Rational design of thiazolidine-4-one-gallic acid hybrid derivatives as selective partial PPARγ modulators: an in-silico approach for type 2 diabetes treatment

Type 2 diabetes mellitus is a bipolar metabolic disorder characterized by abnormalities in insulin production from β-cells and insulin resistance. Thiazolidinediones are potent anti-diabetic agents that act through the modulation of the peroxisome proliferator-activated receptor γ (PPARγ), a nuclear receptor. However, their full agonistic activity leads to severe side effects by stabilizing Helix12 through strong hydrogen bonding with the TYR473 residue. Partial and selective PPARγ modulators (GW0072, GQ16, VSP-51, MRL-20, MBX-213, INT131) have demonstrated superior results compared to full agonists without causing adverse effects, as reported in existing data. To address this uncertainty and advance therapeutic options, we identified and designed a novel class of compounds (A1-A23) based on a hybrid structure combining phenolic and Thiazolidine-4-one's moieties. Our rational drug design strategy incorporated structural-activity relationship principle, and validated the docking studies through calculated the root mean square deviation. Additionally, we conducted molecular docking, binding energy, molecular dynamics simulations, and post-molecular dynamics calculations to evaluate the dynamics behavior between the ligands and protein. The selected ligands demonstrated highly favorable docking scores and binding energies, comparable to the co-crystal (rosiglitazone) such as A12 (-13.9 kcal/mol and -86.2 kcal/mol), A1 (-11.1 kcal/mol and -79.5 kcal/mol), A13 (-11.3 kcal/mol and -91.4 kcal/mol), and the co-crystal itself (-9.8 kcal/mol and -76 kcal/mol), respectively. Finally, the MD revealed that, the selected ligands were equally contributed for stabilization of Helix12 and β-sheets. It was concluded, the designed ligands (A12, A1, and A13) exhibited weaker hydrogen-bond interactions with specific residue TYR473 which partially modulated the PPARγ protein.Communicated by Ramaswamy H. Sarma.

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

Topomer-CoMFA proposed as a tool to construct dual EGFR/HER-2 models

Protein kinases (in this case, HER-2 and EGFR) are involved in cancer-related diseases. Some reports have shown unique CoMFA models using the sum of activities expressed as pIC₅₀ (-log IC₅₀), as the classical CoMFA technique would not be the best strategy to construct models for multitarget therapy considering that the molecular alignment will not be the same for different targets. An alternative for this problem is the use of Topomer-CoMFA, a variation of CoMFA, which does not require the alignment step in the generation of 3D models. In this study, we propose the combined use of the sum of activities and Topomer-CoMFA for the construction of a unique dual 3D model considering the inhibitory activities against EGFR and HER-2. For this, 88 compounds from the literature were divided into two groups: training (71) and test (17) sets. The biological activity of each compound, expressed as IC₅₀ for EGFR and HER-2, was transformed into pIC₅₀, summed, and used as the dependent variable in the Topomer-CoMFA analyses. The obtained model was considered statistically robust in the prediction of the dual activity of new compounds. Finally, based on the obtained model, we proposed structural modifications to some of the compounds used to improve the biological data. From the 3D model, we suggested new derivative compounds with improved biological activity for both targets. Therefore, the combination of the techniques proposed in this study proves to be a good strategy to construct better statistical models that can predict biological activities in multitarget systems.

Sulfur-containing therapeutics in the treatment of Alzheimer's disease

Sulfur is widely existent in natural products and synthetic organic compounds as organosulfur, which are often associated with a multitude of biological activities. OBenzothiazole, in which benzene ring is fused to the 4,5-positions of the thiazolerganosulfur compounds continue to garner increasing amounts of attention in the field of medicinal chemistry, especially in the development of therapeutic agents for Alzheimer's disease (AD). AD is a fatal neurodegenerative disease and the primary cause of age-related dementia posing severe societal and economic burdens. Unfortunately, there is no cure for AD. A lot of research has been conducted on sulfur-containing compounds in the context of AD due to their innate antioxidant potential and some are currently being evaluated in clinical trials. In this review, we have described emerging trends in the field, particularly the concept of multi-targeting and formulation of disease-modifying strategies. SAR, pharmacological targets, in vitro/vivo ADMET, efficacy in AD animal models, and applications in clinical trials of such sulfur compounds have also been discussed. This article provides a comprehensive review of organosulfur-based AD therapeutic agents and provides insights into their future development.

