Abstract

About 14% of the protein sequences in the Swissprot database contain repetitive region, viz., tandem repeats, multiple copies of motifs/profiles, multiple copies of domain. And eukaryotic proteins are more likely to have repeats than Bacteria and Archaea. Our main focus is only on tandem repeats. Tandem repeat can be defined as contiguous repeat pattern of two or more copies. These copies can be exact or approximate. Many proteins with these repeat are involved in functions like transcription, translation, protein-protein interaction. Proteins with tandem repeats are involved in various neurodegenerative diseases like Huntington's disease. These proteins are also found to occur in sequences which are poorly conserved in evolution. We have developed a database of tandem repeats in protein sequences: Protein Tandem Repeats DataBase(PTRDB). The data for this database is extracted using our in-house tool PEPPER, a tool for identifying PEPtide PEriodic Repeats. This database is built on SwissProt (ver 51.7). PTRDB have 3145 proteins with 4713 tandem repeats. 77.74% are found in Eukaryota, 16.63% in Bacteria and 0.67% in Archaea. About 5% of proteins in this database are associated with disease. We have classified the database organism wise. This database can be queried by various attributes like SwissProt ID, organism name, PDBID, repeat pattern, repeat length, keyword and copy number. It gives the detail information of tandem repeats like SwissProt ID (hyperlinked to SwissProt to give Fasta sequence), organism name, PDBID (hyperlinked to PDB), one line description of the protein, gene name, protein name, taxonomy ID (hyperlinked to EBI), Family information (hyperlinked to Pfam), Description of associated disease, OMIM ID, scoring matrix with gap extension for the repeat, repeat pattern with alignment score, copy number, repeat length, start point, end point, alignment of repeat pattern with repeat region, secondary structure information of the repeat region. With the increasing abundance of tandem protein repeats in various proteomes this database will be increasingly important in proteome comparison.

Abstract

Recently much attention is being focused on the analysis of the three dimensional structure of proteins using graph and network concepts. The simplest protein network graph is constructed by defining the amino acids as nodes and the edges drawn between amino acids (within a threshold) which attempt to capture not only covalent but also non-covalent interactions. Analysis of the topological details of proteins with known structures, such as clustering of specific types of amino acids important for structure, folding and function, is of great value and is an active field of research. Since structures of a large number of proteins is now available, automatic methods of analysis are required to analyze them and recently, the tools from graph theory are being explored for such analysis. Here, we propose to use graph properties and their spectral analysis for identifying patterns in protein structures, in particular, structural repeats or motifs. These repeats are not easily detectable at the sequence level because of low conservation or high divergence between independent repeated units. The importance of such repeats in understanding biological function resides not only in their high frequency among known sequences, but also in their abilities to confer multiple binding and structural roles on proteins, e.g., zinc finger domain, a constituent of transcription factors involved in DNA binding, where the composition and copy number of individual tandem repeats confers selectivity and activity of DNA binding. This functional versatility is apparent not only among different repeat types, but also for similar repeats from the same family. Our understanding of repeats, with respect to their structures, functions, and evolution, therefore represents a considerable challenge. Our analysis of the degree distribution and spectral analysis of a set of proteins from various repeat families show that the repeat regions exhibit similar connectivity patterns in the graph. The network property, Betweenness, was found to identify accurately the repeat boundaries in protein families. Thus, this approach can help in identifying repeated motifs in proteins which are difficult to identify at the sequence level.

Abstract

The ultimate goal of molecular cell biology is to understand the physiology of living cells in terms of the information that is encoded in the genome of the cell and we would like to address the question how computational biology can help in achieving this goal. Genes coding for proteins is a very important pattern recognition problem in bioinformatics and this lecture focuses on some computational issues in gene identification.

Abstract

Most natural spatiotemporal systems are an organized ensemble of dynamical subsystems whose behaviour is regulated by nonlinearly coupled multi-variable processes. The response of each of these variables and/or combinations of them to any single or composite external perturbation can influence its spatiotemporal behaviour in a complex and non-intuitive manner. This paper attempts to study the dynamical response of two coupled map lattice systems having local dynamics described by (a) coupled discrete maps, and (b) coupled differential equations, to external perturbation (or “pinning”) applied to each variable individually or simultaneously. We show that the response of different variables to external pinning is quite different. Our results indicate that, though this pinning approach is useful in controlling complex dynamics both globally and locally, enhancing complexity in dynamics (“anti-control”) is …