International Journal of Computational Bioinformatics and In Silico Modeling
||Prof. Dr. Hubert G. Schwelberger studied Biochemistry at the Graz University of Technology where he also did his PhD in yeast molecular biology. After post-doctoral studies in translational regulation at the University of California Davis he moved to the Department of Surgery at the Medical University Innsbruck where he is currently head of the Molecular Biology Laboratory. His research interests include histamine metabolism, amine oxidases, tumor biology and organ transplantation. He has published over 70 research papers and several reviews and book chapters.
How to cite: Hubert G. Schwelberger. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 104-105
ABSTRACT: This paper provides an optimal storage algorithm of an effective design and implementation of a distributed bioinformatics computing system for analysis of DNA sequences (OPTSDNA). This system could be used for storing various sizes of DNA sequences into database. DNA sequences of different lengths were stored by using this algorithm. These sequences varied in size from very small to very large. The performance of this storage system is compared with sequential approach.
KeyWords: Distributed Bioinformatics System, DNA Sequence, Optimal Storage, Sequential Approach.
How to cite: Chotan Sheel et. al. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 106-109
ABSTRACT: Protein kinase CK2 is a critical regulator of several cellular and molecular signaling pathways. CK2 is unanimously distributed in eukaryotes and subsists in tetrameric complexes comprising two catalytic alpha and two regulatory beta subunits. Several reports have confirmed that protein kinase CK2 has great significance in diverse biological courses, particularly in cellular growth and proliferation in normal and disease conditions. However, in silico analysis of phosphorylation sites in the catalytic alpha subunit of CK2 remain to be elucidated. We describe the distribution of predicted (neural network predictions for serine (S), threonine (T) and tyrosine(Y)) STY phosphorylation sites in 15 multicellular and 2 unicellular organisms. We also showed the clustering of CK2 alpha subunit in these organisms using a phylogram. This data showed the prevalence of CK2 alpha subunits with potential STY phophorylation sites in several eukaryotic unicellular and mulicellular organisms that could be significant in the context of enigmatic protein kinase activities of CK2, enzyme-substrate interactions, further ligand-binding studies and new therapeutic interventions.
KeyWords: CK2 alpha subunit, protein phosphorylation sites, phylogeny
How to cite: Priyanka Dhar et. al. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 110-114
ABSTRACT: YAP (Yes kinase-associated protein) is a transcriptional coactivator which plays key role in Hippo Signaling pathway. The Hippo pathway controls cell growth, proliferation and apoptosis by regulation of target genes mediated by core pathway proteins. YAP/Yki mediates gene expression by interacting with TEAD family transcription factors. However, YAP-TEAD interaction is also required for oncogenic transformation of cells. Three-dimensional crystal structure of YAP-TEAD complex has revealed extensive molecular details with highly conserved interfaces. The amino terminal domain of YAP in complex with the carboxy terminal domain of TEAD transcription factor provides vital information of molecular complexity. Here, we will review the basic Hippo signalling pathway and role of YAP as an oncogene. We will also discuss about the crystal structure of YAP in complex with TEAD, various molecular interactions between YAP-TEAD, and WW domain of YAP with PPxY motif peptides. Lastly, we will also provide a brief discussion on the implications of in silico analysis on inhibition of YAP-TEAD complex and development of novel anticancer therapeutics. Future directions for the research are outlined.
KeyWords: YAP; TEAD; Hippo; WW domain; PPxY motif; cancer
How to cite: Pooja Purohit et. al. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 115-122
ABSTRACT: Understanding the basic mechanisms of micro RNA control in the cell has been one of the open ended problems in this field of study. Though next generation sequencing has helped us unearth a large number of candidate microRNAs and their possible targets, we still do not know the exact mechanisms by which the production of these microRNAs is actually controlled. MicroRNAs in plants have been well documented to be involved in developmental processes and their expression levels have also been sketched throughout the life cycle of a plant. The upregulation and downregulation of these micro RNA entities provides clear indication that a regulatory network exists for the control of their differential expression. This work focuses on the identification of the regulatory motifs in the precursor sequences using position specific weight matrix based pattern classification algorithm. The candidate microRNA family used for this study is mir156 family which has been reported in a large number of plant species in monocotyledons as well as dicotyledons. Results indicate that regulatory motifs are present in large numbers at the DNA as well as RNA levels. Few motifs were found to be overrepresented.
