Hardik Bhatt

Histamine H4 Receptor: A Novel Therapeutic Target for Immune and Allergic Responses

HIstamine is a biomolecular compound located in various parts of body. It participated in various important cellular activities associated with allergy and asthma. This magic bio-molecule is directly and indirectly involved in various biochemical reactions through G-protein couple receptors. Various histamine receptors and their unexplored biochemical activities attracted many biologists in last few decades. A surprising discovery of histamine H(4) receptor was done when scientist worked on histamine H(3) receptor in brain cells. The binding pocket of histamine H(4) differs by transmembrane domains (TM3, TM5 and TM6) from histamine H(3)-sub type. In this review, we enlightened various functions of histamine H(4) and use of histamine H(4) receptor antagonists in autoimmune diseases, allergic responses, inflammatory responses, and in superoxide generation which are helpful to establish H(4) receptor antagonists as newer anti histamines.

A supercritical fluid chromatography/tandem mass spectrometry method for the simultaneous quantification of metformin and gliclazide in human plasma

Present study reports the development and validation of a simultaneous estimation of metformin and gliclazide in human plasma using supercritical fluid chromatography followed by tandem mass spectrometry. Acetonitrile:water (80:20) mixture was used as a mobile phase along with liquid CO2 in supercritical fluid chromatography and phenformin as an internal standard. The modified plasma samples were analyzed by electro-spray ionization method in selective reaction monitoring mode in tandem mass spectrometry. Supercritical fluid chromatographic separation was performed using nucleosil C18 containing column as a stationary phase. The separated products were identified by characteristic peaks and specific fragments peaks in tandem mass spectrometry as m/z 130 to 86 for metformin, m/z 324 to 110 for gliclazide and m/z 206 to 105 for phenformin. The present method was found linear in the concentration ranges of 6.0-3550 ng/ml and 7.5-7500 ng/ml for metformin and gliclazide, respectively. Pharmacokinetic study was performed after an oral administration of dispersible tablets containing 500 mg of metformin and 80 mg of gliclazide using same techniques.

Pharmacophore modeling, virtual screening and 3D-QSAR studies of 5-tetrahydroquinolinylidine aminoguanidine derivatives as sodium hydrogen exchanger inhibitors.

Sodium hydrogen exchanger (SHE) inhibitor is one of the most important targets in treatment of myocardial ischemia. In the course of our research into new types of non-acylguanidine, SHE inhibitory activities of 5-tetrahydroquinolinylidine aminoguanidine derivatives were used to build pharmacophore and 3D-QSAR models. Genetic Algorithm Similarity Program (GASP) was used to derive a 3D pharmacophore model which was used in effective alignment of data set. Eight molecules were selected on the basis of structure diversity to build 10 different pharmacophore models. Model 1 was considered as the best model as it has highest fitness score compared to other nine models. The obtained model contained two acceptor sites, two donor atoms and one hydrophobic region. Pharmacophore modeling was followed by substructure searching and virtual screening. The best CoMFA model, representing steric and electrostatic fields, obtained for 30 training set molecules was statistically significant with cross-validated coefficient (q(2)) of 0.673 and conventional coefficient (r(2)) of 0.988. In addition to steric and electrostatic fields observed in CoMFA, CoMSIA also represents hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. CoMSIA model was also significant with cross-validated coefficient (q(2)) and conventional coefficient (r(2)) of 0.636 and 0.986, respectively. Both models were validated by an external test set of eight compounds and gave satisfactory prediction (r(pred)(2)) of 0.772 and 0.701 for CoMFA and CoMSIA models, respectively. This pharmacophore based 3D-QSAR approach provides significant insights that can be used to design novel, potent and selective SHE inhibitors.

