3D-QSAR CoMFA and CoMSIA on protein tyrosine phosphatase 1B inhibitors

Protein Tyrosine Phosphatase 1B Inhibitors: A Novel Therapeutic Strategy for the Management of type 2 Diabetes Mellitus

Diabetes is one of the most common endocrine non-communicable metabolic disorders which is mainly caused either due to insufficient insulin or inefficient insulin or both together and is characterized by hyperglycemia. Diabetes emerged as a serious health issue in the industrialized and developing country especially in the Asian pacific region. Out of the two major categories of diabetes mellitus, type 2 diabetes is more prevalent, almost 90 to 95% cases, and the main cause of this is insulin resistance. The main cause of the progression of type 2 diabetes mellitus has been found to be insulin resistance. The type 2 diabetes mellitus may be managed by the change in lifestyle, physical activities, dietary modifications and medications. The major currently available management strategies are sulfonylureas, biguanides, thiazolidinediones, α-glucosidase inhibitors, dipeptidyl peptidase-IV inhibitors, and glucagon-like peptide-1 (GLP-1) agonist. Binding of insulin on the extracellular unit of insulin receptor sparks tyrosine kinase of the insulin receptor which induces autophosphorylation. The phosphorylation of the tyrosine is regulated by insulin and leptin molecules. Protein tyrosine phosphatase-1B (PTP1B) works as a negative governor for the insulin signalling pathways, as it dephosphorylates the tyrosine of the insulin receptor and suppresses the insulin signalling cascade. The compounds or molecules which inhibit the negative regulation of PTP1B can have an inductive effect on the insulin pathway and finally help in the management of diabetes mellitus. PTP1B could be an emerging therapeutic strategy for diabetes management. There are a number of clinical and basic research results which suggest that induced expression of PTP1B reduces insulin resistance. In this review, we briefly elaborate and explain the place of PTP1B and its significance in diabetes as well as a recent development in the PTP1B inhibitors as an antidiabetic therapy.

Anti-Diabetic Activity of 2,3,6-Tribromo-4,5-Dihydroxybenzyl Derivatives from Symphyocladia latiuscula through PTP1B Downregulation and α-Glucosidase Inhibition

The marine alga, Symphyocladia latiuscula (Harvey) Yamada, is a good source of bromophenols with numerous biological activities. This study aims to characterize the anti-diabetic potential of 2,3,6-tribromo-4,5-dihydroxybenzyl derivatives isolated from S. latiuscula via their inhibition of tyrosine phosphatase 1B (PTP1B) and α-glucosidase. Additionally, this study uses in silico modeling and glucose uptake potential analysis in insulin-resistant (IR) HepG2 cells to reveal the mechanism of anti-diabetic activity. This bioassay-guided isolation led to the discovery of three potent bromophenols that act against PTP1B and α-glucosidase: 2,3,6-tribromo-4,5-dihydroxybenzyl alcohol (1), 2,3,6-tribromo-4,5-dihydroxybenzyl methyl ether (2), and bis-(2,3,6-tribromo-4,5-dihydroxybenzyl methyl ether) (3). All compounds inhibited the target enzymes by 50% at concentrations below 10 μM. The activity of 1 and 2 was comparable to ursolic acid (IC₅₀; 8.66 ± 0.82 μM); however, 3 was more potent (IC₅₀; 5.29 ± 0.08 μM) against PTP1B. Interestingly, the activity of 1–3 against α-glucosidase was 30–110 times higher than acarbose (IC₅₀; 212.66 ± 0.35 μM). Again, 3 was the most potent α-glucosidase inhibitor (IC₅₀; 1.92 ± 0.02 μM). Similarly, 1–3 showed concentration-dependent glucose uptake in insulin-resistant HepG2 cells and downregulated PTP1B expression. Enzyme kinetics revealed different modes of inhibition. In silico molecular docking simulations demonstrated the importance of the 7–OH group for H-bond formation and bromine/phenyl ring number for halogen-bond interactions. These results suggest that bromophenols from S. latiuscula, especially highly brominated 3, are inhibitors of PTP1B and α-glucosidase, enhance insulin sensitivity and glucose uptake, and may represent a novel class of anti-diabetic drugs.

Discovery and evaluation of the hybrid of bromophenol and saccharide as potent and selective protein tyrosine phosphatase 1B inhibitors

Protein tyrosine phosphatase 1B (PTP1B) is a key negative regulator of insulin signaling pathway. Inhibition of PTP1B is expected to improve insulin action. Appropriate selectivity and permeability are the gold standard for excellent PTP1B inhibitors. In this work, molecular hybridization-based screening identified a selective competitive PTP1B inhibitor. Compound 10a has IC₅₀ values of 199 nM against PTP1B, and shows 32-fold selectivity for PTP1B over the closely related phosphatase TCPTP. Molecule docking and molecular dynamics studies reveal the reason of selectivity for PTP1B over TCPTP. Moreover, the cell permeability and cellular activity of compound 10a are demonstrated respectively.