KeyWords: Position Specific weight matrix, regulatory motifs, microRNA, mir156 family
How to cite: Sayak Ganguli et. al. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 123-127
ABSTRACT: Three periplasmic Sox proteins encoded by the soxBXAK and soxYZ genes are mainly responsible for thiosulfate oxidation in Allochromatium vinosum. Thiosulphate (S2O32–) fulfils an important role in the natural sulphur cycle. It is a stable and environmentally abundant sulphur compound of intermediate oxidation state. Thiosulphate-oxidizing sox enzyme can be classified as two types, type one group forms sulphur globules as intermediate for ex Allochromatium vinosum and another which does not form sulphur globules as intermediate for ex example Paracoccus pantotrophus. It is well documented that thiosulphate oxidation in Allochromatium vinosum is mainly dependent on the presence of three periplasmic Sox proteins encoded by the soxB, soxXAK, and soxYZ genes. So the interactions between SoxXA complexes with soxK are very crucial to understand thiosulphate oxidation in Allochromatium vinosum. In the present work, homology modeling and ab-initio structure prediction have been used to build the three dimensional structures of SoxA, SoxX and SoxK. With the help of protein-protein docking complex structure of SoxAX is formed, The Cluspro 2.0 protein-protein docking and P.I.C server have been used to predict possible interaction between soxAX and soxK protein. The interactions between the SoxAX complex, and SoxK proteins are mediated mainly through hydrogen bonding, hydrophobic interaction, electrostatic interaction.
KeyWords: Homology modeling, Protein-protein interactions, Docking simulations, Environmental sulphur balance, Sox operon, Sulfur oxidation
How to cite: Sujay Ray and Angshuman Bagchi. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 128-131
ABSTRACT: Legionellosis is a potentially fatal infectious disease caused by gram negative aerobic bacteria belonging to the genus Legionella. Over 90% of legionellosis cases are caused by Legionella pneumophila which is a thin, aerobic, pleomorphic, flagellated, non-spore forming bacteria. The emergence of drug resistance of L. pneumophila has led to the search for novel drug targets. In the present research work, computational analysis of metabolic pathways of the bacteria and host was performed to identify novel drug targets non-homologous to Homo sapiens. All enzymes involved in the metabolic pathways of L. pneumophila strain Paris were searched against the proteome of Homo sapiens using the BLASTp program and the threshold of E-value was set to as 0.001. Total 45 unique putative targets were identified and encoding genes of these targets were further searched in the DEG database to recognize the essentiality of genes. It was found that 37 encoding genes were essential for the survival of the pathogen. Among those identified targets, it has been reported in literature that phosphoglyceromutase, phosphoglucosamine mutase and phosphomannomutase enzymes can be used as potential therapeutic drug target. The 3D structure of candidate enzyme phosphoglyceromutase (PGM) was predicted by comparative modeling method using the Swiss model, ModWeb and HHPred servers respectively. The stereochemical qualities of all predicted models were evaluated by the SAVES server. The best quality model was generated by the Swiss model server, which was further subjected to molecular dynamics simulation (MDS) to assess the stability of modeled structure. The MDS was performed at 100 pico second (ps) time scale and in 50000 steps using the Gromacs v4.06 program. The MDS results have shown the significant stability to the modeled structure of PGM. In future modeled structure of PGM might be exploited for the designing of novel inhibitors against L. pneumophila.
KeyWords: Drug target, metabolic pathways, phosphoglyceromutase, modelling, dynamics simulation
How to cite: PK Yadav and HK Pandey. Int J Comput Bioinfo In Silico Model. 2(3) 2013: 132-137