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*  Human Protein Reference Database and Human Proteinpedia as resources for phosphoproteome analysis - Molecular BioSystems (RSC...
Human Protein Reference Database (HPRD) is a rich resource of experimentally proven features of human proteins. Protein information in HPRD includes protein-protein interactions, post-translational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localiz
http://pubs.rsc.org/en/Content/ArticleLanding/2012/MB/C1MB05340J
*  Transient protein-protein interactions | Jan Steyaert Lab at VUB and VIB
Protein-protein interactions (PPIs) are central to most biological processes - from intercellular communication to programmed cell death - and therefore represent a large and important class of targets for human therapeutics. A crucial step towards understanding these biological processes and targeting them for therapy is mapping networks of physical DNA-, RNA- and protein-protein interactions, the "interactome network", of an organism of interest as completely and accurately as possible. Recently a large number of biological pathway and network databases have been developed to capture the expanding knowledge of protein-protein interactions. However, the complete understanding of molecular interactions requires high resolution 3D structures as they provide key atomic details about binding interfaces and information about ...
http://steyaertlab.structuralbiology.be/PPI
*  How many ways protein protein interactions are regulated? - Biochemistry - BioForum
How many ways protein protein interactions are regulated? - posted in Biochemistry: I wonder how many ways protein-protein interactions are regulated. I know a lot of protein protein interactions are modified by phosphorylaton or other modification. Is there other ways that mediate the protein protein interaction? Thanks!
http://www.protocol-online.org/forums/topic/31921-how-many-ways-protein-protein-interactions-are-regulated/
*  Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis
Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring ...
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0088943
*  Trapping Transient Protein-Protein Interactions in Polyketide Biosynthesis
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https://www.infona.pl/resource/bwmeta1.element.acs-doi-10_1021_cb600451d
*  Large‐scale mapping of human protein-protein interactions by mass spectrometry | Molecular Systems Biology
Understanding the roles and consequences of protein-protein interactions is a fundamental goal in cellular biology and a prerequisite for the development of molecular systems biology. The endeavor of cataloging protein interactions is primarily hindered by the throughput and reproducibility of existing technologies. Different techniques for mapping protein interactions are available, such as the two‐hybrid approach (Chien et al, 1991) and the LUMIER approach (Barrios‐Rodiles et al, 2005) and assay whether two proteins interact in a pair‐wise fashion. We have developed a high‐throughput platform combining immunoprecipitation and high‐throughput mass spectrometry (IP‐HTMS) to rapidly identify potentially novel protein interactions for a bait protein of interest. We (Ho et al, 2002) and others (Gavin et al, ...
http://msb.embopress.org/content/3/1/89.print
*  Protein Interaction Analysis Services - Profacgen
Profacgen provides One-Stop-Service on protein-protein interaction analysis, including Yeast two-hybrid, Pull-downs and Surface Plasmon Resonance (SPR) assay etc., to facilitate your scientific research. Our service can be tailored according to your specific requirements.
https://www.profacgen.com/protein-interaction-analysis-services.htm
*  RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks | BMC Bioinformatics | Full Text
In recent years, protein-protein interaction (PPI) datasets have been recognized as important resources to elucidate various biological processes and cellular mechanisms. The prediction of protein complexes from PPIs (see, for example, survey papers [1-3]) is one of the most challenging inference problems from PPIs because protein complexes are essential entities in the cell. Proteins' functions are manifested in the form of a protein complex. Thus, the identification of protein complexes is necessary for the precise description of biological systems.. For protein complex prediction, many computational methods have been proposed, which were directly or indirectly designed based on the observation that densely connected subgraphs, or clusters of proteins, of a whole PPI network often overlap with known complexes. This observation is often ...
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1920-5
*  Protein Interaction Analysis - PDF
Protein Interaction Analysis ProteOn XPR36 Protein Interaction Array System 248 Instrument 248 Software 249 Regulatory Tools 249 Sensor Chips 250 Kits, Reagents, and Consumables 250 Ordering Information
http://docplayer.net/713093-Protein-interaction-analysis.html
*  Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions | Protocol (Translated to Korean)
단백질 상호 작용은 세포의 기능의 핵심이다. 열량 및 분광 기술은 일반적으로 그 특성을하는 데 사용됩니다. 여기에서 우리는 Shwachman - 다이아몬드 증후군 (SBDS)에 돌연변이 단백질과 신장 인자 같은 1는 GTPase (EFL1) ...
https://www.jove.com/video/54640/-?language=Korean
*  A protein interaction map for a better insight in cancer development
Researchers from the Institut Curie and from the Paris-based biotechnology company Hybrigenics announced today that they have built a protein-protein interaction map of the fruit fly, Drosophila melanogaster. This 'simple' model organism allows them to study a 'reference set' of proteins that includes most of those known to be involved in human cancer. Since proteins function in networks, the systematic identification of the physical interactions that occur between proteins will help understanding their biological function, and improve our capacity to intervene and, ultimately, to discover novel, more specific therapeutic targets. Their results are published in the March 1st issue of Genome Research ...