PTP1B inhibitors for type 2 diabetes treatment: a patent review (2011 - 2014)

INTRODUCTION

Protein tyrosine phosphatase 1B (PTP1B) plays an important role in the negative regulation of insulin signal transduction pathway and has emerged as novel therapeutic strategy for the treatment of type 2 diabetes. PTP1B inhibitors enhance the sensibility of insulin receptor (IR) and have favorable curing effect for insulin resistance-related diseases. A large number of PTP1B inhibitors, either synthetic or isolated as bioactive agents from natural products, have developed and investigated for their ability to stimulate insulin signaling.

AREAS COVERED

This review includes an updated summary (2011 - 2014) of PTP1B inhibitors that have been published in patent applications, with an emphasis on their chemical structure, mode of action and therapeutic outcomes. The usefulness of PTP1B inhibitors as pharmaceutical agents for the treatment of type 2 diabetes is also discussed.

EXPERT OPINION

PTP1B inhibitors show beneficial effects to enhance sensibility of IR by restricting the activity of enzyme and have favorable curing effects. However, structural homologies in the catalytic domain of PTP1B with other protein tyrosine phosphatases (PTPs) like leukocyte common antigen-related, CD45, SHP-2 and T-cell-PTP present a challenging task of achieving selectivity. Thus, for therapeutic application of PTP1B inhibitors, highly selective molecules exhibiting desired effects without side effects are expected to find clinical application.

Identification of small molecule inhibitors of PTPσ through an integrative virtual and biochemical approach

PTPσ is a dual-domain receptor type protein tyrosine phosphatase (PTP) with physiologically important functions which render this enzyme an attractive biological target. Specifically, loss of PTPσ has been shown to elicit a number of cellular phenotypes including enhanced nerve regeneration following spinal cord injury (SCI), chemoresistance in cultured cancer cells, and hyperactive autophagy, a process critical to cell survival and the clearance of pathological aggregates in neurodegenerative diseases. Owing to these functions, modulation of PTPσ may provide therapeutic value in a variety of contexts. Furthermore, a small molecule inhibitor would provide utility in discerning the cellular functions and substrates of PTPσ. To develop such molecules, we combined in silico modeling with in vitro phosphatase assays to identify compounds which effectively inhibit the enzymatic activity of PTPσ. Importantly, we observed that PTPσ inhibition was frequently mediated by oxidative species generated by compounds in solution, and we further optimized screening conditions to eliminate this effect. We identified a compound that inhibits PTPσ with an IC₅₀ of 10 µM in a manner that is primarily oxidation-independent. This compound favorably binds the D1 active site of PTPσ in silico, suggesting it functions as a competitive inhibitor. This compound will serve as a scaffold structure for future studies designed to build selectivity for PTPσ over related PTPs.

Self-organizing molecular field analysis on pregnane derivatives as human steroidal 5alpha-reductase inhibitors

Normal growth and development of human prostate is regulated by the androgens which balances cell proliferation and apoptosis. Testosterone (T) and dihydrotestosterone (DHT) are the two key androgens that stimulate most of the androgen action in prostate. Testosterone is converted to DHT by the membrane bound NADPH-dependent 5alpha-reductase enzyme. As a consequence of the important observation that progesterone and deoxycortisone inhibits the synthesis of DHT by competing with 4-en-3-one function of the testosterone for the 5alpha-reductase enzyme a number of pregnane derivatives were synthesized and have been reported as inhibitors of human 5alpha-reductase enzyme. Due to lack of information on the crystal structure of human 5alpha-reductase, ligand-based 3D-QSAR study has been performed on pregnane derivatives using self-organizing molecular field analysis (SOMFA) for rationalizing the molecular properties and human 5alpha-reductase inhibitory activities. The statistical results having good cross-validated r(cv)(2) (0.881), non-cross-validated r(2) (0.893) and F-test value (175.527), showed satisfied predictive ability r(pred)(2) (0.777). Analysis of SOMFA models through electrostatic and shape grids provide useful information for the design and optimization of steroidal structure as novel human 5alpha-reductase inhibitors.

