[show abstract][hide abstract] ABSTRACT: Small RNAs (sRNAs) are non-coding transcripts exerting their functions in the cells directly. Identification of sRNAs is a difficult task due to the lack of clear sequence and structural biases. Most sRNAs are identified within genus specific intergenic regions in related genomes. However, several of these regions remain un-annotated due to lack of sequence homology and/or potent statistical identification tools. A computational engine has been built to search within the intergenic regions to identify and roughly annotate new putative sRNA regions in Enterobacteriaceae genomes. It utilizes experimentally known sRNA data and their flanking genes/KEGG Orthology (KO) numbers as templates to identify similar sRNA regions in related query genomes. The search engine not only has the capability to locate putative intergenic regions for specific sRNAs, but also has the potency to locate conserved, shuffled or deleted gene clusters in query genomes. Because it uses the KO terms for locating functionally important regions such as sRNAs, any further KO number assignment to additional genes will increase the sensitivity. The PsRNA server is used for the identification of putative sRNA regions through the information retrieved from the sRNA of interest. The computing engine is available online at http://bioserver1.physics.iisc.ernet.in/psrna/ and http://bicmku.in:8081/psrna/.
[show abstract][hide abstract] ABSTRACT: Distant repeats in protein sequence play an important role in various aspects of protein analysis. A keen analysis of the distant repeats would enable to establish a firm relation of the repeats with respect to their function and three-dimensional structure during the evolutionary process. Further, it enlightens the diversity of duplication during the evolution. To this end, an algorithm has been developed to find all distant repeats in a protein sequence. The scores from Point Accepted Mutation (PAM) matrix has been deployed for the identification of amino acid substitutions while detecting the distant repeats. Due to the biological importance of distant repeats, the proposed algorithm will be of importance to structural biologists, molecular biologists, biochemists and researchers involved in phylogenetic and evolutionary studies.
[show abstract][hide abstract] ABSTRACT: Ion pairs contribute to several functions including the activity of catalytic triads, fusion of viral membranes, stability in thermophilic proteins and solvent-protein interactions. Furthermore, they have the ability to affect the stability of protein structures and are also a part of the forces that act to hold monomers together. This paper deals with the possible ion pair combinations and networks in 25% and 90% non-redundant protein chains. Different types of ion pairs present in various secondary structural elements are analysed. The ion pairs existing between different subunits of multisubunit protein structures are also computed and the results of various analyses are presented in detail. The protein structures used in the analysis are solved using X-ray crystallography, whose resolution is better than or equal to 1.5 A and R-factor better than or equal to 20%. This study can, therefore, be useful for analyses of many protein functions. It also provides insights into the better understanding of the architecture of protein structure.
Journal of Biosciences 07/2007; 32(4):693-704. · 1.76 Impact Factor
[show abstract][hide abstract] ABSTRACT: The Ramachandran plot displays the main chain conformation angles (Phi and Psi) of the polypeptide chain of a protein molecule. The paper reports the updated version of the Ramachandran plot web server and has several improved options for displaying the conformation angles in various regions. In addition, options are provided to display the conformation angles in various secondary structural elements and regions within the user specified Phi and Psi values in the plot. The updated version is accessible at the following URL: http://dicsoft1.physics.iisc.ernet.in/rp/.
Protein and Peptide Letters 02/2007; 14(7):669-71. · 1.99 Impact Factor