scholarly journals A reliable and unbiased human protein network with the disparity filter

2017 ◽  
Author(s):  
Gregorio Alanis-Lobato ◽  
Miguel A. Andrade-Navarro
Keyword(s):  
Experimental Evidence ◽  
Protein Interactions ◽  
Living Cell ◽  
Human Proteome ◽  
Human Protein ◽  
Protein Network ◽  
Small Scale ◽  
Cellular Functions ◽  
Wiring Diagram ◽  
Human Interactome

AbstractThe living cell operates thanks to an intricate network of protein interactions. Proteins activate, transport, degrade, stabilise and participate in the production of other proteins. As a result, a reliable and systematically generated protein wiring diagram is crucial for a deeper understanding of cellular functions. Unfortunately, current human protein networks are noisy and incomplete. Also, they suffer from both study and technical biases: heavily studied proteins (e.g. those of pharmaceutical interest) are known to be involved in more interactions than proteins described in only a few publications. Here, we use the experimental evidence supporting the interaction between proteins, in conjunction with the so-called disparity filter, to construct a reliable and unbiased proteome-scale human interactome. The application of a global filter, i.e. only considering interactions with multiple pieces of evidence, would result in an excessively pruned network. In contrast, the disparity filter preserves interactions supported by a statistically significant number of studies and does not overlook small-scale protein associations. The resulting disparity-filtered protein network covers 67% of the human proteome and retains most of the network’s weight and connectivity properties.

scholarly journals A synthesis of over 9,000 mass spectrometry experiments reveals the core set of human protein complexes

2016 ◽  
Author(s):  
Kevin Drew ◽  
Chanjae Lee ◽  
Ryan L. Huizar ◽  
Fan Tu ◽  
Blake Borgeson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Genetic Diseases ◽  
Intraflagellar Transport ◽  
Human Protein ◽  
Disease Genes ◽  
Cellular Functions ◽  
The Core

AbstractMacromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing >4,600 total complexes, >7,700 proteins and >56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k-cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations and the map overall shows improved coverage of many disease-associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

scholarly journals A reference map of the human protein interactome

2019 ◽  
Author(s):  
Katja Luck ◽  
Dae-Kyum Kim ◽  
Luke Lambourne ◽  
Kerstin Spirohn ◽  
Bridget E. Begg ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Function ◽  
Molecular Mechanisms ◽  
Human Genetics ◽  
Genomic Variation ◽  
Small Scale ◽  
Human Interactome ◽  
Tissue Specific ◽  
Cellular Context ◽  
Reference Map

AbstractGlobal insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human “all-by-all” binary reference interactome map, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

scholarly journals Flexible web-based integration of distributed large-scale human protein interaction maps

2007 ◽  
Vol 4 (1) ◽  
pp. 40-50 ◽  
Author(s):  
Gautam Chaurasia ◽  
Yasir Iqbal ◽  
Christian Hänig ◽  
Hanspeter Herzel ◽  
Erich E. Wanker ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Large Scale ◽  
Human Interaction ◽  
Human Protein ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Protein Protein Interactions ◽  
Human Interactome ◽  
Protein Protein Interaction

Summary Protein-protein interactions constitute the backbone of many molecular processes. This has motivated the recent construction of several large-scale human protein-protein interaction maps [1-10]. Although these maps clearly offer a wealth of information, their use is challenging: complexity, rapid growth, and fragmentation of interaction data hamper their usability. To overcome these hurdles, we have developed a publicly accessible database termed UniHI (Unified Human Interactome) for integration of human protein-protein interaction data. This database is designed to provide biomedical researchers a common platform for exploring previously disconnected human interaction maps. UniHI offers researchers flexible integrated tools for accessing comprehensive information about the human interactome. Several features included in the UniHI allow users to perform various types of network-oriented and functional analysis. At present, UniHI contains over 160,000 distinct interactions between 17,000 unique proteins from ten major interaction maps derived by both computational and experimental approaches [1-10]. Here we describe the details of the implementation and maintenance of UniHI and discuss the challenges that have to be addressed for a successful integration of interaction data.

Current trends in mathematical modeling of tumor–microenvironment interactions: a survey of tools and applications

2010 ◽  
Vol 235 (4) ◽  
pp. 411-423 ◽  
Author(s):  
Katarzyna A Rejniak ◽  
Lisa J McCawley
Keyword(s):  
Mathematical Modeling ◽  
Protein Interactions ◽  
Computational Models ◽  
Chemical Species ◽  
Tumor Stroma ◽  
Cellular Functions ◽  
Complex Interactions ◽  
Expanding Population

In its simplest description, a tumor is comprised of an expanding population of transformed cells supported by a surrounding microenvironment termed the tumor stroma. The tumor microcroenvironment has a very complex composition, including multiple types of stromal cells, a dense network of various extracellular matrix (ECM) fibers interpenetrated by the interstitial fluid and gradients of several chemical species that either are dissolved in the fluid or are bound to the ECM structure. In order to study experimentally such complex interactions between multiple players, cancer is dissected and considered at different scales of complexity, such as protein interactions, biochemical pathways, cellular functions or whole organism studies. However, the integration of information acquired from these studies into a common description is as difficult as the disease itself. Computational models of cancer can provide cancer researchers with invaluable tools that are capable of integrating the complexity into organizing principles as well as suggesting testable hypotheses. We will focus in this Minireview on mathematical models in which the whole cell is a main modeling unit. We will present a current stage of such cell-focused mathematical modeling incorporating different stromal components and their interactions with growing tumors, and discuss what modeling approaches can be undertaken to complement the in vivo and in vitro experimentation.