Development of predictive 3D-QSAR CoMFA and CoMSIA models for beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors

A three-dimensional quantitative structure-activity relationship study was performed on a series of beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors employing comparative molecular field analysis and comparative molecular similarity indices analysis techniques to investigate the structural requirements for the inhibitors, and derive a predictive model that could be used for the design of novel tumor necrosis factor-alpha converting enzyme inhibitors. log P was used as an additional descriptor in the comparative molecular field analysis analysis to study the effects of lipophilic parameters on activity. Inclusion of log P did not improve the models significantly. The statistically significant model was established with 45 molecules, which were validated by a test set of 11 compounds. Ligand molecular superimposition on the template structure was performed by the atom-/shape-based root mean square fit and database alignment methods. Docked conformer based alignment (V) yielded the best predictive comparative molecular field analysis model = 0.673, = 0.860, F-value = 86.073, predictive r (2) = 0.642, with two components, standard error of prediction = 0.394 and standard error of estimates = 0.243 while the comparative molecular similarity indices analysis model yielded = 0.635, = 0.858, F-value = 84.451, predictive r (2) = 0.441 with three components, standard error of prediction = 0.393 and standard error of estimates = 0.245. The contour maps obtained from three-dimensional quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular field analysis models exhibited good external predictivity as compared with that of comparative molecular similarity indices analysis models. The model generated through comparative molecular field analysis was validated with the IK-682. The data generated from this study may guide our efforts in designing and predicting the tumor necrosis factor-alpha converting enzyme inhibitory activity of novel molecules.

CoMFA and CoMSIA analysis of 2,4-thiazolidinediones derivatives as aldose reductase inhibitors

Diabetes remains a life-threatening disease. The clinical profile of diabetic subjects is often worsened by the presence of several long-term complications, for example neuropathy, nephropathy, retinopathy, and cataract. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 2,4-thiazolidinediones derivatives as aldose reductase (ALR2) inhibitors. Molecular ligand superimposition on a template structure was finished by the database alignment method. The 3D-QSAR models resulted from 44 molecules gave q (2) values of 0.773 and 0.817, r (2) values of 0.981 and 0.979 for CoMFA and CoMSIA, respectively. The contour maps from the models indicated that a large volume group next to the R-substituent will increase the ALR2 inhibitory activity. In fact, adding a -CH(2)COOH substituent at the R-position would generate a new compound with higher predicted activity.

CoMFA on the melanogenesis inhibitory activity of alkyl-3,4-dihydroxybenzoate, N-alkyl-3,4-dihydroxybenzamide analogues, and prediction of higher active compounds

To predict a new materials of superior melanogenesis inhibitory activities (MIA), the comparative molecular field analysis (CoMFA) models on MIA of alkyl-3,4-dihydroxybenzoates and N-alkyl-3,4-dihydroxybenzamides analogues against mouse melanoma cell were derived and discussed quantitatively. The optimized CoMFA model II from the field fit alignment demonstrated better predictability of molecular structure with the non-cross validated conventional coefficient (r2 (nev.)=0.984) and cross-validated coefficient (r2 (cv.) or q=0.706) than that from atom based fit alignment. Also, the relative contribution of the optimized CoMFA model II showed the steric (63.8%), electrostatic (18.4%), and hydrophobic (ClogP) field (17.8%), respectively. The results indicated that the esters (alkyl-3,4-dihydroxybenzoates) are more active inhibitors than the amides (N-alkyl-3,4-dihydroxybenzamides). Furthermore, the optimized CoMFA model II is proven to be a useful approach to design a highly active melanogenesis inhibitor molecules, and enables to predict R1 = n-dodecy and R2 = n-heptyloxy substituted compound of alkyl-3,4-dihydroxybenzoates as the most active compounds (Pred. pI50 = 5.87).

Insights into the structural requirements of farnesyltransferase inhibitors as potential anti-tumor agents based on 3D-QSAR CoMFA and CoMSIA models

A three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on three different chemical series reported as selective farnesyltransferase (FTase) inhibitors employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) techniques to investigate the structural requirements for substrates and derive a predictive model that may be used for the design of novel FTase inhibitors. Removal of outliers improved the predictive power of models developed for all three structurally diverse classes of compounds. 3D-QSAR models were derived for 3-aminopyrrolidinone derivatives (training set N=38, test set N=7), 2-amino-nicotinonitriles (training set N=46, test set N=13) and 1-aryl-1'-imidazolyl methyl ethers (training set N=35, test set N=5). The CoMFA models with steric and electrostatic fields exhibited r(2)(cv) 0.479-0.803, r(2)(ncv) 0.945-0.993, r(2)(pred) 0.686-0.811. The CoMSIA models displayed r(2)(cv) 0.411-0.814, r(2)(ncv) 0.923-0.984, r(2)(pred) 0.399-0.787. 3D contour maps generated from these models were analyzed individually, which provide the regions in space where interactive fields may influence the activity. The superimposition of contour maps on the active site of farnesyltransferase additionally helps in understanding the structural requirements of these inhibitors. 3D-QSAR models developed may guide our efforts in designing and predicting the FTase inhibitory activity of novel molecules.