Benchmarking 2D/3D/MD-QSAR Models for Imatinib Derivatives: How Far Can We Predict?

Imatinib, a 2-phenylaminopyridine-based BCR-ABL tyrosine kinase inhibitor, is a highly effective drug for treating Chronic Myeloid Leukemia (CML). However, cases of drug resistance are constantly emerging due to various mutations in the ABL kinase domain; thus, it is crucial to identify novel bioactive analogues. Reliable QSAR models and molecular docking protocols have been shown to facilitate the discovery of new compounds from chemical libraries prior to experimental testing. However, as the vast majority of QSAR models strictly relies on 2D descriptors, the rise of 3D descriptors directly computed from molecular dynamics simulations offers new opportunities to potentially augment the reliability of QSAR models. Herein, we employed molecular docking and molecular dynamics on a large series of Imatinib derivatives and developed an ensemble of QSAR models relying on deep neural nets (DNN) and hybrid sets of 2D/3D/MD descriptors in order to predict the binding affinity and inhibition potencies of those compounds. Through rigorous validation tests, we showed that our DNN regression models achieved excellent external prediction performances for the pKi data set (n = 555, R² ≥ 0.71. and MAE ≤ 0.85), and the pIC₅₀ data set (n = 306, R² ≥ 0.54. and MAE ≤ 0.71) with strict validation protocols based on external test sets and 10-fold native and nested cross validations. Interestingly, the best DNN and random forest models performed similarly across all descriptor sets. In fact, for this particular series of compounds, our external test results suggest that incorporating additional 3D protein-ligand binding site fingerprint, descriptors, or even MD time-series descriptors did not significantly improve the overall R² but lowered the MAE of DNN QSAR models. Those augmented models could still help in identifying and understanding the key dynamic protein-ligand interactions to be optimized for further molecular design.

Critical Insight into the Design of PPAR-γ Agonists by Virtual Screening Techniques

BACKGROUND

Design of novel PPAR-γ modulators with better binding efficiency and fewer side effects to treat type 2 diabetes is still a challenge for medicinal chemists. Cost and time efficient computational methods have presently become an integral part of research in nuclear receptors and their ligands, enabling hit to lead identification and lead optimization. This review will focus on cutting-edge technologies used in most recent studies on the design of PPAR- γ agonists and will discuss the chemistry of few molecules which emerged successful.

METHODS

Literature review was carried out in google scholar using customized search from 2011- 2017. Computer-aided design methods presented in this article were used as search terms to retrieve corresponding literature.

RESULTS

Virtual screening of natural product libraries is an effective strategy to harness nature as the source of ligands for PPARs. Rigid and induced fit docking and core hopping approach in docking are rapid screening methods to predict the PPAR- γ and PPAR-α/ γ dual agonistic activity. Onedimensional drug profile matching is one of the recent virtual screening methods by which an antiprotozoal drug, Nitazoxanide was identified as a PPAR- γ agonist.

CONCLUSION

It is concluded that to achieve a convincing and reliable design of PPAR-γ agonist by virtual screening techniques, customized workflow comprising of appropriate models is essential in which methods may be applied either sequentially or simultaneously.

