Abstract

BackgroundPlasmodium falciparum causes the most severe form of malaria and affects 3.2 million people annually. Due to the increasing incidence of resistance to existing drugs, there is a growing need to discover new and more effective drugs against malaria. Despite the global importance of P. falciparum, vast majority of its proteins are uncharacterized experimentally. Application of newer approaches using several “omics” data has become successful for exploring the biological interactions underlying cellular processes. Till date not many system level study has been published using P. falciparum protein protein interaction. Hence, the purpose of this study is to develop a standardized pipeline for structural, functional, and topographical analysis of large scale protein protein interaction network (PPIN) in order to identify proteins important for network topology and integrity. Here, P. falciparum PPIN has been utilized as a model for better understanding of the molecular mechanisms of survival and pathogenesis of malaria parasite.MethodsVarious graph theoretical approaches were implemented to identify highly interacting hub and central proteins that are crucial for network integrity. Further, potential network perturbing proteins via an in-silico knock-out (KO) analysis to isolate important interacting proteins (IIPs), which in principle, can elicit significant impact on the global and local environments of the P. falciparum interaction network.Results177 hubs and 132 central proteins were identified from the malarial (proteins: 1607; interactions: 4750) PPI networks. Using the in-silico knock-out exercise 131 and 99 global and local network perturbing proteins were also identified. Finally, 271 proteins from P. falciparum were shortlisted as important interacting proteins (IIPs), which not only play crucial role in intra-pathogen network integrity, stage specificity but also interact with various human proteins involved in multiple metabolic pathways within the host cell. These IIPs could be used as potential drug targets in malarial research.ConclusionGraph theoretical analysis of PPIN can be a very useful approach to identify proteins that are important for regulation of the interactions required for an organism’s survival. Important interacting proteins (IIPs) identified using P. falciparum PPIN provides a useful dataset containing probable candidates for future drug target analysis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0562-1) contains supplementary material, which is available to authorized users.

Highlights

  • Plasmodium falciparum causes the most severe form of malaria and affects 3.2 million people annually

  • Graph theoretical analysis of protein protein interaction network (PPIN) can be a very useful approach to identify proteins that are important for regulation of the interactions required for an organism’s survival

  • Construction of Malaria network (MN) and E. coli Network (EN) was validated by comparing them with the random networks generated by Barabasi-Albert (BA) preferential attachment algorithm [42,43]

Read more

Summary

Introduction

Plasmodium falciparum causes the most severe form of malaria and affects 3.2 million people annually. Application of newer approaches using several “omics” data has become successful for exploring the biological interactions underlying cellular processes. P. falciparum PPIN has been utilized as a model for better understanding of the molecular mechanisms of survival and pathogenesis of malaria parasite. Though the intricate details of the pathogenesis are not yet clear, effective drugs against P. falciparum were in use since 1920. Exploring the protein-protein interactome of the parasite at the system level could be a useful strategy in unravelling its critical biological processes. New approaches like this will enhance the knowledge base about the underlying mechanism of parasite’s survival, and will help us to identify proteins crucial for pathogenesis

Objectives
Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.