Research paperIdentifying a potential receptor for the antibacterial peptide of sponge Axinella donnani endosymbiont
Introduction
Natural products have been used as foods, fragrances, insecticides etc., and are real sources of most of the active ingredients of medicines. It has been reported that more than 80% of available drugs are from natural products and more than 12,000 antimicrobial compounds have been identified from marine organisms (Jacob and Ravikumar, 2012, Senthilkumar and Kim, 2013). Among the isolated potential metabolites, sponges were the predominant contributors. The identified bioactive substances from sponge associated microorganisms showed therapeutic importance such as anticancer, antibacterial, antifungal, antiviral, antiprotozoal, anthelmintic, anti-inflammatory, immunosuppressive and antifouling activities (Santos-Gandelman et al., 2014). Over the last decade a diverse group of sponge associated microbial metabolite structures were identified and tested for biological activity (Da Silva et al., 2014). The peptide based structural studies form a vital platform eventually leads to target identification and further drug designing. These studies mainly focused on the structure elucidation and function characterization of the steroids, terpenoids and related compounds and the proteomic analysis is not yet well documented. Hence, it is necessary to identify the structure–function relationship of antibacterial peptides. In our previous study, a novel antibacterial peptide from the endosymbiotic bacteria of the sponge Axinella donnani was identified and the antibacterial activity of the endosymbiont was experimentally determined against the human and shrimp pathogenic bacteria (Vimala et al., 2012). Based on these facts, in this work, we have carried out a systematic analysis for identifying the receptor protein using comparative genomics approach. We obtained a set of 60 proteins, which are common among all the eight pathogens and omp85 has been selected as a potential receptor using substrate and docking analysis. The structure of the antibacterial peptide was modeled using de novo modeling and subjected for protein–peptide docking with the BamA. Molecular Dynamics (MD) simulations were performed to assess the conformational stability of the peptide and its complex form with BamA. Our study agrees well with the experimental report (Albrecht et al., 2014) that the antibacterial peptide interacts with BamA at the conserved regions having functional importance.
Section snippets
Antibacterial peptide
We have used the antibacterial peptide, MSASTCLRREYFHCFRVLLIASVLDQPFVRETDQKTETI isolated from the endosymbiotic bacteria of the sponge A. donnani to identify the potential receptor and to study its mode of inhibitory activity.
Receptor identification
We have used the bacterial pathogens of human (Vibrio alginolyticus, Pseudomonas aerogenosa, Areomonas hydrophila and Vibrio harvae) and shrimp (Vibrio fischeri, Escherichia coli, Morgenella morgenii and Bacillus cereus) in the present study (Table 1). The genome sequences
Comparative genomics
The comparative genome analysis revealed the presence of 60 common coding sequences as shown in Fig. 1. We have identified the substrate of the resultant proteins using Interpro database and the information available in the literature. All common coding sequences of eight pathogenic organisms and their binding substrates are shown in Table 2. We found that only three proteins such as omp85 family outer membrane protein, protein-export membrane protein SecF and protein-export membrane protein
Conclusion
The systematic comparative genomics study predicted that BamA, one of the omp85 outer membrane family proteins can serve as a receptor for the broad spectrum of antibacterial peptide. The evolutionarily conserved motifs RGF and YGDG were functionally important in BamA and they were interacting with the peptide inhibitor. The Asp639, Gly640 and Leu641 were located in the L6 loop of extra-cytosolic region of the receptor showed the stable interactions with the peptide. The results found from this
Acknowledgment
We thank Protein Bioinformatics Laboratory, Department of Biotechnology, Bioinformatics Infrastructure Facility and Indian Institute of Technology Madras for computational facilities. A Vimala is a recipient of Women Post-Doctoral Fellowship from the Indian Institute of Technology Madras. We would like to thank the anonymous reviewers for their constructive comments.
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