http://www.innovations-report.com/html/reports/life-sciences/report-41033.html
*  Green Connections | Science Signaling
Interactomes can be used to define the interactions between an enormous number of constituent proteins, and thus the interactome of the model plant Arabidopsis should reveal fundamental insight into plant biology (see the Perspective by Landry). The Arabidopsis Interactome Mapping Consortium describes the generation and analysis of a proteome-scale, binary protein-protein interactome map of Arabidopsis. With this resource, Mukhtar et al. investigated hundreds of proteins implicated in immune system function and their interactions with proteins from two evolutionarily disparate pathogens. A "plant-pathogen interaction network" revealed interactions between pathogen effectors and plant proteins and suggests that divergent pathogens attack a highly overlapping set of host proteins that interact with a common ...
http://stke.sciencemag.org/content/4/184/ec216
*  Predicting the Fission Yeast Protein Interaction Network | G3: Genes | Genomes | Genetics
SVM and RF contributed 15 and 10 unique predictions, respectively, that were confirmed experimentally. Thus, the two methods were somewhat complementary and, if used together, may provide better coverage of true predictions. On the other hand, using the overlap of predictions from both SVM and RF provides a more conservative and, hence, more reliable list of protein interactions that could be used as a starting point for further investigations.. The Cbf11 interactors predicted were significantly enriched for the experimentally determined targets, both in the case of SVM (Fisher's exact test, P = 10−14), RF (Fisher's P = 10−28), and in the overlap of the two methods (Fisher's P = 10−28). So far, there are no known genetic interactions for Cbf11 and no functional interactions due to the protein not being conserved in budding yeast. For this reason, our method for predicting its physical association partners can only be ...
http://www.g3journal.org/content/2/4/453
*  Predicting the Fission Yeast Protein Interaction Network | G3: Genes | Genomes | Genetics
SVM and RF contributed 15 and 10 unique predictions, respectively, that were confirmed experimentally. Thus, the two methods were somewhat complementary and, if used together, may provide better coverage of true predictions. On the other hand, using the overlap of predictions from both SVM and RF provides a more conservative and, hence, more reliable list of protein interactions that could be used as a starting point for further investigations.. The Cbf11 interactors predicted were significantly enriched for the experimentally determined targets, both in the case of SVM (Fisher's exact test, P = 10−14), RF (Fisher's P = 10−28), and in the overlap of the two methods (Fisher's P = 10−28). So far, there are no known genetic interactions for Cbf11 and no functional interactions due to the protein not being conserved in budding yeast. For this reason, our method for predicting its physical association partners can only be ...
http://www.g3journal.org/content/2/4/453.long
*  PLOS Computational Biology: Age-Dependent Evolution of the Yeast Protein Interaction Network Suggests a Limited Role of Gene...
Author Summary Proteins function together forming stable protein complexes or transient interactions in various cellular processes, such as gene regulation and signaling. Here, we address the basic question of how these networks of interacting proteins evolve. This is an important problem, as the structures of such networks underlie important features of biological systems, such as functional modularity, error-tolerance, and stability. It is not yet known how these network architectures originate or what driving forces underlie the observed network structure. Several models have been proposed over the past decade-in particular, a
http://journals.plos.org/ploscompbiol/article/metrics?id=10.1371/journal.pcbi.1000232
*  Charting the Landscape of Tandem BRCT Domain-Mediated Protein Interactions | Science Signaling
Eukaryotic cells have evolved an intricate system to resolve DNA damage to prevent its transmission to daughter cells. This system, collectively known as the DNA damage response (DDR) network, includes many proteins that detect DNA damage, promote repair, and coordinate progression through the cell cycle. Because defects in this network can lead to cancer, this network constitutes a barrier against tumorigenesis. The modular BRCA1 carboxyl-terminal (BRCT) domain is frequently present in proteins involved in the DDR, can exist either as an individual domain or as tandem domains (tBRCT), and can bind phosphorylated peptides. We performed a systematic analysis of protein-protein interactions involving tBRCT in the DDR by combining literature curation, yeast two-hybrid screens, and tandem affinity purification coupled to mass spectrometry. We identified 23 proteins containing conserved BRCT domains and generated ...
http://stke.sciencemag.org/content/5/242/rs6
*  Representing molecular interactions data | EMBL-EBI Train online
Some experimental protocols, such as tandem affinity purification (TAP), generate complex data sets, depicting interactions in which more than two proteins are involved at the same time (n-ary interactions).. However, interaction data are often stored in tabular formats that aim to be amenable to quick, comprehensive searches. It may be desirable to convert these complexes into sets of binary interactions to simplify and speed up searches. There are two algorithms that will perform such conversion: the matrix model and the spoke model 2, as depicted in Figure 10. In this hypothetical example, take the bottom right protein complex (marked "reality"). A tandem affinity experiment (far left) might tell you that each of the other five proteins interact with the red bait protein in the middle. In reality, the red protein has only one interactor, which is the ...
https://www.ebi.ac.uk/training/online/course/intact-molecular-interactions-ebi/representing-molecular-interactions-data
*  "DroID: the Drosophila Interactions Database, a comprehensive resource for annotated g . . ." by Jingkai Yu, Svetlana Pacifico...