scholarly journals Antibodies for profiling the human proteome-The Human Protein Atlas as a resource for cancer research

PROTEOMICS ◽  
2012 ◽  
Vol 12 (13) ◽  
pp. 2067-2077 ◽  
Author(s):  
Anna Asplund ◽  
Per-Henrik D. Edqvist ◽  
Jochen M. Schwenk ◽  
Fredrik Pontén
Keyword(s):  
Cancer Research ◽  
Human Proteome ◽  
Human Protein ◽  
Human Protein Atlas

scholarly journals PF16 encodes a protein with armadillo repeats and localizes to a single microtubule of the central apparatus in Chlamydomonas flagella.

1996 ◽  
Vol 132 (3) ◽  
pp. 359-370 ◽  
Author(s):  
E F Smith ◽  
P A Lefebvre
Keyword(s):  
Protein Interactions ◽  
Insertional Mutagenesis ◽  
Flagellar Motility ◽  
Wild Type ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Central Pair ◽  
Central Apparatus ◽  
Immunofluorescence Labeling ◽  
Armadillo Repeats

Several studies have indicated that the central pair of microtubules and their associated structures play a significant role in regulating flagellar motility. To begin a molecular analysis of these components we have generated central apparatus-defective mutants in Chlamydomonas reinhardtii using insertional mutagenesis. One paralyzed mutant recovered in our screen, D2, is an allele of a previously identified mutant, pf16. Mutant cells have paralyzed flagella, and the C1 microtubule of the central apparatus is missing in isolated axonemes. We have cloned the wild-type PF16 gene and confirmed its identity by rescuing pf16 mutants upon transformation. The rescued pf16 cells were wild-type in motility and in axonemal ultrastructure. A full-length cDNA clone for PF16 was obtained and sequenced. Database searches using the predicted 566 amino acid sequence of PF16 indicate that the protein contains eight contiguous armadillo repeats. A number of proteins with diverse cellular functions also contain armadillo repeats including pendulin, Rch1, importin, SRP-1, and armadillo. An antibody was raised against a fusion protein expressed from the cloned cDNA. Immunofluorescence labeling of wild-type flagella indicates that the PF16 protein is localized along the length of the flagella while immunogold labeling further localizes the PF16 protein to a single microtubule of the central pair. Based on the localization results and the presence of the armadillo repeats in this protein, we suggest that the PF16 gene product is involved in protein-protein interactions important for C1 central microtubule stability and flagellar motility.

scholarly journals A computational interactome and functional annotation for the human proteome

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
José Ignacio Garzón ◽  
Lei Deng ◽  
Diana Murray ◽  
Sagi Shapira ◽  
Donald Petrey ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Enrichment Analysis ◽  
Human Proteome ◽  
Gene Set Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Functional Relationships ◽  
Structural Relationships ◽  
Human Proteins ◽  
Validation Tests

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function.

scholarly journals Network Protein Interaction in the Link between Stroke and Periodontitis Interplay: A Pilot Bioinformatic Analysis

2021 ◽  
Author(s):  
Yago Leira ◽  
Paulo Mascarenhas ◽  
Juan Blanco ◽  
Tomás Sobrino ◽  
José João Mendes ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Exploratory Study ◽  
Plaque Rupture ◽  
Bioinformatic Analysis ◽  
Protein Network ◽  
Biological Mechanism ◽  
Ppi Networks ◽  
Network Interaction ◽  
Atheroma Plaque ◽  
New Protein

The clinical interaction between stroke and periodontitis has been consistently studied and confirmed. Hence, forecasting potentially new protein interactions in this association using bioinformatic strategies presents potential interest. In this exploratory study, we conducted a protein-protein network interaction (PPI) search with documented encoded proteins for both stroke and periodontitis. Genes of interest were collected via GWAS database. The STRING database was used to predict the PPI networks, first in a sensitivity purpose (confidence cut-off of 0.7), and then with a highest confidence cut-off (0.9). Genes over-representation was inspected in the final network. As a result, we foresee a prospective protein network of interaction between stroke and periodontitis. Inflammation, pro-coagulant/pro-thrombotic state and ultimately atheroma plaque rupture is the main biological mechanism derived from the network. These pilot results may pave the way to future molecular and therapeutic studies to further comprehend the mechanisms between these two conditions.

scholarly journals Developing drugs for the ‘undruggable’

BioTechniques ◽  
2020 ◽  
Vol 69 (4) ◽  
pp. 239-241
Author(s):  
Abigail Sawyer
Keyword(s):  
Protein Interactions ◽  
Therapeutic Targets ◽  
Protein Protein Interactions ◽  
Human Interactome ◽  
Novel Therapeutic

There are up to 650,000 ‘undruggable’ protein-protein interactions (PPIs) in the human interactome that can be potentially considered as novel therapeutic targets. How does the ‘undruggable’ become ‘druggable’?

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