MOTIVATION: Viruses, from the human protein-protein interaction network perspective, target hubs, bottlenecks and interconnected nodes enriched in certain biological pathways. However, not much is known about the general characteristic features of the human proteins interacting with viral proteins (referred to as hVIPs) as well as the motifs and domains utilized by human-virus protein-protein interactions (referred to as Hu-Vir PPIs). RESULTS: Our study has revealed that hVIPs are mostly disordered proteins, whereas viral proteins are mostly ordered proteins. Protein disorder in viral proteins and hVIPs varies from one subcellular location to another. In any given viral-human PPI pair, at least one of the two proteins is structurally disordered suggesting that disorder associated conformational flexibility as one of the characteristic features of virus-host interaction. Further analyses reveal that hVIPs are (i) slowly evolving proteins, (ii) associated with high centrality scores in human-PPI network, (iii) involved in multiple pathways, (iv) enriched in eukaryotic linear motifs (ELMs) associated with protein modification, degradation and regulatory processes, (v) associated with high number of splice variants and (vi) expressed abundantly across multiple tissues. These aforementioned findings suggest that conformational flexibility, spatial diversity, abundance and slow evolution are the characteristic features of the human proteins targeted by viral proteins. Hu-Vir PPIs are mostly mediated via domain-motif interactions (DMIs) where viral proteins employ motifs that mimic host ELMs to bind to domains in human proteins. DMIs are shared among viruses belonging to different families indicating a possible convergent evolution of these motifs to help viruses to adopt common strategies to subvert host cellular pathways. AVAILABILITY AND IMPLEMENTATION: Hu-Vir PPI data, DDI and DMI data for human-virus PPI can be downloaded from http://cdfd.org.in/labpages/computational_biology_datasets.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Microsatellites, also known as simple sequence repeats, are the tandem repeats of nucleotide motifs of the size 1-6 bp found in every genome known so far. Their importance in genomes is well known. Microsatellites are associated with various disease genes, have been used as molecular markers in linkage analysis and DNA fingerprinting studies, and also seem to play an important role in the genome evolution. Therefore, it is of importance to study distribution, enrichment and polymorphism of microsatellites in the genomes of interest. For this, the prerequisite is the availability of a computational tool for extraction of microsatellites (perfect as well as imperfect) and their related information from whole genome sequences. Examination of available tools revealed certain lacunae in them and prompted us to develop a new tool. RESULTS: In order to efficiently screen genome sequences for microsatellites (perfect as well as imperfect), we developed a new tool called IMEx (Imperfect Microsatellite Extractor). IMEx uses simple string-matching algorithm with sliding window approach to screen DNA sequences for microsatellites and reports the motif, copy number, genomic location, nearby genes, mutational events and many other features useful for in-depth studies. IMEx is more sensitive, efficient and useful than the available widely used tools. IMEx is available in the form of a stand-alone program as well as in the form of a web-server. AVAILABILITY: A World Wide Web server and the stand-alone program are available for free access at http://203.197.254.154/IMEX/ or http://www.cdfd.org.in/imex.

MOTIVATION: Fold recognition is a key step in the protein structure discovery process, especially when traditional sequence comparison methods fail to yield convincing structural homologies. Although many methods have been developed for protein fold recognition, their accuracies remain low. This can be attributed to insufficient exploitation of fold discriminatory features. RESULTS: We have developed a new method for protein fold recognition using structural information of amino acid residues and amino acid residue pairs. Since protein fold recognition can be treated as a protein fold classification problem, we have developed a Support Vector Machine (SVM) based classifier approach that uses secondary structural state and solvent accessibility state frequencies of amino acids and amino acid pairs as feature vectors. Among the individual properties examined secondary structural state frequencies of amino acids gave an overall accuracy of 65.2% for fold discrimination, which is better than the accuracy by any method reported so far in the literature. Combination of secondary structural state frequencies with solvent accessibility state frequencies of amino acids and amino acid pairs further improved the fold discrimination accuracy to more than 70%, which is approximately 8% higher than the best available method. In this study we have also tested, for the first time, an all-together multi-class method known as Crammer and Singer method for protein fold classification. Our studies reveal that the three multi-class classification methods, namely one versus all, one versus one and Crammer and Singer method, yield similar predictions. AVAILABILITY: Dataset and stand-alone program are available upon request.

AmpliBASE MT is an online databank of high-resolution DNA fingerprints representing fluorescent amplified fragment length polymorphism (FAFLP) profiles or amplitypes developed for the Mycobacterium tuberculosis complex strains from 48 different countries. AmpliBASE MT is based on a relational database management system that is hyperlinked to visualize genotyping results in the form of DNA fingerprint images for individual strains. A flexible search system based on systematic comparisons of fragment sizes in base pairs allows inter-laboratory comparison of FAFLP profiles. Besides this, the database also displays previously published data on IS6110 profiles, spoligotypes, MIRU-VNTRs and large sequence polymorphisms along with the FAFLP records that will give the overall comparisons. Being the first of its kind, AmpliBASE MT is expected to be a very helpful tool in strengthening the concept of 'geographic genomics' and will be very helpful to molecular epidemiologists and those interested in diagnostic development for tuberculosis.