AlignHUSH: alignment of HMMs using structure and hydrophobicity information.

Background: Sensitive remote homology detection and accurate alignments especially in the midnight zone of sequence similarity are needed for better function annotation and structural modeling of proteins. An algorithm, AlignHUSH for HMM-HMM alignment has been developed which is capable of recognizing distantly related domain families The method uses structural information, in the form of predicted secondary structure probabilities, and hydrophobicity of amino acids to align HMMs of two sets of aligned sequences. The effect of using adjoining column(s) information has also been investigated and is found to increase the sensitivity of HMM-HMM alignments and remote homology detection.

Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria.

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms.

Prediction of protein-protein interactions between Helicobacter pylori and a human host.

A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro.

Evolutionary divergence of Plasmodium falciparum: sequences, protein-protein interactions, pathways and processes.

In this article we review the organism-wide biological data available for Plasmodium falciparum (P. falciparum), a malarial parasite, in relation to the data available for other organisms. We provide comparisons at different levels such as amino acid sequences of proteins encoded in the genomes, protein-protein interaction features, metabolic and signaling pathways and processes.

A data integration approach to predict host-pathogen protein-protein interactions: application to recognize protein interactions between human and a malarial parasite.

Lack of large-scale efforts aimed at recognizing interactions between host and pathogens limits our understanding of many diseases. We present a simple and generally applicable bioinformatics approach for the analysis of possible interactions between the proteins of a parasite, Plasmodium falciparum, and human host. In the first step, the physically compatible interactions between the parasite and human proteins are recognized using homology detection.