CoMFA based de novo design of pyridazine analogs as PTP1B inhibitors

PTP1B plays an important role as a negative regulator in insulin and leptin signaling pathways. Potent and orally active PTP1B inhibitors can act as potential agents for the treatment of Type 2 diabetes and obesity. CoMFA (Comparative Molecular Field Analysis) and de novo ligand design using LeapFrog (LF) studies were performed on pyridazine analogs, reported to be selective and non-competitive inhibitors of PTP1B. A robust model was developed which produced statistically significant results with cross-validated and conventional correlation coefficients of 0.619 and 0.990, respectively. Further, the robustness of the model was verified by bootstrapping analysis. LeapFrog (LF) program is a de novo drug discovery tool, which uses CoMFA maps to generate hypothetical cavity and ligands. As the crystal structure of PTP1B-pyridazine complex is not yet known, the contours of CoMFA model was used to serve as a pharmacophoric model to generate hypothetical cavity for LeapFrog calculations. Ligands were optimized using this concept.

Discovery of new potent human protein tyrosine phosphatase inhibitors via pharmacophore and QSAR analysis followed by in silico screening

A pharmacophoric model was developed for human protein tyrosine phosphatase 1B (h-PTP 1B) inhibitors utilizing the HipHop-REFINE module of CATALYST software. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of physicochemical descriptors and pharmacophore hypothesis that yield consistent QSAR equation of good predictive potential (r = 0.87,F-statistic = 69.13,r(BS)2 = 0.76,r(LOO)2 = 0.68). The validity of the QSAR equation and the associated pharmacophoric hypothesis was experimentally established by the identification of five new h-PTP 1B inhibitors retrieved from the National Cancer Institute (NCI) database.

3D QSAR Studies on Protein Tyrosine Phosphatase 1B Inhibitors: Comparison of the Quality and Predictivity among 3D QSAR Models Obtained from Different Conformer-Based Alignments

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

3D-QSAR of histone deacetylase inhibitors: hydroxamate analogues

The histone deacetylase enzyme has increasingly become an attractive target for developing novel anticancer drugs. Hydroxamates are a new class of anticancer agents reported to act by selective inhibition of the histone deacetylase (HDAC) enzyme. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were employed to study three-dimensional quantitative structure-activity relationships (3D-QSARs). QSAR models were derived from a training set of 40 molecules. An external test set consisting of 17 molecules was used to validate the CoMFA and CoMSIA models. All molecules were superimposed on the template structure by atom-based, multifit and the SYBYL QSAR rigid body field fit alignments. The statistical quality of the QSAR models was assessed using the parameters r(2)(conv), r(2)(cv) and r(2)(pred). In addition to steric and electronic fields, ClogP was also taken as descriptor to account for lipophilicity. The resulting models exhibited a good conventional r(2)(conv) and cross-validated r(2)(cv) values up to 0.910 and 0.502 for CoMFA and 0.987 and 0.534 for CoMSIA. Robust cross-validation by 2 groups was performed 25 times to eliminate chance correlation. The CoMFA models exhibited good external predictivity as compared to that of CoMSIA models. These 3D-QSAR models are very useful for design of novel HDAC inhibitors.

3D-QSAR studies of indole derivatives as phosphodiesterase IV inhibitors

The 3D-QSAR studies of some indole derivatives as phosphodiesterase (PDE) type IV inhibitors was performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The global minimum energy conformer of the template molecule, 3 the most active molecule of the series, was obtained by simulated annealing method and used to build the structures of the molecules in the dataset. The CoMFA model produced statistically significant results with cross-validated and conventional correlation coefficients of 0.494 and 0.986 respectively. The combination of steric, electrostatic and hydrophobic fields in CoMSIA gave the best results with cross-validated and conventional correlation coefficients of 0.541 and 0.967 respectively. The predictive ability of CoMFA and CoMSIA were determined using a test set of seven indole derivatives giving predictive correlation coefficients of 0.56 and 0.59 respectively indicating good predictive power. Further, the robustness of the models was verified by bootstrapping analysis. Based upon the information derived from CoMFA and CoMSIA, we have identified some key features that may be used to design new indole derivatives and predict their PDE IV affinities prior to synthesis.

Comparative molecular field analysis (CoMFA) of phthalazine derivatives as phosphodiesterase IV inhibitors

A comparative molecular field analysis (CoMFA) of phthalazine class of phosphodiesterase IV (PDE IV) inhibitors has been performed to correlate their chemical structures with their observed biological activity. A statistically valid model with good correlative and predictive power is reported. The leave one out cross-validation study gave cross-validation r(2)(cv) of value 0.507 at six optimum components and conventional r(2) of value 0.98. The predictive ability of the model was tested by predicting the seven molecules belonging to the test set giving predictive correlation coefficient of 0.59. This model is potentially helpful in the design of novel and more potent PDE IV inhibitors.