3D-QSAR (CoMFA, CoMFA-RG, CoMSIA) and molecular docking study of thienopyrimidine and thienopyridine derivatives to explore structural requirements for aurora-B kinase inhibition

Aurora-B kinase plays a crucial role in cell cycle events and is identified as an important factor in regulation of spindle check point assembly. Thus, it can be proved as an important target in the field of oncology. 3D-QSAR model was generated using 54 molecules reported in literature containing thienopyrimidine and thienopyridine as scaffolds. All molecules were aligned using Distill function in Sybyl X1.2. This generated best model of CoMFA-RG (Region focusing) and CoMSIA were statistically significant with correlation coefficient r(2)ncv of 0.97, for both & Leave one out coefficient (LOO) q(2) of 0.70 and 0.72, respectively. Best CoMSIA model was built up using various combination of descriptors and proved statistical significant among all models. Best CoMFA-RG and CoMSIA models were validated by 12 test set molecules giving satisfactory prediction (r(2)pred) values of 0.86 and 0.88, respectively. External test set validation was performed using 20 molecules and satisfactory prediction of their biological activity was found. Active compounds were docked on protein (PDB ID: 4C2V) by GOLD module and revealed important interactions with amino acids at ATP-binding region. These data explored insight requirements for Aurora-B inhibition which might be fruitful for understanding mechanisms with kinase ligand interactions.

A comprehensive review on Aurora kinase: Small molecule inhibitors and clinical trial studies

Aurora kinase belongs to serine/threonine kinase family which controls cell division. Therapeutic inhibition of Aurora kinase showed great promise as probable anticancer regime because of its important role during cell division. Here, in this review, we have carried out exhaustive study of various synthetic molecules reported as Aurora kinase inhibitors and developed as lead molecule at various stages of clinical trials from its discovery in 1995 to till date. We reported details of small molecules, specifically inhibiting all 3 types of Aurora kinases, which includes extensive literature search in various database like various scientific journals, patents, scifinder and PubMed database, internet resources, books, etc. IC50 values of tumor growth inhibition, in-vitro and in-vivo activity along with clinical trial data. Here, we took efforts to describe essence of Aurora kinase and its inhibition which could be used to develop anti-mitotic drug for the treatment of cancer. In conclusion, we also discuss future perspectives for development of novel inhibitors and their scope in drug development process.

Discovery of HIV-1 integrase inhibitors: pharmacophore mapping, virtual screening, molecular docking, synthesis, and biological evaluation.

HIV‐1 integrase enzyme plays an important role in the life cycle of HIV and responsible for integration of virus into human genome. Here, both computational and synthetic approaches were used to design and synthesize newer HIV‐1 integrase inhibitors. Pharmacophore mapping was performed on 20 chemically diverse molecules using DISCOtech, and refinement was carried out using GASP. Ten pharmacophore models were generated, and model 2, containing four features including two donor sites, one acceptor atom, and one hydrophobic region, was considered the best model as it has the highest fitness score. It was used as a query in NCI and Maybridge databases. Molecules having more than 99% Qfit value were used to design 30 molecules bearing pteridine ring and were docked on co‐crystal structure of HIV‐1 integrase enzyme. Among these, six molecules, showing good docking score compared with the reference standards, were synthesized by conventional as well as microwave‐assisted methods. All compounds were characterized by physical and spectral data and evaluated for in vitro anti‐HIV activity against the replication of HIV‐1 (IIIB) in MT‐4 cells. The used approach of molecular docking and anti‐HIV activity data of designed molecules will provide significant insights to discover novel HIV‐1 Integrase Inhibitors.

3D-QSAR, molecular dynamics simulations and molecular docking studies of benzoxazepine moiety as mTOR inhibitor for the treatment of lung cancer.

According to WHO statistics, lung cancer is one of the leading causes of death among all other types of cancer. Many genes get mutated in lung cancer but involvement of EGFR and KRAS are more common. Unavailability of drugs or resistance to the available drugs is the major problem in the treatment of lung cancer. In the present research, mTOR was selected as an alternative target for the treatment of lung cancer which involves PI3K/AKT/mTOR pathway. 28 synthetic mTOR inhibitors were selected from the literature. Ligand based approach (CoMFA and CoMSIA) and structure based approach (molecular dynamics simulations assisted molecular docking study) were applied for the identification of important features of benzoxazepine moiety, responsible for mTOR inhibition. Three different alignments were tried to obtain best QSAR model, of which, distil was found to be the best method, as it gave good statistical results. In CoMFA, Leave One Out (LOO) cross validated coefficients (q(2)), conventional coefficient (r(2)) and predicted correlation coefficient (r(2)pred) values were found to be 0.615, 0.990 and 0.930, respectively. Similarly in CoMSIA, q(2), r(2)ncv and r(2)pred values were found to be 0.748, 0.986 and 0.933, respectively. Molecular dynamics and simulations study revealed that B-chain of mTOR protein was stable at and above 500 FS with respect to temperature (at and above 298 K), Potential energy (at and above 7669.72 kJ/mol) and kinetic energy (at and above 4009.77 kJ/mol). Molecular docking study was performed on simulated protein of mTOR which helped to correlate interactions of amino acids surrounded to the ligand with contour maps generated by QSAR method. Important features of benzoxazepine were identified by contour maps and molecular docking study which would be useful to design novel molecules as mTOR inhibitors for the treatment of lung cancer.

