HORI: a web server to compute Higher Order Residue Interactions in protein structures.

BACKGROUND: Folding of a protein into its three dimensional structure is influenced by both local and global interactions within a protein. Higher order residue interactions, like pairwise, triplet and quadruplet ones, play a vital role in attaining the stable conformation of the protein structure. It is generally agreed that higher order interactions make significant contribution to the potential energy landscape of folded proteins and therefore it is important to identify them to estimate their contributions to overall stability of a protein structure. RESULTS: We developed HORI [Higher order residue interactions in proteins], a web server for the calculation of global and local higher order interactions in protein structures. The basic algorithm of HORI is designed based on the classical concept of four-body nearest-neighbour propensities of amino-acid residues. It has been proved that higher order residue interactions up to the level of quadruple interactions plays a major role in the three-dimensional structure of proteins and is an important feature that can be used in protein structure analysis. CONCLUSION: HORI server will be a useful resource for the structural bioinformatics community to perform analysis on protein structures based on higher order residue interactions. HORI server is a highly interactive web server designed in three modules that enables the user to analyse higher order residue interactions in protein structures. HORI server is available from the URL: http://caps.ncbs.res.in/hori.

An improved hypergeometric probability method for identification of functionally linked proteins using phylogenetic profiles.

Predicting functions of proteins and alternatively spliced isoforms encoded in a genome is one of the important applications of bioinformatics in the post-genome era. Due to the practical limitation of experimental characterization of all proteins encoded in a genome using biochemical studies, bioinformatics methods provide powerful tools for function annotation and prediction. These methods also help minimize the growing sequence-to-function gap. Phylogenetic profiling is a bioinformatics approach to identify the influence of a trait across species and can be employed to infer the evolutionary history of proteins encoded in genomes. Here we propose an improved phylogenetic profile-based method which considers the co-evolution of the reference genome to derive the basic similarity measure, the background phylogeny of target genomes for profile generation and assigning weights to target genomes. The ordering of genomes and the runs of consecutive matches between the proteins were used to define phylogenetic relationships in the approach. We used Escherichia coli K12 genome as the reference genome and its 4195 proteins were used in the current analysis. We compared our approach with two existing methods and our initial results show that the predictions have outperformed two of the existing approaches. In addition, we have validated our method using a targeted protein-protein interaction network derived from protein-protein interaction database STRING. Our preliminary results indicates that improvement in function prediction can be attained by using coevolution-based similarity measures and the runs on to the same scale instead of computing them in different scales. Our method can be applied at the whole-genome level for annotating hypothetical proteins from prokaryotic genomes.

HORIBALFRE program: Higher Order Residue Interactions Based ALgorithm for Fold REcognition.

Understanding the functional and structural implication of a protein encoded in novel genes using function association or fold recognition approaches remains to be a challenging task in the current era of genomes, metagenomes and personal genomes. In an attempt to enhance potential-based fold-recognition methods in recognizing remote homology between proteins, we propose a new approach "Higher Order Residue Interaction Based ALgorithm for Fold REcognition (HORIBALFRE)". Higher order residue interactions refer to a class of interactions in protein structures mediated by C(α) or C(ß) atoms within a pre-defined distance cut-off. Higher order residue interactions (pairwise, triplet and quadruplet interactions) play a vital role in attaining the stable conformation of a protein structure. In HORIBALFRE, we incorporated the potential contributions from two body (pairwise) interactions, three body (triplet interactions) and four-body (quadruple interaction) interactions, to implement a new fold recognition algorithm. Core of HORIBALFRE algorithm includes the potentials generated from a library of protein structure derived from manually curated CAMPASS database of structure based sequence alignment. We used Fischer's dataset, with 68 templates and 56 target sequences, derived from SCOP database and performed one-against-all sequence alignment using TCoffee. Various potentials were derived using custom scripts and these potentials were incorporated in the HORIBALFRE algorithm. In this manuscript, we report outline of a novel fold recognition algorithm and initial results. Our results show that inclusion of quadruplet class of higher order residue interaction improves fold recognition.

Dynamic modeling and simulation of JNK and P38 kinase cascades with feedbacks and crosstalks.

All cells receive and respond to signals from their environment, whether they live freely or are part of a tissue. Feedback loops are one among the interactions in signal-transduction cascades, in which the information from the downstream components is sent back to the upstream components of the system. Crosstalks between signal-transduction cascades are able to combine the information's received and processed to trigger the appropriate response. To understand how signaling networks make decisions, the dynamic interactions of proteins in the signal-transduction cascades are important rather than just creating static maps of pathways. Based on reaction kinetics, we have developed mathematical models to predict and analyze the impacts of the feedback loops in JNK cascades and the crosstalks between JNK and P38 kinase cascades. Feedback loops in JNK cascades and crosstalks between JNK and P38 kinase cascades plays the complementary roles in making the impacts on the activation of JNK and P38 kinases. JNK and P38 kinase cascades with feedbacks and crosstalks is a robust system.

Analysis of the impact of ERK5, JNK, and P38 kinase cascades on each other: a systems approach.

The classical concept of linear pathways is being increasingly challenged by network representations, which emphasize the importance of interactions between components of a biological system, and motivates for adopting a system-level approach in biology. We have developed a dynamical system that integrates quantitative, dynamic and topological representation of network of ERK5 (Extracellular signal-regulated kinases 5), JNK(c-Jun N-terminal kinases) and P38 kinase cascades. We have observered that, the transient activation of ERK5, JNK1 and P38beta kinase, and the persistent activation of JNK2, JNK3 and P38 delta kinase does not get affected due to the cross-talks between ERK5, JNK and P38 kinase cascades. But it is due to the cross - talks, the transiently activated P38alpha kinase become inactivated, and the transiently activated P38gamma kinase become persistently activated. The impacts of one-way cross-talks between the cascades are insignificant and differ from the impact of two-way cross-talks. We generate a hypothesis that, signaling pathways should be studied as a system by considering the cross-talks between the two adjacent cascades.

Computational prediction and analysis of impact of the cross-talks between JNK and P38 kinase cascades.

Signal transduction is a complex protein signaling process with a rich network of multifunctional interactions that occur in a non-linear fashion. Mitogen-activated protein kinase (MAPK) signal transduction pathways regulate diverse cellular processes ranging from proliferation and differentiation to apoptosis. In mammals, out of five, there are three well characterized subfamilies of MAPKs - ERKs (Extracellular signal-regulated kinases), JNKs (c-Jun N-terminal kinases), and P38 kinases, and their activators, are implicated in human diseases and are targets for drug development. Kinase cascades in MAPK pathways mediate the sensing and processing of stimuli. To understand how cells makes decisions, the dynamic interactions of components of signaling cascades are important rather than just creating static maps. Based on enzyme kinetic reactions, we have developed a mathematical model to analyze the impact of the cross-talks between JNK and P38 kinase cascades. Cross-talks between JNK and P38 kinase cascades influence the activities of P38 kinases. Responses of the signals should be studied for network of kinase cascades by considering cross-talks.