Screening of Some Sulfonamide and Sulfonylurea Derivatives as Anti-Alzheimer’s Agents Targeting BACE1 and PPARγ

In the last few decades, Alzheimer’s disease (AD) has emerged as a serious global problem, and it has been considered as the most common type of dementia. PPARγ and beta-secretase 1 (BACE1) are considered as potential targets for Alzheimer’s disease management. In the same time, sulfonylureas and sulfonamides have been confirmed to have PPARγ agonistic activity. Aiming to obtain new anti-AD agents, thirty-five compounds of sulfonamide and sulfonylurea derivatives having the same essential pharmacophoric features of the reported PPARγ agonists have been subjected to virtual screening. Docking studies revealed that five compounds (1, 2, 3, 4, and 5) have promising affinities to PPARγ. They were also docked into the binding site of BACE1. In addition, ADMET and physicochemical properties of these compounds were considered. Additionally, these compounds were further evaluated against BACE1 and PPARγ. Compound 2 showed IC50 value of 1.64 μM against BACE1 and EC50 value of 0.289 μM against PPARγ.

The Journey of Thiazolidinediones as Modulators of PPARs for the Management of Diabetes: A Current Perspective

Peroxisome Proliferator-Activated Receptors (PPARs) also known as glitazone receptors are a family of receptors that regulate the expression of genes and have an essential role in carbohydrate, lipid and protein metabolism apart from other functions. PPARs come in 3 sub-types: PPAR-α, PPAR-β/δ and PPAR-γ - with PPAR-γ having 2 isoforms - γ1 and γ2. Upon activation, the PPARs regulate the transcription of various genes involved in lipid and glucose metabolism, adipocyte differentiation, increasing insulin sensitivity, prevention of oxidative stress and to a certain extent, modulation of immune responses via macrophages that have been implicated in the pathogenesis of insulin resistance. Hence, PPARs are an attractive molecular target for designing new anti-diabetic drugs. This has led to a boost in the research efforts directed towards designing of PPAR ligands - particularly ones that can selectively and specifically activate one or more of the PPAR subtypes. Though, PPAR- γ full agonists such as Thiazolidinediones (TZDs) are well established agents for dyslipidemia and type 2 diabetes mellitus (T2D), the side effect profile associated with TZDs has potentiated an imminent need to come up with newer agents that act through this pathway. Several newer derivatives having TZD scaffold have been designed using structure based drug designing technique and computational tools and tested for their PPAR binding affinity and efficacy in combating T2D and some have shown promising activities. This review would focus on the role of PPARs in the management of T2D; recently reported TZD derivatives which acted as agonists of PPAR- γ and its subtypes and are potentially useful in the new drug discovery for the disease.

Identification and structural insight of an effective PPARγ modulator with improved therapeutic index for anti-diabetic drug discovery

Peroxisome proliferator-activated receptor γ (PPARγ) is a key regulator of glucose homeostasis and lipid metabolism, and an important target for the development of modern anti-diabetic drugs. However, current PPARγ-targeting anti-diabetic drugs such as classical thiazolidinediones (TZDs) are associated with undesirable side effects. To address this concern, we here describe the structure-based design, synthesis, identification and detailed in vitro and in vivo characterization of a novel, decanoic acid (DA)-based and selective PPARγ modulator (SPPARγM), VSP-77, especially (S)-VSP-77, as the potential "hit" for the development of improved and safer anti-diabetic therapeutics. We have also determined the co-crystal structure of the PPARγ ligand-binding domain (LBD) in complex with two molecules of (S)-VSP-77, which reveal a previously undisclosed allosteric binding mode. Overall, these findings not only demonstrate the therapeutic advantage of (S)-VSP-77 over current TZD drugs and representative partial agonist INT131, but also provide a rational basis for the development of future SPPARγMs as safe and highly efficacious anti-diabetic drugs.

Design, synthesis, molecular modeling and anti-hyperglycemic evaluation of phthalimide-sulfonylurea hybrids as PPARγ and SUR agonists

New series of phthalimide-sulfonylurea hybrids were prepared and examined for their in vivo anti-hyperglycemic activities in STZ-induced hyperglycemic rats using glibenclamide as a reference drug. Compounds 6_c, 6_d, 6_g, 6_h, 6_j and 6_k induced significant reduction in the blood glucose levels of diabetic rats ranging from 24.43 to 21.43%. Moreover, molecular docking and pharmacophore approaches were carried out to examine binding modes and fit values of the prepared compounds against PPARγ and SUR, respectively. Compounds 6_c, 6_d, 6_j and 6_m exhibited the highest binding free energies against PPARγ. Compounds 6_c, 6_j, 6_k, 6_l, and 6_n showed the highest fit values against the generated pharmacophore model. Also, QSAR technique was carried out to estimate the proposed PPARγ binding affinities and insulin-secreting abilities. The synthesized compounds showed promising estimated activities. In-silico ADMET studies were performed to investigate pharmacokinetics of the synthesized compounds. They showed considerable human intestinal absorption with low BBB penetration.