Design, synthesis and anti-HIV activity of novel quinoxaline derivatives

In order to design novel anti-HIV agents, pharmacophore modelling, virtual screening, 3D-QSAR and molecular docking studies were performed. Pharmacophore model was generated using 17 structurally diverse molecules using DISCOtech followed by refinement with GASP module of Sybyl X. The best model containing four features; two donor sites, one acceptor atom and one hydrophobic region; was used as a query for virtual screening in NCI database and 6 compounds with Qfit value ≥98 were retrieved. The quinoxaline ring which is the bio-isostere of pteridine ring, retrieved as a hit in virtual screening, was selected as a core moiety. 3D-QSAR was carried on thirty five 5-hydroxy-6-oxo-1,6-dihydropyrimidine-4-carboxamide derivatives. Contour map analysis of best CoMFA and CoMSIA model suggested incorporation of hydrophobic, bulky and electronegative groups to increase potency of the designed compounds. 50 quinoxaline derivatives with different substitutions were designed on basis of both ligand based drug design approaches and were mapped on the best pharmacophore model. From this, best 32 quinoxaline derivatives were docked onto the active site of integrase enzyme and in-silico ADMET properties were also predicted. From this data, synthesis of top 7 quinoxaline derivatives was carried out and were characterized using Mass, (1)H-NMR and (13)C-NMR spectroscopy. Purity of compounds were checked using HPLC. These derivatives were evaluated for anti-HIV activity on III-B strain of HIV-1 and cytotoxicity studies were performed on VERO cell line. Two quinoxaline derivatives (7d and 7e) showed good results, which can be further explored to develop novel anti-HIV agents.

Design and synthesis of potent N-phenylpyrimidine derivatives for the treatment of skin cancer

The development of novel synthetic compounds for the treatment of skin cancer is much needed, as there is a sudden rise in the incidence of skin cancer throughout the world and the available chemotherapy is facing problems of resistance. Hence, present research efforts have been made to discover potent molecules against skin cancer. Pharmacophore models were developed using the GALAHAD module of Sybyl X, followed by validation, virtual screening, design and in silico ADMET studies. Based on features generated in the computational studies and the structural importance of the pyrimidine moiety with the highest QFIT value molecule for virtual hits; it was selected as a core moiety for further designing molecules of interest. Fourteen substituted pyrimidine derivatives were designed, synthesized and characterised by 1H and 13C NMR, mass and elemental analysis, while the purity was checked by HPLC. All these compounds were evaluated in in vitro studies on five cancer lines; from which, four compounds were found to be potent, specifically with the skin cancer cell line. Based on the results of the in vitro studies, they were selected further, along with 5-FU, for an in vivo study with the DMBA-induced skin cancer model. One compound, 6h, showed favourable action against skin cancer and treated tumours, demonstrating the potential of the series. This study could be explored in future to design lead molecule for the treatment of skin cancer.

3D QSAR study of 4H-chromen-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives as potential anti-mycobacterial agents

In this study, 3D QSAR (CoMFA and CoMSIA) analysis was performed on 4H-chromen-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives as potential anti-mycobacterial agents. ‘Distill’ function in SYBYL X 1.2 was used for alignment of the molecules. The best CoMFA and CoMSIA models were obtained for the training set compounds with leave-one-out correlation coefficients (q2) of 0.753 and 0.646, cross validated correlation coefficients (rcv2) of 0.714 and 0.619, and conventional coefficients (r2) of 0.975 and 0.983, respectively. Both the models were validated by a test set of 8 compounds giving satisfactory prediction (rpred2) of 0.788 and 0.663 for CoMFA and CoMSIA models, respectively. The results of the study would provide useful information for the design of new compounds and it would also help in prediction of activity of designed compounds prior to their synthesis.