Koel Mukherjee

SVM based model generation for binding site prediction on helix turn helix motif type of transcription factors in eukaryotes.

Support vector machine is a class of machine learning algorithms which uses a set of related supervised learning methods for classification and regression. Nowadays this method is vividly applied to many detection problems related with secondary structure, tumor cell and binding residue prediction. In this work, support vector machines (SVMs) have been trained on 90 sequences of transcription factors with HTH motif. Four sequence features were used as attribute for the prediction of interaction site in HTH motif. A web page was also developed so that user can easily enter the protein sequence and receive the output as interaction site predicted or not predicted. The generated model shows a very high amount of accuracy, sensitivity and specificity which proves to be a good model for the selected case.

Molecular Dynamics Simulation of Rap1 Myb-type domain in Saccharomyces cerevisiae

Telomere is a nucleoprotein complex that plays important role in stability and their maintenance and consists of random repeats of species specific motifs. In budding Saccharomyces cerevisiae, Repressor Activator Protein 1 (Rap1) is a sequence specific protein that involved in transcriptional regulation. Rap1 consist of three active domains like N-terminal BRCT-domain, DNA-binding domain and C-terminal RCT-domain. In this study the unknown 3D structure of Myb-type domain (having 61 residues) within DNAbinding domain was modeled by Modeller7, and verified using different online bioinformatics tools (ProCheck, WhatIf, Verify3D). Dynamics of Myb-type domain of Rap1was carried out through simulation studies using GROMACS software. Time dependent interactions among the molecules were analyzed by Root Mean Square Deviation (RMSD), Radius of Gyration (Rg) and Root Mean Square Fluctuation (RMSF) plots. Motional properties in reduced dimension were also performed by Principal Component Analysis (PCA). Result indicated that Rap1 interacts with DNA major groove through its Helix Turn Helix motifs. Helix 3 was rigid, less amount of fluctuation was found as it interacts with DNA major groove. Helix2 and N-terminal having considerable fluctuation in the time scale.

Molecular aspect of silver nanoparticles regulated embryonic development in Zebrafish ( Danio rerio) by Oct-4 expression

With the enhancement of commercial manifestation of silver nanoparticles, concerned has risen on their accumulation in aquatic system and consequent effects on fish development and metabolism. In this study, experiments were conducted to assess the impacts of silver nanoparticles on early life cycles of fish considering Zebrafish (Danio rerio) as experimental model. Silver nanoparticles were synthesized through chemical reduction method and characterized through UV-visible spectroscopy, dynamic light scattering (DLS), and HR-TEM. Different sub lethal doses of nanosilver were applied (13.6, 21.6, 42.4, 64, and 128 μgL-1) to post-fertilization phases of Zebrafish embryos and their interaction effects were monitored up to six days period. No significant morphological variations were observed at 13.6, 21.6, 42.4 μgL-1 dose of silver nanoparticles, whereas 64 and 128 μgL-1 exposure dose exhibited bending in myotome, deformity in tail region, somites, notochord and swelling in anterior and posterior region of embryos and larva. Hatching performances analysis elicited highest hatching success in 13.6 and 21.6 μgL-1 doses of silver nanoparticles followed by positive and negative control, whereas exposure dose of 64 and 128 μgL-1 exhibited comparatively lower success. Western blot analysis were conducted on developing hatchlings with Oct4 antibody and at 13.6 and 21.6 μgL-1dose,it showed over expression elucidating stimulatory role of nanosilver in these mentioned doses. In silico analysis depicted a firm interaction of nanosilver with Oct4 revealing their key role in growth stimulation of developing embryos. The study demonstrates the function of nanosilver as a growth promoter rather only as a toxicant in fish metabolic system.

3D Structure Modeling of Human Telomere Repeat Binding Factor 2 and DNA-Protein Docking Studies

