Protein-protein Interaction Networks: from Interactions to Networks

Cho, Sayeon; Park, Sung Goo; Lee, Do Hee; Park, Byoung Chul

doi:10.5483/bmbrep.2004.37.1.045

Cited by 50 publications

(31 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is underscored by the discovery of cytoskeletal and scaffold molecules, such as clathrin and tubulin, and a dearth in the identification of signaling molecules such as kinases among the list of NIPs. Our findings are consistent with those of others on protein interactions for receptor and channel molecules and highlight a limitation of the current high-throughput proteomic approach (33).…”

Section: Discussionsupporting

confidence: 81%

“…The isolation of protein complexes from native tissue provides a significant advantage over traditional protein interaction screens, such as the yeast two-hybrid, because it allows for the analysis of interactions within the normal cellular milieu (33). We conclude that the ␤2 subunit associates with well Ͼ20 cellular proteins termed NIPs.…”

Section: Discussionmentioning

confidence: 99%

“…Because the results of the pulldown study are based on interactions of the M3-M4 loop fusion protein with proteins expressed in brain, we propose that the NIPs identified by the pulldown strategy (such as synaptotagmin 1 and NSF) associate with the ␤2 subunit by coupling to the intracellular region of the receptor either directly or indirectly (as by an intermediate protein). Moreover, because interactions between proteins depend on conditions defined by the experimental paradigm, such as those imposing constraints on the stability of protein bonds as well as the proximity of interaction motifs (36), it is expected that NIPs identified by pulldown will differ from NIPs identified by immunoprecipitation (33,37). Clearly, the combined use of multiple techniques provides the best strategy for identifying the full spectrum of interactions for any given protein (38).…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Intracellular complexes of the β2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics

Kabbani

Woll

Levenson

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Nicotine acetylcholine receptors (nAChRs) comprise a family of ligand-gated channels widely expressed in the mammalian brain. The ␤2 subunit is an abundant protein subunit critically involved in the cognitive and behavioral properties of nicotine as well as in the mechanisms of nicotine addiction. In this work, we used matrixassisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF-TOF MS/MS) to uncover protein interactions of the intracellular loop of the ␤2 subunit and components of immunoprecipitated ␤2-nAChR complexes from mouse brain. Using the ␤2-knockout mouse to exclude nonspecific binding to the ␤2 antibody, we identify 21 nAChR-interacting proteins (NIPs) expressed in brain. Western blot analysis confirmed the association between the ␤2 subunit and candidate NIPs. Based on their functional profiles, the hypothesis is suggested that the identified NIPs can regulate the trafficking and signaling of the ␤2-nAChR. Interactions of the ␤2 subunit with NIPs such as G protein ␣, G protein-regulated inducer of neurite outgrowth 1, and G proteinactivated K ؉ channel 1 suggest a link between nAChRs and cellular G protein pathways. These findings reveal intracellular interactions of the ␤2 subunit and may contribute to the understanding of the mechanisms of nAChR signaling and trafficking in neurons.mass spectrometry ͉ receptor complex N icotine is a common drug of addiction and a leading cause of preventable deaths in developed countries (1, 2). The target of nicotine is a class of nicotinic acetylcholine receptors (nAChRs) existing as pentameric channels made up of various receptor subunits and distributed throughout the brain (3). To date, 11 neuronal subunits have been identified: ␣2-␣9 and ␤2-␤4. The specific combination of these subunits confers the pharmacological and physiological properties of the nAChR (4). Studies show that Ϸ90% of the high-affinity nicotine receptor sites within the brain consist of the ␣4␤2-nAChR (5, 6). Topological analysis of nAChR subunits indicates the presence of a large, highly divergent intracellular loop (M3-M4 loop) that is implicated in trafficking and targeting properties of nAChRs (7,8). Recent analysis of a prokaryotic homolog of the nAChR family reveals that the M3-M4 loop is unique to the evolution of the nAChR in eukaryotes (9).The generation of subunit-specific knockout (KO) mice has proven valuable in defining the role of individual nAChR subunits in brain physiology and animal behavior (10). Experiments in mice lacking the ␤2 subunit (␤2 Ϫ/Ϫ ) demonstrate an important role for this receptor subunit in neuronal development and plasticity (10), protection from excitotoxicity (11), and the mechanisms underlying cognitive and social behaviors (12). ␤2 Ϫ/Ϫ mice also exhibit a loss of nicotine self-administration and nicotine-elicited firing and dopamine release from dopaminergic neurons of the ventral tegmental area (13,14). Because reexpression of the ␤2 subunit in ␤2 Ϫ/Ϫ mice was found sufficient to restore the electrophysiological and beh...

