MAAP: malarial adhesins and adhesin-like proteins predictor.

Malaria caused by protozoan parasites belonging to the genus Plasmodium is a dreaded disease, second only to tuberculosis. The emergence of parasites resistant to commonly used drugs and the lack of availability of vaccines aggravates the problem. One of the preventive approaches targets adhesion of parasites to host cells and tissues. Adhesion of parasites is mediated by proteins called adhesins. Abrogation of adhesion by either immunizing the host with adhesins or inhibiting the interaction using structural analogs of host cell receptors holds the potential to develop novel preventive strategies. The availability of complete genome sequence offers new opportunities for identifying adhesin and adhesin-like proteins. Development of computational algorithms can simplify this task and accelerate experimental characterization of the predicted adhesins from complete genomes. A curated positive dataset of experimentally known adhesins from Plasmodium species was prepared by careful examination of literature reports. "Controversial" or "hypothetical" adhesins were excluded. The negative dataset consisted of proteins representing various intracellular functions including information processing, metabolism, and interface (transporters). We did not include proteins likely to be on the surface with unknown adhesin properties or which are linked even indirectly to the adhesion process in either of the training sets. A nonhomology-based approach using 420 compositional properties of amino acid dipeptide and multiplet frequencies was used to develop MAAP Web server with Support Vector Machine (SVM) model classifier as its engine for the prediction of malarial adhesins and adhesin-like proteins. The MAAP engine has six SVM classifier models identified through an exhaustive search from 728 kernel parameters set. These models displayed an efficiency (Mathews correlation coefficient) of 0.860-0.967. The final prediction P(maap) score is the maximum score attained by a given sequence in any of the six models. The results of MAAP runs on complete proteomes of Plasmodium species revealed that in Plasmodium falciparum at P(maap) scores above 0.0, we observed a sensitivity of 100% with two false positives. In P. vivax and P. yoelii an optimal threshold P(maap) score of 0.7 was optimal with very few false positives (upto 5). Several new predictions were obtained. This list includes hypothetical protein PF14_0040, interspersed repeat antigen, STEVOR, liver stage antigen, SURFIN, RIFIN, stevor (3D7-stevorT3-2), mature parasite-infected erythrocyte surface antigen or P. falciparum erythrocyte membrane protein 2, merozoite surface protein 6 in P. falciparum, circumsporozoite proteins, microneme protein-1, Vir18, Vir12-like, Vir12, Vir18-like, Vir18-related and Vir4 in P. vivax, circumsporozoite protein/thrombospondin related anonymous proteins, 28 kDa ookinete surface protein, yir1, and yir4 of P. yoelii. Among these, a few proteins identified by MAAP were matched with those identified by other groups using different experimental and theoretical strategies. Most other interspersed repeat proteins in Plasmodium species had lower P(maap) scores. These new predictions could serve as new leads for further experimental characterization (MAAP webserver: http://maap.igib.res.in).

ARC: automated resource classifier for agglomerative functional classification of prokaryotic proteins using annotation texts.

Functional classification of proteins is central to comparative genomics. The need for algorithms tuned to enable integrative interpretation of analytical data is felt globally. The availability of a general,automated software with built-in flexibility will significantly aid this activity. We have prepared ARC (Automated Resource Classifier), which is an open source software meeting the user requirements of flexibility. The default classification scheme based on keyword match is agglomerative and directs entries into any of the 7 basic non-overlapping functional classes: Cell wall, Cell membrane and Transporters (C), Cell division (D), Information (I), Translocation (L), Metabolism (M), Stress(R), Signal and communication (S) and 2 ancillary classes: Others (O) and Hypothetical (H). The keyword library of ARC was built serially by first drawing keywords from Bacillus subtilis and Escherichia coli K12. In subsequent steps,this library was further enriched by collecting terms from archaeal representative Archaeoglobus fulgidus, Gene Ontology, and Gene Symbols. ARC is 94.04% successful on 6,75,663 annotated proteins from 348 prokaryotes. Three examples are provided to illuminate the current perspectives on mycobacterial physiology and costs of proteins in 333 prokaryotes. ARC is available at http://arc.igib.res.in.

Blood compatibility of novel water soluble hyperbranched polyglycerol-based multivalent cationic polymers and their interaction with DNA.

A novel class of hyperbranched polymers based on polyglycerol (PG) and poly(ethylene glycol) (PEG) are synthesized by multibranching anionic ring opening polymerization. Multivalent cationic sites are added to these polymers by a post-amination and quarternization reactions. Blood compatibility studies using these polymers at different concentrations showed insignificant effects on complement activation, platelet activation, coagulation, erythrocyte aggregation and hemolysis compared to branched cationic polyethyleneimine (PEI). The degree of quarternization does not have large influence on the blood compatibility of the new polymers. Cytotoxicity of these polymers is significantly lower than that of PEI and is a function of quarternized nitrogen present in the polymer. Also, these polymers bind DNA in the nanomolar range and are able to condense DNA to highly compact, stable, water soluble nanoparticles in the range of 60-80 nm. Gel electrophoresis studies showed that they form electroneutral complexes with DNA around N/P ratio 1 irrespective of the percentage of quarternization under the conditions studied.

Simple sequence proteins in prokaryotic proteomes.

BACKGROUND: The structural and functional features associated with Simple Sequence Proteins (SSPs) are non-globularity, disease states, signaling and post-translational modification. SSPs are also an important source of genetic and possibly phenotypic variation. Analysis of 249 prokaryotic proteomes offers a new opportunity to examine the genomic properties of SSPs. RESULTS: SSPs are a minority but they grow with proteome size. This relationship is exhibited across species varying in genomic GC, mutational bias, life style, and pathogenicity. Their proportion in each proteome is strongly influenced by genomic base compositional bias. In most species simple duplications is favoured, but in a few cases such as Mycobacteria, large families of duplications occur. Amino acid preference in SSPs exhibits a trend towards low cost of biosynthesis. In SSPs and in non-SSPs, Alanine, Glycine, Leucine, and Valine are abundant in species widely varying in genomic GC whereas Isoleucine and Lysine are rich only in organisms with low genomic GC. Arginine is abundant in SSPs of two species and in the non-SSPs of Xanthomonas oryzae. Asparagine is abundant only in SSPs of low GC species. Aspartic acid is abundant only in the non-SSPs of Halobacterium sp NRC1. The abundance of Serine in SSPs of 62 species extends over a broader range compared to that of non-SSPs. Threonine(T) is abundant only in SSPs of a couple of species. SSPs exhibit preferential association with Cell surface, Cell membrane and Transport functions and a negative association with Metabolism. Mesophiles and Thermophiles display similar ranges in the content of SSPs. CONCLUSION: Although SSPs are a minority, the genomic forces of base compositional bias and duplications influence their growth and pattern in each species. The preferences and abundance of amino acids are governed by low biosynthetic cost, evolutionary age and base composition of codons. Abundance of charged amino acids Arginine and Aspartic acid is severely restricted. SSPs preferentially associate with cell surface and interface functions as opposed to metabolism, wherein proteins of high sequence complexity with globular structures are preferred. Mesophiles and Thermophiles are similar with respect to the content of SSPs. Our analysis serves to expand the commonly held views on SSPs.