Designing, docking and molecular dynamics simulation studies of novel cloperastine analogues as anti-allergic agents: homology modeling and active site prediction for the human histamine H1 receptor.

The present study predicts a three-dimensional model for the histamine H1 receptor and the design of antihistamine inhibitors using cloperastine as the core molecule by docking studies. In this work, we predicted a three-dimensional structure of the histamine H1 receptor using the MODELLER9V7 software. The protein structure was developed based on the crystal structure of the histamine H1 receptor, the lysozyme chimera of Escherichia virus T4 (PDB ID: 3RZE_A) target collected from the PDB data bank. Using molecular dynamics simulation methods, the final predicted structure is obtained and further analyzed by VERIFY3D and PROCHECK programs, confirming that the final model is reliable. The drug derivatives of cloperastine were designed and docking was performed with the designed ligands along with the drug. The predicted model of the histamine H1 receptor structure is stable and confirms that it is a reliable structure for docking studies. The results indicate that MET 183, THR 184 and ILE 187 in the histamine H1 receptor are important determinant residues for binding as they have strong hydrogen bonding with cloperastine derivatives. The drug derivatives were docked to the histamine H1 receptor protein by hydrogen bonding interactions and these interactions played an important role in the binding studies. The molecule 1-{2-[(4-chlorophenyl) (phenyl) methoxy] ethyl}-4-methylenepiperidine showed the best docking results with the histamine H1 receptor. The docking results predicted the best compounds, which may act as better drugs than cloperastine and in the future, these may be developed for anti-allergy therapy.

In Silico Studies on Anti-Stress Compounds of Ethanolic Root Extract of Hemidesmus indicus L.

BACKGROUND: Alternative medicine is available for those diseases which cannot be treated by conventional medicine. Ayurveda and herbal medicines are important alternative methods in which the treatment is done with extracts of different medicinal plants. This work is concerned with the evaluation of anti-stress bioactive compounds from the ethanolic root extract of Hemidesmus indicus. METHODS: Gas chromatography and Mass Spectrum studies are used to identify the compounds present in the ethanolic extract based on the retention time, area. In order to perform docking studies, Vasopressin model is generated using modeling by Modeller 9v7. Vasopressin structure is developed based on the crystal structure of neurophysin-oxytocin from Bos taurus (PDB ID: 1NPO_A) collected from the PDB data bank. Using molecular dynamics simulation methods, the final predicted structure is obtained and further analyzed by verifying 3D and PROCHECK programs, confirmed that the final model is reliable. The identified compounds are docked to vasopressin for the prediction of anti-stress activity using GOLD 3.0.1 software. RESULTS: The predicted model of Vasopressin structure is stabilized and confirmed that it is a reliable structure for docking studies. The results indicated ARG4, THR7, ASP9, ASP26, ALA32, ALA 80 in Vasopressin are important determinant residues in binding as they have strong hydrogen bonding with phytocompounds. Among the 21 phytocompounds identified and docked, molecule Deoxiinositol, pentakis- O-(trimethylsilyl) showed the best docking results with Vasopressin. CONCLUSION: The identified compounds were used for anti-stress activity by insilico method with Vasopressin which plays an important role in causing stress and hence selected for inhibitory studies with phytocompounds. The phytocompounds are inhibiting vasopressin through hydrogen bodings and are important in protein-ligand interactions. Docking results showed that out of twenty-one compounds, Deoxiinositol, pentakis-O-(trimethylsilyl) showed best docking energy to the Vasopressin.

Genetic polymorphism of glutathione S-transferases: Relevance to neurological disorders.

Glutathione S-tranferases (GSTs) are phase II drug metabolizing enzymes, they play crucial role in detoxification of environmental pollutants, carcinogens, drugs, xenobiotics and oxidative stress products. Genetic differences in expression and activity of GSTs are due to the existence of polymorphic alleles which encode them. Because of genetic polymorphism the GST activity has altered that lead to the increased susceptibility for toxic chemical compounds. GST genetic polymorphism is the main reason for many neurological dysfunctions. GST has over expressed in epileptic brain and pi (π) GST has used to predict stroke; mu (µ) and pi (π) GST are over expressed in Alzheimer's disease (AD). Null and single nucleotide polymorphism of GST has associated with many neurodisorders. Over all, it can be concluded that the GST genetic polymorphism has associated with neurodegenerative diseases.

Analysis of Chemical Signatures of Alkaliphiles using Fatty Acid Methyl Ester Analysis.

BACKGROUND: Fatty acids occur in nearly all living organisms as the important predominant constituents of lipids. While all fatty acids have essentially the same chemical nature, they are an extremely diverse group of compounds. MATERIALS AND METHODS: To test the hypothesis, fatty acids of alkaliphiles isolates, Bacillus subtilis SVUNM4, Bacillus licheniformis SVUNM8, Bacillus methylotrohicus SVUNM9, and Paenibacillus dendritiformis SVUNM11, were characterized compared using gas chromatography-mass spectrometry (GC-MS) analysis. RESULTS: The content of investigated ten fatty acids, 1, 2-benzenedicarboxylic acid butyl 2-methylpropyl ester, phthalic acid, isobutyl 2-pentyl ester, dibutyl phthalate, cyclotrisiloxane, hexamethyl, cyclotetrasiloxane, octamethyl, dodecamethyl, heptasiloxane 1,1,3,3,5,5,7,7,9,9,11,11,13,13-etradecamethyl, 7,15-dihydroxydehydroabietic acid, methyl ester, di (trimethylsilyl) ether, hentriacontane, 2-thiopheneacetic acid, undec-2-enyl ester, obviously varied among four species, suggesting each species has its own fatty acid pattern. CONCLUSIONS: These findings demonstrated that GC-MS-based fatty acid profiling analysis provides the reliable platform to classify these four species, which is helpful for ensuring their biotechnological interest and novel chemotaxonomic.