Abstract Background Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, Drosophila melanogaster. Description DroID, the Drosophila Interactions Database, is a comprehensive interactions database designed ...
https://digitalcommons.wayne.edu/biomedcentral/139/
*  Increasing the precision of orthology-based complex prediction through network alignment [PeerJ]
Macromolecular assemblies play an important role in almost all cellular processes. However, despite several large-scale studies, our current knowledge about protein complexes is still quite limited, thus advocating the use of in silico predictions to gather information on complex composition in model organisms. Since protein-protein interactions present certain constraints on the functional divergence of macromolecular assemblies during evolution, it is possible to predict complexes based on orthology data. Here, we show that incorporating interaction information through network alignment significantly increases the precision of orthology-based complex prediction. Moreover, we performed a large-scale in silico screen for protein complexes in human, yeast and fly, through the alignment of hundreds of known complexes to whole organism interactomes. Systematic comparison of the resulting network alignments to ...
https://peerj.com/articles/413/
*  PLOS ONE: The Type 1 Diabetes - HLA Susceptibility Interactome - Identification of HLA Genotype-Specific Disease Genes for Type...
Background The individual contribution of genes in the HLA region to the risk of developing type 1 diabetes (T1D) is confounded by the high linkage disequilibrium (LD) in this region. Using a novel approach we have combined genetic association data with information on functional protein-protein interactions to elucidate risk independent of LD and to place the genetic association into a functional context. Methodology/Principal Findings Genetic association data from 2300 single nucleotide polymorphisms (SNPs) in the HLA region was analysed in 2200 T1D family trios divided into six risk groups based on HLA-DRB1 genotypes. The best SNP signal in each gene was mapped to proteins in a human protein interaction network and their significance of clustering in functional network modules was evaluated. The significant network modules identified through this approach differed between the six HLA risk groups, which ...
http://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0009576&imageURI=info:doi/10.1371/journal.pone.0009576.g003
*  Protein-protein interaction sites are hot spots for disease-associated nonsynonymous SNPs - Kent Academic Repository
Many nonsynonymous single nucleotide polymorphisms (nsSNPs) are disease causing due to effects at protein-protein interfaces. We have integrated a database of the three-dimensional (3D) structures of human protein/protein complexes and the humsavar database of nsSNPs. We analyzed the location of nsSNPS in terms of their location in the protein core, at protein-protein interfaces, and on the surface when not at an interface. Disease-causing nsSNPs that do not occur in the protein core are preferentially located at protein-protein interfaces rather than surface noninterface regions when compared to random segregation. The disruption of the protein-protein interaction can be explained by a range of structural effects including the loss of an electrostatic salt bridge, the destabilization due to ...
https://kar.kent.ac.uk/31430/
*  Quantitative analysis of protein interaction network dynamics in yeast | Molecular Systems Biology
Here, we described the multiplex in vivo measurement of 1,379 protein-protein interactions in 14 environmental conditions, to our knowledge the most extensive direct study of how protein interaction networks respond dynamically to extrinsic environmental perturbations. The most striking finding was the prevalence of dynamic binary complexes. More than half of the PPIs we considered (757 of 1,379) responded to at least one perturbation. The environmental perturbations that yielded the largest number of changes relative to our reference condition were respiratory growth in ethanol, heat shock, oxidative stress, and DNA damage. That these responses were the most profound might have been expected, as these conditions are likely to have been frequently experienced in the evolutionary history of yeast (Gasch & Werner‐Washburne, 2002; Gasch, 2007), allowing for selection and maintenance of a complex adaptive regulatory strategy. We ...
http://msb.embopress.org/content/13/7/934?ijkey=7ddc8bb4c40e2d4d0e10d5fedf10294b796eb64a&keytype2=tf_ipsecsha
*  visualcomplexity.com | Yeast Protein Interaction Map in 3D
VisualComplexity.com is a unified resource space for anyone interested in the visualization of complex networks. The project's main goal is to leverage a critical understanding of different visualization methods, across a series of disciplines, as diverse as Biology, Social Networks or the World Wide Web.
http://www.visualcomplexity.com/vc/project_details.cfm?id=121&index=121&domain=
*  ARNIE | Construction of a large extracellular protein interaction network and its resolution by spatiotemporal expression...
An online database that integrates the extracellular protein interaction network. ARNIE allows users to browse the network by clicking on individual proteins, or by specifying the spatiotemporal parameters using the drop-down menus. Clicking on connector lines will allow users to compare stage-matched expression patterns for genes encoding interacting proteins. Additionally, users can rapidly search for their genes in the network using the BLAST server provided.
https://omictools.com/avexis-receptor-network-with-integrated-expression-tool