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Background Cardiovascular Disease (CVD) is one of the most common causes of mortality in humans. Presently, the role of pathogens in the initiation and progression of the CVDs is not clearly understood. Hence, it is essential to understand the molecular-level interactions between the human proteins and the microbial proteins to deduce their functional roles in the CVDs. Method The host-pathogen interactions (HPI) related to CVDs in the case of E. coli str. O157:H7 colonization were curated, and also the protein-protein interactions (PPI) between humans and E. coli were collected. Gene interaction network (GIN) and functional enrichment analyses (FEA) were utilized for this. Results The GIN revealed dense interactions between the functional partners. The FEA indicated that the essential pathways played a significant role in humans as well as in E. coli. The primary responses against most of the bacterial pathogens in humans are different from that of E. coli; Terpenoid biosynthesis and production of secondary metabolite pathways aid the survival of the E. coli inside the host. Interestingly, network analysis divulged that the E. coli genes ksgA, rpsT, ispE, rpsI, ispH, and the human genes TP53, CASP3, CYCS, EP300, RHOA communicated by significant numbers in direct interactions. Conclusions The results obtained from the present study will help researchers understand the molecular-level interactions in the CVDs between the human and the E. coli genes. The important genes with vital interactions can be considered as hub molecules and can be exploited for new drug discovery.

Multi Drug Resistance (MDR) in Acinetobacter baumannii is one of the major threats for emerging nosocomial infections in hospital environment. Multidrug-resistance in A. baumannii may be due to the implementation of multi-combination resistance mechanisms such as β-lactamase synthesis, Penicillin-Binding Proteins (PBPs) changes, alteration in porin proteins and in efflux pumps against various existing classes of antibiotics. Multiple antibiotic resistance genes are involved in MDR. These resistance genes are transferred through plasmids, which are responsible for the dissemination of antibiotic resistance among Acinetobacter spp. In addition, these resistance genes may also have a tendency to interact with each other or with their gene products. Therefore, it becomes necessary to understand the impact of these interactions in antibiotic resistance mechanism. Hence, our study focuses on protein and gene network analysis on various resistance genes, to elucidate the role of the interacting proteins and to study their functional contribution towards antibiotic resistance. From the search tool for the retrieval of interacting gene/protein (STRING), a total of 168 functional partners for 15 resistance genes were extracted based on the confidence scoring system. The network study was then followed up with functional clustering of associated partners using molecular complex detection (MCODE). Later, we selected eight efficient clusters based on score. Interestingly, the associated protein we identified from the network possessed greater functional similarity with known resistance genes. This network-based approach on resistance genes of A. baumannii could help in identifying new genes/proteins and provide clues on their association in antibiotic resistance.

Penicillin binding proteins are recognized as important antibacterial targets because of their crucial role in the cell wall synthesis of bacteria. Alteration in the binding site of penicillin binding proteins is one of the major problems for beta lactam antibiotics to exert its effect. In the present study the influence of CH?O interactions in the conformational stability of penicillin binding proteins were analyzed in both Gram positive and Gram negative bacteria. CH?O interactions constitute about 20 to 25% of total hydrogen bonds and act as an important driving force in ligand selectivity. From our analysis we observed a total of 13,398 CH?O interactions in Gram positive bacteria and 10,855 CH?O interactions in Gram negative bacteria. It was interesting to observe that CH?O interactions were higher in Gram positive bacteria than in Gram negative bacteria, which augurs well for the discrepancy in cell wall of the bacteria. CH?O interactions are classified into four types depending on the interaction of acceptor residues with the back bone or side chain of CH groups. From our results we observed that major contribution to penicillin binding proteins was observed from side chain atoms of donor residues and back bone atoms of acceptor residues SM CH?O in both Gram positive and Gram negative bacteria. Conformational preference of Gram positive bacteria indicated that amino acids lacking side chain and the cyclized amino acids preferred to be in turn regions, whereas aromatic amino acids dominated in Gram negative bacteria. Our analysis gives detailed information about the principles involved in the conformational stability of penicillin binding proteins and the results will be useful for researchers exploring penicillin binding proteins. Importance of CH?O bonds in the structural stability of PBPs are analyzed.Significant number of interacting residues shows higher conservation score.Interestingly residues with higher conservation score have more stabilizing regions.Our study provides detailed structural information about PBPs.Results obtained from this study will be useful in designing effective antibiotics.

BackgroundHaemophilus influenzae (H. Influenzae) is the causative agent of pneumonia, bacteraemia and meningitis. The organism is responsible for large number of deaths in both developed and developing countries. Even-though the first bacterial genome to be sequenced was that of H. Influenzae, there is no exclusive database dedicated for H. Influenzae. This prompted us to develop the Haemophilus influenzae Genome Database (HIGDB). MethodsAll data of HIGDB are stored and managed in MySQL database. The HIGDB is hosted on Solaris server and developed using PERL modules. Ajax and JavaScript are used for the interface development. ResultsThe HIGDB contains detailed information on 42,741 proteins, 18,077 genes including 10 whole genome sequences and also 284 three dimensional structures of proteins of H. influenzae. In addition, the database provides "Motif search" and "GBrowse". The HIGDB is freely accessible through the URL: http://bioserver1.physics.iisc.ernet.in/HIGDB/. DiscussionThe HIGDB will be a single point access for bacteriological, clinical, genomic and proteomic information of H. influenzae. The database can also be used to identify DNA motifs within H. influenzae genomes and to compare gene or protein sequences of a particular strain with other strains of H. influenzae. The HIGDB act as a single access point source for Haemophilus influenzae genomes.It provides a dynamic interface to execute varied searches for genes and proteins.The database facilitates the comparative study of H. influenzae genomes.It allows dynamic viewing of the genomic content of H. influenzae strains.It aids in the identification of DNA motifs within H. influenzae genomes.

Studies on intra-protein interactions provide valuable information on protein conformation. The aim of our study is to explore the functional importance of residues participating in N-H...@p hydrogen bonds in maintaining the conformational stability of @b-lactamases. Our results show that most of the residues participating in N-H...@p hydrogen bond formation are functionally important and play a significant role in stabilizing the structure with more than one stabilizing region. Our findings reveal the importance of N-H...@p hydrogen bonds in the stability of @b-lactamases. These findings may be helpful for medicinal and computational protein chemists working in the area of enzyme mediated antibiotic resistance.