Matcha Bhaskar

Identification of substituted (3, 2-a) pyrimidines as selective antiviral agents: Molecular modeling study

A series of novel substituted dihydropyrimidine and 5H-thiazolo [3, 2-a] pyrimidine derivatives were designed and synthesized as a potential target to discover drugs fighting against the viral diseases. The main objective of the present work is to carry out the QSAR studies for all the series of the compounds starting from 4a to 6j to find out their molecular descriptors and predict the biological properties. All of them are showing the best QSAR descriptors, hence chosen for the prediction of anti-viral activity against Newcastle disease virus (NDV). Initially their inhibitory activity was predicted by molecular docking of these compounds against haemaglutinin-neuraminidase (HN) protein using molecular operating environment (MOE) software. Based on the best affinity and highest docking scores 4b, 5b and 6b were assayed in vivo on NDV infected chicks and it was found that there is significant improvement in the survival of the chicks with the treatment (P<0.05). 4b and 6b showed better curative effect than 5b at the dose concentration of 40 mg/kg body weight of chicks. The results from molecular docking study and biological assays can be inferred to consider these molecules as potential antiviral drugs.

Isolation and characterization of ethanol tolerant yeast strains

Yeast strains are commonly associated with sugar rich environments. Various fruit samples were selected as source for isolating yeast cells. The isolated cultures were identified at Genus level by colony morphology, biochemical characteristics and cell morphological characters. An attempt has been made to check the viability of yeast cells under different concentrations of ethanol. Ethanol tolerance of each strain was studied by allowing the yeast to grow in liquid YEPD (Yeast Extract Peptone Dextrose) medium having different concentrations of ethanol. A total of fifteen yeast strains isolated from different samples were used for the study. Seven strains of Saccharomyces cerevisiae obtained from different fruit sources were screened for ethanol tolerance. The results obtained in this study show a range of tolerance levels between 7%-12% in all the stains. Further, the cluster analysis based on 22 RAPD (Random Amplified polymorphic DNA) bands revealed polymorphisms in these seven Saccharomyces strains.

Modeling, molecular dynamics, and docking assessment of transcription factor rho: a potential drug target in Brucella melitensis 16M

The zoonotic disease brucellosis, a chronic condition in humans affecting renal and cardiac systems and causing osteoarthritis, is caused by Brucella, a genus of Gram-negative, facultative, intracellular pathogens. The mode of transmission and the virulence of the pathogens are still enigmatic. Transcription regulatory elements, such as rho proteins, play an important role in the termination of transcription and/or the selection of genes in Brucella. Adverse effects of the transcription inhibitors play a key role in the non-successive transcription challenges faced by the pathogens. In the investigation presented here, we computationally predicted the transcription termination factor rho (TtFRho) inhibitors against Brucella melitensis 16M via a structure-based method. In view the unknown nature of its crystal structure, we constructed a robust three-dimensional homology model of TtFRho’s structure by comparative modeling with the crystal structure of the Escherichia coli TtFRho (Protein Data Bank ID: 1PVO) as a template in MODELLER (v 9.10). The modeled structure was optimized by applying a molecular dynamics simulation for 2 ns with the CHARMM (Chemistry at HARvard Macromolecular Mechanics) 27 force field in NAMD (NAnoscale Molecular Dynamics program; v 2.9) and then evaluated by calculating the stereochemical quality of the protein. The flexible docking for the interaction phenomenon of the template consists of ligand-related inhibitor molecules from the ZINC (ZINC Is Not Commercial) database using a structure-based virtual screening strategy against minimized TtFRho. Docking simulations revealed two inhibitors compounds – ZINC24934545 and ZINC72319544 – that showed high binding affinity among 2,829 drug analogs that bind with key active-site residues; these residues are considered for protein-ligand binding and unbinding pathways via steered molecular dynamics simulations. Arg215 in the model plays an important role in the stability of the protein-ligand complex via a hydrogen bonding interaction by aromatic-π contacts, and the ADMET (absorption, distribution, metabolism, and excretion) analysis of best leads indicate nontoxic in nature with good potential for drug development.

Molecular designing and in silico evaluation of darunavir derivatives as anticancer agents.