Developing Hispolon-based novel anticancer therapeutics against human (NF-κβ) using in silico approach of modelling, docking and protein dynamics

Hispolon is a polyphenolic compound derived from black hoof mushroom (Phellinus linteus) or shaggy bracket mushroom (Inonotus hispidus) which induces the inhibition of cancer-promoting nuclear factor-kappa beta (NF-κβ) complex. To develop more potent lead molecules with enhanced anticancer efficiency, the mechanism of hispolon-mediated nuclear factor-κβ inhibition has been investigated by molecular modelling and docking. Ten derivatives of hispolon (DRG1-10) have been developed by pharmacophore-based design with a view to enhance the anticancer efficacy. Hispolon and its derivatives were further screened for different pharmacological parameters like binding free energy, drug likeliness, absorption-digestion-metabolism-excretion (ADME), permeability, mutagenicity, toxicity and inhibitory concentration 50 (IC50) to find a potent lead molecule. Based on pharmacological validation, comparative molecular dynamics (MD) simulations have been performed for three lead molecules: Hispolon, DRG2 and DRG7 complexed with human NF-κβ up to 50 ns. By analysing different factors like root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA) and principal component analysis (PCA), Gibb's free energy plots DRG2 have more binding efficiency compared to hispolon and DRG7. In RMSD plot, hispolon-bound NF-κβ has the most deviation within a range between 0.125 and 0.45 nm, and DRG2-bound complex showed the range between 0.125 and 0.25 nm. The residues of NF-κβ responsible for hydrophobic interactions with ligand, e.g. Met469, Leu522 and Cys533, have the lowest fluctuation values in DRG2-bound complex. The average Rg fluctuation for DRG2-bound NF-κβ has been recorded under 2.025 nm for most of the simulation time which is much less compared to hispolon and DRG7. Gibb's free energy plots also define the highest stability of DRG2-bound NF-κβ. Communicated by Ramaswamy H. Sarma.

Structural Basis for the Enhanced Anti-Diabetic Efficacy of Lobeglitazone on PPARγ

Peroxisome proliferator-activated receptor γ (PPARγ) is a member of the nuclear receptor superfamily. It functions as a ligand-activated transcription factor and plays important roles in the regulation of adipocyte differentiation, insulin resistance, and inflammation. Here, we report the crystal structures of PPARγ in complex with lobeglitazone, a novel PPARγ agonist, and with rosiglitazone for comparison. The thiazolidinedione (TZD) moiety of lobeglitazone occupies the canonical ligand-binding pocket near the activation function-2 (AF-2) helix (i.e., helix H12) in ligand-binding domain as the TZD moiety of rosiglitazone does. However, the elongated p-methoxyphenol moiety of lobeglitazone interacts with the hydrophobic pocket near the alternate binding site of PPARγ. The extended interaction of lobeglitazone with the hydrophobic pocket enhances its binding affinity and could affect the cyclin-dependent kinase 5 (Cdk5)-mediated phosphorylation of PPARγ at Ser245 (in PPARγ1 numbering; Ser273 in PPARγ2 numbering). Lobeglitazone inhibited the phosphorylation of PPARγ at Ser245 in a dose-dependent manner and exhibited a better inhibitory effect on Ser245 phosphorylation than rosiglitazone did. Our study provides new structural insights into the PPARγ regulation by TZD drugs and could be useful for the discovery of new PPARγ ligands as an anti-diabetic drug, minimizing known side effects.

