Proline-containing β-turns in peptides and proteins. II. Physicochemical studies on tripeptides with the Pro-Gly sequence

Amino acids are known to differ in their individual preferences for each of the four positions of the β-turn conformation formed by tetrapeptide segments. Proline and glycine show relatively high preferences for positions 2 and 3, respectively, of the β-turn. Using tripeptides of the type N-acetyl-Pro-Gly-X-OH, where X = Gly, Ala, Leu, Ile, and Phe, we have sought to study the influence of the 4th residue X on the stability of the β-turn conformation in these tripeptides. Our nmr and CD results show that the β-turn stability is quite significantly governed by the nature of the amino acid residue at this position in the following order: Leu > Ala > Ile, Gly > Phe.     

CoPS: Comprehensive Peptide Signature database

We present the development of a Comprehensive database of 12 076 invariant Peptide Signatures (CoPS) derived from 52 bacterial genomes with a minimum occurrence in at least seven organisms. These peptides were observed in functionally similar proteins and are distributed over nearly 1250 different functional proteins. The database provides function, structure and occurrence in biochemical pathways of the proteins containing these signature peptides. It houses additional information on the signature peptides, such as identical match in other motif/pattern (e.g. PROSITE, BLOCKS, PRINTS and Pfam) databases and the database of interacting proteins, human proteome and mutation effect on these signature peptides. There is a wide applicability of this database in the identification of critical functional residues in proteins. The database also facilitates the identification of folding nucleus/structural determinants in proteins and functional assignment to yet unknown proteins. We demonstrate functional assignment to 2605 hypothetical proteins in bacterial genomes and 112 unknown proteins in human using this database. AVAILABILITY: The database can be freely accessed through the following URL: http://203.195.151.46/copsv2/index.html or http://203.90.127.70/copsv2/index.html     

L<Subscript>2</Subscript>-norm multiple kernel learning and its application to biomedical data fusion

Background  

This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields different extensions of multiple kernel learning (MKL) such as L _∞, L ₁, and L ₂ MKL. In particular, L ₂ MKL is a novel method that leads to non-sparse optimal kernel coefficients, which is different from the sparse kernel coefficients optimized by the existing L _∞ MKL method. In real biomedical applications, L ₂ MKL may have more advantages over sparse integration method for thoroughly combining complementary information in heterogeneous data sources.     

Comparative analysis of DNA polymorphisms and phylogenetic relationships among Syzygium cumini Skeels based on phenotypic characters and RAPD technique

The Indian black berry (Syzygium cumini Skeels) has a great nutraceutical and medicinal properties. As in other fruit crops, the fruit characteristics are important attributes for differentiation were also determined for different accessions of S. cumini. The fruit weight, length, breadth, length: breadth ratio, pulp weight, pulp content, seed weight and pulp: seed ratio significantly varied in different accessions. Molecular characterization was carried out using PCR based RAPD technique. Out of 80 RAPD primers, only 18 primers produced stable polymorphisms that were used to examine the phylogenetic relationship. A sum of 207 loci were generated out of which 201 loci found polymorphic. The average genetic dissimilarity was 97 per cent among jamun accessions. The phylogenetic relationship was also determined by principal coordinates analysis (PCoA) that explained 46.95 per cent cumulative variance. The two-dimensional PCoA analysis showed grouping of the different accessions that were plotted into four sub-plots, representing clustering of accessions. The UPGMA (r = 0.967) and NJ (r = 0.987) dendrogram constructed based on the dissimilarity matrix revealed a good degree of fit with the cophenetic correlation value. The dendrogram grouped the accessions into three main clusters according to their eco-geographical regions which given useful insight into their phylogenetic relationships.