Darunavir is a synthetic nonpeptidic protease inhibitor which has been tested for anticancer properties. To deduce and enhance the anticancer activity of the Darunavir, we have modified its reactive moiety in an effective way. We designed 9 analogues in ChemBioOffice 2010 and minimized using the LigPrep tool of Schrödinger 2011. These analogues can obstruct the activity of other signalling pathways which are implicated in many tumors. Results of the QikProp showed that all the analogues lied in the specified range of all the pharmacokinetic (ADMET) properties required to become the successful drug. Docking study was performed to test its anticancer activity against the biomarkers of the five main types of cancers i.e. bone, brain, breast, colon and skin cancer. Grid was generated for each oncoproteins by specifying the active site amino acids. The binding model of best scoring analogue with each protein was assessed from their G-scores and disclosed by docking analysis using the XP visualizer tool. An analysis of the receptor-ligand interaction studies revealed that these nine Darunavir analogues are active against all cancer biomarkers and have the features to prove themselves as anticancer drugs, further to be synthesized and tested against the cell lines.

Comparison and correlation of binding mode of ATP in the kinase domains of Hexokinase family.

Hexokinases (HKs) are the enzymes that catalyses the ATP dependent phosphorylation of Hexose sugars to Hexose-6-Phosphate (Hex-6-P). There exist four different forms of HKs namely HK-I, HK-II, HK-III and HK-IV and all of them share a common ATP binding site core surrounded by more variable sequence that determine substrate affinities. Although they share a common binding site but they differ in their kinetic functions, hence the present study is aimed to analyze the binding mode of ATP. The analysis revealed that the four ATP binding domains are showing 13 identical, 7 similar and 6 dissimilar residues with similar structural conformation. Molecular docking of ATP into the kinase domains using Molecular Operating Environment (MOE) soft ware tool clearly showed the variation in the binding mode of ATP with variable docking scores. This probably explains the variable phosphorylation rates among hexokinases family.

CGMD: An integrated database of cancer genes and markers

Integrating cancer genes and markers with experimental evidence might provide valuable information for the further investigation of crosstalk between tumor genes and markers in cancer biology. To achieve this objective, we developed a database known as the Cancer Gene Marker Database (CGMD), which integrates data on tumor genes and markers based on experimental evidence. The major goal of CGMD is to provide the following: 1) current systematic treatment approaches and recent advances in different cancer treatments; 2) the aggregation of different genes and markers by their molecular characteristics and pathway associations; and 3) free access to the data compiled by CGMD at http://cgmd.in/. The database consists of 309 genes and 206 markers, as well as a list of 40 different human cancers, with detailed descriptions of all characterized markers. CGMD provides complete cancer annotations and molecular descriptions of cancer genes and markers such as CpG islands, promoters, exons, PDB structures, active sites and domains.

Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M

Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis.

Identification of Microbial Pathogens in Periodontal disease and Diabetic patients of South Indian Population

Periodontitis have been referred to as the sixth complication of diabetes found in high prevalence among diabetic patients than among healthy controls. The aim of the present study was to examine the periodontal disease status among collected dental plaque samples. Chromosomal DNA was isolated and amplified by universal primers. The DNA was sequenced for bacterial confirmation and phylogenetic analysis performed for the evolutionary relationship with other known pathogens. No amplification products were observed in groups labeled non periodontal and non Diabetes (NP&ND) and non Periodontal and Diabetes (NP&D). But in the case of Periodontal and non Diabetes (P&ND) groups 22 amplified products were observed. In case of Periodontal and Diabetes (P&D), 32 amplified products were positive for microbes. Among the four microbial groups, Treponemadenticola, and Tannerella forsythia were found to be prevalent in P&D. The phylogenetic analysis of 16s rRNA of Treponemadenticola showed the relationship with other Treponema oral pathogen species and with the Spirochaetazuelaera. Tannerella forsythia shows its evolutionary relationship only with four oral pathogens (Macellibacteroidesfermentans, Porphyromadaceae bacterium, Parabacteroidesmeredae and Bacillus fosythus). Prevotellaintermedia also showed its evolutionary relationship only with Prevotella Spcs while Fusobacterium revealed close evolutionary relationship only with Porpiromonasgingivalis.

Comparison and correlation of Simple Sequence Repeats distribution in genomes of Brucella species

Computational genomics is one of the important tools to understand the distribution of closely related genomes including simple sequence repeats (SSRs) in an organism, which gives valuable information regarding genetic variations. The central objective of the present study was to screen the SSRs distributed in coding and non-coding regions among different human Brucella species which are involved in a range of pathological disorders. Computational analysis of the SSRs in the Brucella indicates few deviations from expected random models. Statistical analysis also reveals that tri-nucleotide SSRs are overrepresented and tetranucleotide SSRs underrepresented in Brucella genomes. From the data, it can be suggested that over expressed tri-nucleotide SSRs in genomic and coding regions might be responsible in the generation of functional variation of proteins expressed which in turn may lead to different pathogenicity, virulence determinants, stress response genes, transcription regulators and host adaptation proteins of Brucella genomes. Abbreviations SSRs - Simple Sequence Repeats, ORFs - Open Reading Frames.