Design, synthesis, molecular modeling and anti-hyperglycemic evaluation of novel quinoxaline derivatives as potential PPARγ and SUR agonists

In our effort to develop potent anti-hyperglycemic agents with potential agonistic activities toward PPARγ and SUR, three novel series of quinoxaline derivatives bearing sulfonylurea or sulfonylthiourea moieties with different linkers were designed and synthesized. Some of the newly synthesized compounds were evaluated in vivo for their anti-hyperglycemic activities in STZ-induced hyperglycemic rats. Compounds 15_a, 15_e, 19_b and 24_a exhibited the highest anti-hyperglycemic activities with % reduction in blood glucose level of (50.58, 43.84, 45.10 and 49.62, respectively). Additionally, eight compounds revealed potent anti-hyperglycemic activities were further evaluated in vitro for their PPARγ binding affinity and insulin-secreting ability as potential mechanisms for anti-hyperglycemic activity. Four compounds (15_a, 15_b, 15_d and 15_e) significantly bound to PPARγ with IC₅₀ values of 0.482, 0.491, 0.350 and 0.369μM, respectively. Moreover, Compounds 15_a and 15_b have demonstrated induction of insulin-secretion with EC₅₀ values of 0.92 and 0.98μM, respectively. Furthermore, molecular docking and pharmacophore generation techniques were carried out to investigate binding patterns and fit values of the designed compounds with PPARγ and SUR, respectively.

Regulatory landscape of AGE-RAGE-oxidative stress axis and its modulation by PPARγ activation in high fructose diet-induced metabolic syndrome

Background

The AGE-RAGE-oxidative stress (AROS) axis is involved in the onset and progression of metabolic syndrome induced by a high-fructose diet (HFD). PPARγ activation is known to modulate metabolic syndrome; however a systems-level investigation looking at the protective effects of PPARγ activation as related to the AROS axis has not been performed.

The aim of this work is to simultaneously characterize multiple molecular parameters within the AROS axis, using samples taken from different body fluids and tissues of a rat model of HFD-induced metabolic syndrome, in the presence or absence of a PPARγ agonist, Rosiglitazone (RGZ).

Methods

Rats were fed with 60% HFD for the first half of the treatment duration (21 days) then continued with either HFD alone or HFD plus RGZ for the second half.

Results

Rats receiving HFD alone showed metabolic syndrome manifestations including hypertension, dyslipidemia, increased glucose levels and insulin resistance, as well as abnormal kidney and inflammatory parameters. Systolic blood pressure, plasma triglyceride and glucose levels, plasma creatinine, and albuminuria were significantly improved in the presence of RGZ. The following molecular parameters of the AROS axis were significantly upregulated in our rat model: carboxymethyl lysine (CML) in urine and liver; carboxyethyl lysine (CEL) in urine; advanced glycation end products (AGEs) in plasma; receptor for advanced glycation end products (RAGE) in liver and kidney; advanced oxidation protein products (AOPP) in plasma; and 4-hydroxynonenal (HNE) in plasma, liver, and kidney. Conversely, with RGZ administration, the upregulation of AOPP and AGEs in plasma, CML and CEL in urine, RAGE in liver as well as HNE in plasma and liver was significantly counteracted/prevented.

Conclusions

Our data demonstrate (i) the systems-level regulatory landscape of HFD-induced metabolic syndrome involving multiple molecular parameters, including HNE, AGEs and their receptor RAGE, and (ii) attenuation of metabolic syndrome by PPARγ modulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12986-016-0149-z) contains supplementary material, which is available to authorized users.

Understanding PPAR-δ affinity and selectivity using hologram quantitative structure-activity modeling, molecular docking and GRID calculations

AIM

Type 2 diabetes mellitus and metabolic syndrome are two diseases related to disorders of lipid and carbohydrate metabolism and insulin resistance. Peroxisome proliferator-activated receptors (PPARs) are a class of nuclear receptors that control the metabolism of lipids/carbohydrates and are considered targets for both diseases. PPAR affinity and selectivity are critical points to design drug candidates with appropriated pharmacodynamic/kinetic profiles.