show abstract

Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Intracellular complexes of the β2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics

Kabbani

Woll

Levenson

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…Protein phosphorylation has been known to play a significant role in the regulation of numerous aspects of cellular function such as growth, metabolism, motility, survival, and apoptosis. Moreover, numerous protein-protein interactions have been shown to be regulated by phosphorylation (Cho et al, 2004). Since HRPAP20 appears to complex with CaM and contains three consensus motifs for PKC catalyzed phosphorylation, it was hypothesized that HRPAP20 function may be regulated by CaM-binding and phosphorylation.…”

Section: Discussionmentioning

confidence: 99%

EGF Regulation of HRPAP20: A Role for Calmodulin and Protein Kinase C in Breast Cancer Cells

Shukla¹,

Buckley²,

Buckley³

2011

Breast Cancer - Carcinogenesis, Cell Growth and Signalling Pathways

View full text Add to dashboard Cite

“…To quantify a network [1][2][3] it is important to standardize various measures that capture the internal structure of the system. In this section, we discuss some of the important measures that can be used to analyze complex systems.…”

Section: Centrality Measuresmentioning

confidence: 99%

Community Detection in Biological Networks

Thakur

2011

Applied Statistics for Network Biology

View full text Add to dashboard Cite

Networks are everywhere and evolving in various forms, following certain characteristic patterns like small-world and scale-free characteristics. The basis of these forms is not the random addition of nodes and vertices to the system under study, but a systematic process of mutual evolution. This makes many aspects of such systems worth studying. Researchers have invested many years interpreting such systems, for instance how biological networks evolve and why humans form societies to name a few. Thus, seminal to the behavior to these systems are the way internal components are connected to each other. These connections breed structures that exemplify the nature and the behavior of the overall system. Advances in genomics have generated enormous amounts of data, currently gathered by biologists and now available to the scientific community at large. The categorization of this data naturally falls into various classes, ranging from protein sequences to complex molecules. Thus, challenges lie in understanding the properties and dynamics of such complex systems rather than gaining insight into the individual components. Fortunately, promises shown in statistical physics and network theory that offer a host of methods and tools to analyze large data can invariably be used in biology. Modeling interactions between proteins, cells, and other genomic data as network graphs and applying statistical techniques on them can greatly benefit us in scrutinizing the intricacies that exist in these datasets. These methods not only simplify the representations, but also aid in searching for general principles of organization and evolution of biological structures. For example, smallworld analysis is used to explain protein-protein interaction networks and scale-free invariance properties exist for in silico evolution of metabolic networks, which encode an increasing amount of information about their environment. The questions often arises as to which properties of such systems are worth studying and how are the emergent behaviors actually affecting the overall functionality of such systems. Visualization is a potential tool that was used as a first step to display the connectivity patterns between various components and describe the structure as a whole. Another

show abstract

Protein-protein Interaction Networks: from Interactions to Networks

Cited by 50 publications

References 43 publications

Intracellular complexes of the β2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics

Intracellular complexes of the β2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics

EGF Regulation of HRPAP20: A Role for Calmodulin and Protein Kinase C in Breast Cancer Cells

Community Detection in Biological Networks

Contact Info

Product

Resources

About