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Protease-associated cellular networks in malaria parasite Plasmodium falciparum

BACKGROUND: Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzym...

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Autores principales: Lilburn, Timothy G, Cai, Hong, Zhou, Zhan, Wang, Yufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287505/
https://www.ncbi.nlm.nih.gov/pubmed/22369208
http://dx.doi.org/10.1186/1471-2164-12-S5-S9
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author Lilburn, Timothy G
Cai, Hong
Zhou, Zhan
Wang, Yufeng
author_facet Lilburn, Timothy G
Cai, Hong
Zhou, Zhan
Wang, Yufeng
author_sort Lilburn, Timothy G
collection PubMed
description BACKGROUND: Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species [1-3], providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. RESULTS: We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database [4], and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system [5], blood stage microarray experiments [6-8], proteomics [9-12], literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks. CONCLUSIONS: Our network analysis of proteases from P. falciparum uses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence.
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spelling pubmed-32875052012-02-28 Protease-associated cellular networks in malaria parasite Plasmodium falciparum Lilburn, Timothy G Cai, Hong Zhou, Zhan Wang, Yufeng BMC Genomics Research Article BACKGROUND: Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species [1-3], providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. RESULTS: We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database [4], and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system [5], blood stage microarray experiments [6-8], proteomics [9-12], literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks. CONCLUSIONS: Our network analysis of proteases from P. falciparum uses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence. BioMed Central 2011-12-23 /pmc/articles/PMC3287505/ /pubmed/22369208 http://dx.doi.org/10.1186/1471-2164-12-S5-S9 Text en Copyright ©2011 Lilburn et al. licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lilburn, Timothy G
Cai, Hong
Zhou, Zhan
Wang, Yufeng
Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title_full Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title_fullStr Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title_full_unstemmed Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title_short Protease-associated cellular networks in malaria parasite Plasmodium falciparum
title_sort protease-associated cellular networks in malaria parasite plasmodium falciparum
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287505/
https://www.ncbi.nlm.nih.gov/pubmed/22369208
http://dx.doi.org/10.1186/1471-2164-12-S5-S9
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