MATERIALS & METHODS

Hologram quantitative structure-activity relationships studies were conducted, as well molecular docking and molecular interaction field calculations, in order to explain affinity and selectivity of selected compounds.

RESULTS

The constructed hologram quantitative structure-activity relationship models are robust and predictive (values of q² and r²_test above 0.70).

CONCLUSION

The quantitative structure-activity relationship models and docking/GRID analyses indicated that carboxyl group of indole-sulfonamide derivatives could interact at helix-3 region, being considered important point of PPAR-δ selectivity.

Current Advances in the Biochemical and Physiological Aspects of the Treatment of Type 2 Diabetes Mellitus with Thiazolidinediones

The present review summarizes the current advances in the biochemical and physiological aspects in the treatment of type 2 diabetes mellitus (DM2) with thiazolidinediones (TZDs). DM2 is a metabolic disorder characterized by hyperglycemia, triggering the abnormal activation of physiological pathways such as glucose autooxidation, polyol's pathway, formation of advance glycation end (AGE) products, and glycolysis, leading to the overproduction of reactive oxygen species (ROS) and proinflammatory cytokines, which are responsible for the micro- and macrovascular complications of the disease. The treatment of DM2 has been directed toward the reduction of hyperglycemia using different drugs such as insulin sensitizers, as the case of TZDs, which are able to lower blood glucose levels and circulating triglycerides by binding to the nuclear peroxisome proliferator-activated receptor gamma (PPARγ) as full agonists. When TZDs interact with PPARγ, the receptor regulates the transcription of different genes involved in glucose homeostasis, insulin resistance, and adipogenesis. However, TZDs exhibit some adverse effects such as fluid retention, weight gain, hepatotoxicity, plasma-volume expansion, hemodilution, edema, bone fractures, and congestive heart failure, which limits their use in DM2 patients.

Structural and Dynamical Insight into PPARγ Antagonism: In Silico Study of the Ligand-Receptor Interactions of Non-Covalent Antagonists

The structural and dynamical properties of the peroxisome proliferator-activated receptor γ (PPARγ) nuclear receptor have been broadly studied in its agonist state but little is known about the key features required for the receptor antagonistic activity. Here we report a series of molecular dynamics (MD) simulations in combination with free energy estimation of the recently discovered class of non-covalent PPARγ antagonists. Their binding modes and dynamical behavior are described in details. Two key interactions have been detected within the cavity between helices H3, H11 and the activation helix H12, as well as with H12. The strength of the ligand-amino acid residues interactions has been analyzed in relation to the specificity of the ligand dynamical and antagonistic features. According to our results, the PPARγ activation helix does not undergo dramatic conformational changes, as seen in other nuclear receptors, but rather perturbations that occur through a significant ligand-induced reshaping of the ligand-receptor and the receptor-coactivator binding pockets. The H12 residue Tyr473 and the charge clamp residue Glu471 play a central role for the receptor transformations. Our results also demonstrate that MD can be a helpful tool for the compound phenotype characterization (full agonists, partial agonists or antagonists) when insufficient experimental data are available.

Polyyne hybrid compounds from Notopterygium incisum with peroxisome proliferator-activated receptor gamma agonistic effects

In the search for peroxisome proliferator-activated receptor gamma (PPARγ) active constituents from the roots and rhizomes of Notopterygium incisum, 11 new polyacetylene derivatives (1-11) were isolated. Their structures were elucidated by NMR and HRESIMS as new polyyne hybrid molecules of falcarindiol with sesquiterpenoid or phenylpropanoid moieties, named notoethers A-H (1-8) and notoincisols A-C (9-11), respectively. Notoincisol B (10) and notoincisol C (11) represent two new carbon skeletons. When tested for PPARγ activation in a luciferase reporter assay with HEK-293 cells, notoethers A-C (1-3), notoincisol A (9), and notoincisol B (10) showed promising agonistic activity (EC50 values of 1.7 to 2.3 μM). In addition, notoincisol A (9) exhibited inhibitory activity on NO production of stimulated RAW 264.7 macrophages.