FrameOUT and FrameOUTDB: A web based application and repository for the identification and analysis of frameshift mutations

Frameshift, one of the three classes of recoding, leads to waste of energy, resources and activity of biosynthetic machinery. In addition, some peptides, probably cycotoxic synthesized after frameshifts, results in diseases and disorders like muscular dystrophies, lysosomal storage disorders, and cancer. Hidden Stop Codons that occur naturally in coding sequences among all organisms, are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frame-shift events. Hidden stop codons and their association with numerous diseases. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frame-shift events. There are lots of appearances of hidden stops in mitochondrial genomes and we tried to study this putative event in mitochondrial genomes of vertebrates. To reduce this gap, this work presents an algorithmic web based tool to study hidden stops in frame-shifted translation for vertebrate mitochondrial genomes through respective genetic code system. FrameOUT (FO), an algorithmic web based application, predicts mutations in a user input sequence, be it a diseased or a normal sequence by implementation of Hidden Markov Model. FODB is a collection of all available Frameshift events and their association with various diseases

A Mathematical Model of Central Dogma of Molecular Biology employing a Novel Irrational-Integral-Imaginary (i3) Encoding and Numerical Approximation based on Cellular Automaton

Cellular Automaton (CA) is usually used to model the spatio-temporal evolution of dynamical systems. In this work, a special class of the same known as 'Outer-totalistic' Cellular Automaton is applied to examine if there is a rationale behind the correlation between 64 possible codons and the resulting 20 amino-acids. Also, an attempt is made to mathematically model the central dogma of molecular biology in an intelligible format, including transcription and translation. Results suggest that our irrational-integral-imaginary (i3) encoding approach forms not only a satisfactory basis for a mathematical model of translation of mRNA to protein but also that of transcription from ssDNA (single stranded DNA) to mRNA (messenger RNA)

Molecular modelling, docking and interaction studies of human-plasmogen and salmonella enolase with enolase inhibitors

Salmonella enteric serovar Typhi Ty2 is a human specific pathogen and an etiological agent for typhoid fever. Most of Salmonella serotypes produce glycogen which has a comparatively minor role in virulence and colonization, but has a more significant role in survival. Enzymes present in glycolytic pathway of bacteria help bacteria to survive by activating other factors inside host. Numerous pathogenic bacteria species intervene with the plasminogen system, and this plasminogen–enolase association may play a critical role in the virulence of S. Typhi by causing direct damage to the host cell extracellular matrix, possibly by enzymic degradation of extracellular matrix proteins or other protein constituents. In this study, molecular modelling of enolase of Salmonella has been accomplished in silico by comparative modelling; we have then analyzed Human alpha enolase which is a homodimer and serves on epithelial cells with our model. Both Structures were docked by D-tartronate semialdehyde phosphate (TSP) and 3-aminoenolpyruvate phosphate (AEP) enolase inhibitors. Our study shows that salmonella enolase and human enolase have different active sites in their structure. This will help in development of new ligands, more suitable for inhibiting bacterial survival inside host as vaccines for typhoid fever are not fully protective. The study also confirmed that enolase Salmonella and Human Plasminogen suggested direct physical interaction between both of them as the activation loop of plasminogen residues showed conformational changes similar to the tissue type plasminogen activator. Various computational biology tools were used for our present study such as Modeller, Molegro Virtual Docker, Grommacs

SMDB: Soybean Marker DataBase

Soybean Marker Database (SMDB) is a repository of important genomic information for soybean. At present several genomic databases are available for plants. Some of the important oilseeds plant databases are ATPID database, Castor Bean Genome Database, CGPDB, SoyBase, Legume Information System (LIS), Brassica database, Sinbase, etc. To gain comprehensive information from varied amount of resources, we developed  this database which provides general as well as specific information at universal level. Along with this it also furnishes gene level information for various functional categories such as transcription factor, disease resistant varieties, heat shock protein, genetically modified strain of soybean. The bunch of information available to researchers today increases in tremendous manner. Hence understanding the plant genome specific databases for acquiring specific information is the demand of time for crop improvement and  research programmes. SMDB is designed for the purpose of exploring potential gene differences in different plant genotypes, including genetically modified and disease resistant crops beneficial to the farmer who cultivate this crop. SMDB is publicly accessible for academic and research purpose at: http://www.bioinfoindia.org/smdb/

MatSAM: a Matlab implementation for Significance Analysis of Microarrays

Microarray experiments enable the simultaneous measure of expression levels of large amount of genes and have many applications. A widespread one is finding set of genes that are differentially expressed. Significance Analysis of Microarrays (SAM) helps to produce those sets using multiple testing techniques. There is unfortunately not yet a public tool enabling to do SAM using the Matlab platform. We here define MatSAM, a SAM implementation in Matlab, and show that it yields results of high confidence comparatively to those obtained by putative tools available in the R programming environment. MatSAM can be used in conjunction with Matlab Bioinformatics toolbox to perform further analysis.Availability: MatSAM is available as source code at  http://www.bioinfoindia.org/MatSA

Tunicate mitogenomics and phylogenetics: peculiarities of the Herdmania momus mitochondrial genome and support for the new chordate phylogeny

International audienceBACKGROUND: Tunicates represent a key metazoan group as the sister-group of vertebrates within chordates. The six complete mitochondrial genomes available so far for tunicates have revealed distinctive features. Extensive gene rearrangements and particularly high evolutionary rates have been evidenced with regard to other chordates. This peculiar evolutionary dynamics has hampered the reconstruction of tunicate phylogenetic relationships within chordates based on mitogenomic data. RESULTS: In order to further understand the atypical evolutionary dynamics of the mitochondrial genome of tunicates, we determined the complete sequence of the solitary ascidian Herdmania momus. This genome from a stolidobranch ascidian presents the typical tunicate gene content with 13 protein-coding genes, 2 rRNAs and 24 tRNAs which are all encoded on the same strand. However, it also presents a novel gene arrangement, highlighting the extreme plasticity of gene order observed in tunicate mitochondrial genomes. Probabilistic phylogenetic inferences were conducted on the concatenation of the 13 mitochondrial protein-coding genes from representatives of major metazoan phyla. We show that whereas standard homogeneous amino acid models support an artefactual sister position of tunicates relative to all other bilaterians, the CAT and CAT+BP site- and time-heterogeneous mixture models place tunicates as the sister-group of vertebrates within monophyletic chordates. Moreover, the reference phylogeny indicates that tunicate mitochondrial genomes have experienced a drastic acceleration in their evolutionary rate that equally affects protein-coding and ribosomal-RNA genes. CONCLUSION: This is the first mitogenomic study supporting the new chordate phylogeny revealed by recent phylogenomic analyses. It illustrates the beneficial effects of an increased taxon sampling coupled with the use of more realistic amino acid substitution models for the reconstruction of animal phylogeny