Aims: Human telomere repeat binding factor (hTRF2) is a double stranded telomere binding protein that plays key role in protecting the chromosome ends and a necessary building block of telomere structure maintenance. The aim of the present study was to focus on the modeling of 3D structure of hTRF2 (500 residues long) and its interaction studies with DNA in silico. Study Design: The overall work was designed in different steps starting with the modeling of the concerned protein, its physiochemical properties study, modeling of 3DDNA with specific length and varying bend angle, docking studies of modeled DNA and hTRF2 protein. Place and Duration of Study: Bioinformatics Lab, Department of Biotechnology, Birla Institute of Technology, Mesra, India. November 2012July 2013. Methodology: 3D structure of hTRF2 was modeled through I-TASSER method. The modeled structure was verified by 5ns of simulation run in solvent (water) condition and also evaluated with different bioinformatics tools. Physiochemical properties were calculated through CLC Protein Workbench. DNA 3D structure was modeled with the conserved nucleotide sequence motif, TTAGGG with varying bend angles of 0° to 60°. The DNA-protein docking studies were carried out through HADDOCK easy interface for Original Research Article British Biotechnology Journal, 4(1): 81-95, 2014 82 each bend angle. Results: The best model was selected depending on minimum RMSD value and C-Score and the Stereochemical quality of that model was verified with different tools, as the Molprobity score (>1) of hTRF2 was predicted 4.2 and Ramachandra favored residue was 80.56%. The selected model protein and DNA structure was docked and among all the docking results the best orientation of DNA and hTRF2 was at 60° DNA bend angle with lowest RMSD and maximum Z-value. The amino acids which are directly involved in the interaction were also selected. Conclusion: In future further study will be planned with further bend angle for getting better information on DNA-protein interactions. In silico studies will also be helpful for the researchers to study the complex structure in vitro.

Synthesis of silver nanoparticles by Bacillus clausii and computational profiling of nitrate reductase enzyme involved in production

Biogenic synthesis of silver nanoparticles using microorganisms has found interest recently since last decade because of their prospect to synthesize nanoparticles of various size, shape and morphology which are eco-friendly. Here, an eco-friendly method for production of silver nanoparticles from Bacillus clausii cultured from Enterogermina is explored. Along with the biosynthesis and conformity test, in silico studies was done on NADPH dependent nitrate reductase enzymes from the view point of designing a rational enzymatic strategy for the synthesis. The detailed characterization of the nanoparticles was carried out using UV-Vis spectroscopy, Dynamic Light Scattering (DLS) particle size analysis, Transmission Electron Microscopy (TEM), X-Ray Diffraction (XRD) analysis. Computational profiling and in silico characterization of NADH dependent enzymes was carried out based on literature and work done so far. Nitrate reductase sequence was retrieved from NCBI for characterization. Secondary structure was evaluated and verified by JPred as well as SOPMA Tool. Tertiary structure was also modeled by MODELLER and ITASSER parallel and the best structure was selected based on energy values. Structure validation was done by GROMACS and RMSD, RMSF, temperature variation plot were also plotted. Interactions graphs between nitrate reductase and ligand silver nitrate was done through molecular docking using Hex.

Identification and Screening of Potent Inhibitors Against Spore Wall Proteins of Flacherie Infected Bombyx mori Through Molecular Modeling and Docking Studies

Sericulture or cultivation of silkworms is practiced in India and other Asian countries since time immemorial. The mulberry silkworm, Bombyx mori are affected by viral, fungal and protozoan pathogens, which causes huge monetary loss. Among many other diseases, Flacherie is the most rampant in the silkworm community causing flaccidity and subsequent death. Previous studies indicate Andrographolide, Quercitin and chitosan are the active compounds from the extracts of Andrographis paniculata and Tridax procumbens to be effective against the flacherie pathogens. The main aim of the following work depends on the screening and selecting of the potent inhibitor against the spore wall proteins of flacherie-infected B. mori. In this study, two wall proteins were selected from flacherie-infected mulberry silkworm, the 3D structures were modeled through Modeller 9.15. Eventually the modeled structures were docked with reference inhibitors (three best reference) using GLIDE suite of Maestro 9.3.5. The best one among the three references was identified and selected for the screening of next set of inhibitors (50 inhibitors) with a structural similarity of 70, 80 and 90%. They were again docked in the same active region of the targets and identified as the best reference inhibitor. The result shows a promising potent inhibitor which can be further validated by experimental procedures.

Gene Expression Profiling of Cervical Cancer Using Statistical Method

Cervical cancer is accountable for numerous cancer-related deaths in women worldwide. Cancer causes molecular alterations in two types of genes with opposing functions, proto-oncogenes and tumor suppressor genes (TSG), respectively. Proto-oncogenes stimulate cell growth and hinder apoptosis, whereas TSGs inhibit growth and maintain the cell integrity. Deregulation of both types of genes may change the growth and division of cells, leading to a tumorigenic transformation. Thus we aim to study the gene expression of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The data were selected and retrieved from TCGA data portal. A list of 12 driver genes responsible for causing cervical cancer was found. A code in R was written to find the correlation of these driver genes with the cancer genes by Spearman’s method. Different statistical methods were applied to calculate the significantly co-expressed genes. Co-express pathways were also identified by DAVID.