by Novo Nordisk for treating type 2 diabetes) did in activating PPARα and PPARγ, but they also had more favorable conformation for binding to the two receptors. Moreover, the residues involved in forming the binding pockets of PPARα and PPARγ among the top ten compounds are explicitly presented, and this will be very useful for the in-depth conduction of mutagenesis experiments. It is anticipated that the ten compounds may become potential drug candidates, or at the very least, the findings reported here may stimulate new strategies or provide useful insights for designing new and more powerful dual-agonist drugs for treating type 2 diabetes.

SAR and Computer-Aided Drug Design Approaches in the Discovery of Peroxisome Proliferator-Activated Receptor γ Activators: A Perspective

Activators of PPARγ, Troglitazone (TGZ), Rosiglitazone (RGZ), and Pioglitazone (PGZ) were introduced for treatment of Type 2 diabetes, but TGZ and RGZ have been withdrawn from the market along with other promising leads due cardiovascular side effects and hepatotoxicity. However, the continuously improving understanding of the structure/function of PPARγ and its interactions with potential ligands maintain the importance of PPARγ as an antidiabetic target. Extensive structure activity relationship (SAR) studies have thus been performed on a variety of structural scaffolds by various research groups. Computer-aided drug discovery (CADD) approaches have also played a vital role in the search and optimization of potential lead compounds. This paper focuses on these approaches adopted for the discovery of PPARγ ligands for the treatment of Type 2 diabetes. Key concepts employed during the discovery phase, classification based on agonistic character, applications of various QSAR, pharmacophore mapping, virtual screening, molecular docking, and molecular dynamics studies are highlighted. Molecular level analysis of the dynamic nature of ligand-receptor interaction is presented for the future design of ligands with better potency and safety profiles. Recently identified mechanism of inhibition of phosphorylation of PPARγ at SER273 by ligands is reviewed as a new strategy to identify novel drug candidates.