ArticleMalaria journal2015
Identification of important interacting proteins (IIPs) in Plasmodium falciparum using large-scale interaction network analysis and in-silico knock-out studies.
Article in Malaria journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed.
- Heterologous protection against malaria by a simple chemoattenuated PfSPZ vaccine regimen in a randomized trial.Nature communications · 2021Trial
- Evaluating network-based algorithms for protein function prediction using plant protein-protein interaction networks.BMC plant biology · 2026Article
- In silico Methods for Identification of Potential Therapeutic Targets.Interdisciplinary sciences, computational life sciences · 2022Review
- RegEnrich gene regulator enrichment analysis reveals a key role of the ETS transcription factor family in interferon signaling.Communications biology · 2022Article
- Identification of Cross-Pathway Connections via Protein-Protein Interactions Linked to Altered States of Metabolic Enzymes in Cervical Cancer.Frontiers in medicine · 2021Article
- Heat Shock Proteins as Targets for Novel Antimalarial Drug Discovery.Advances in experimental medicine and biology · 2021Article
- Structural and Drug Screening Analysis of the Non-structural Proteins of Severe Acute Respiratory Syndrome Coronavirus 2 Virus Extracted From Indian Coronavirus Disease 2019 Patients.Frontiers in genetics · 2021Article
- Analysis of Pan-omics Data in Human Interactome Network (APODHIN).Frontiers in genetics · 2020Article
- Membrane Interactome of a Recombinant Fragment of Human Surfactant Protein D Reveals GRP78 as a Novel Binding Partner in PC3, a Metastatic Prostate Cancer Cell Line.Frontiers in immunology · 2020Article
- Identification of Important Effector Proteins in the FOXJ1 Transcriptional Network Associated With Ciliogenesis and Ciliary Function.Frontiers in genetics · 2019Article
- Identification of drug target candidates of the swine pathogen Actinobacillus pleuropneumoniae by construction of protein-protein interaction network.Genes & genomics · 2018Article
- Prediction ofGalen medical journal · 2018Article
- Computational analysis of protein interaction networks for infectious diseases.Briefings in bioinformatics · 2016Review
- Plasmodium falciparum Secretome in Erythrocyte and Beyond.Frontiers in microbiology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.