Evidence map›Paper›PMID 22369208›Full record

ArticleBMC genomics2011

Protease-associated cellular networks in malaria parasite Plasmodium falciparum.

Timothy G Lilburn, Hong Cai, Zhan Zhou, Yufeng Wang

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. In Silico Survey and Characterization ofPathogens (Basel, Switzerland) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 2 countries.

Timothy G LilburnDepartment of Biology, University of Texas at San Antonio, San Antonio, TX 78249, USA.
Hong Cai
Zhan Zhou
Yufeng Wang
The University of Texas at San Antonio · US

Funding

STRUCTURAL VISUALIZATION IN BIOINFORMATICSG12RR013646 · NCRR · UNIVERSITY OF TEXAS SAN ANTONIO · PI WENK, CAROLA · 1998 to 2011
$19.6M
Systems Biology of Plasmodium falciparum: Building and Exploring Network ModelsSC1GM100806 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI WANG, YUFENG · 2012 to 2015
$1.5M
Systems Biology of Plasmodium falciparum: Building and Exploring Network ModelsSC1AI080579 · NIAID · UNIVERSITY OF TEXAS SAN ANTONIO · PI WANG, YUFENG · 2008 to 2011
$962k
Systems Biology of Plasmodium falciparum: Building and Exploring Network ModelsSC1GM081068 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI WANG, YUFENG · 2007 to 2007
$248k
NCRR NIH HHS RR013646NIAID NIH HHS AI080579NIAID NIH HHS SC1 AI080579NIGMS NIH HHS GM081068NIGMS NIH HHS SC1 GM081068NIGMS NIH HHS SC1 GM100806
6 · The paper itself

Abstract

backgroundMalaria 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 123, 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.

resultsWe 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 678, proteomics 9101112, 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.

conclusionsOur 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.

Indexed as

AnimalsDatabases, ProteinData MiningErythrocytesPeptide HydrolasesPlasmodium falciparumProtein Array AnalysisProtein Interaction MappingProteomicsProtozoan ProteinsSequence HomologyTwo-Hybrid System TechniquesUbiquitinsPeptide HydrolasesProtozoan ProteinsUbiquitins

Identifiers

PMID22369208
PMCPMC3287505
OpenAlexW2117200623

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.