The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.

2013-07-12

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about experimentally and computationally detected human PPIs as well as their corresponding annotation data. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://biotools.ceid.upatras.gr/hint-kb/), a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, cal-culatesasetoffeaturesofinterest and computesaconfidence score for every candidate protein interaction. This confidence score is essential for filtering the false positive interactions which are present in existing databases, predicting new protein interactions and measuring the frequency of each true protein interaction. For this reason, a novel machine learning hybrid methodology, called (Evolutionary Kalman Mathematical Modelling—EvoKalMaModel), was used to achieve an accurate and interpretable scoring methodology. The experimental results indicated that the proposed scoring scheme outperforms existing computational methods for the prediction of PPIs.

Human-Chromatin-Related Protein Interactions Identify a Demethylase Complex Required for Chromosome Segregation

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Edyta Marcon

2014-07-01

Full Text Available Chromatin regulation is driven by multicomponent protein complexes, which form functional modules. Deciphering the components of these modules and their interactions is central to understanding the molecular pathways these proteins are regulating, their functions, and their relation to both normal development and disease. We describe the use of affinity purifications of tagged human proteins coupled with mass spectrometry to generate a protein-protein interaction map encompassing known and predicted chromatin-related proteins. On the basis of 1,394 successful purifications of 293 proteins, we report a high-confidence (85% precision network involving 11,464 protein-protein interactions among 1,738 different human proteins, grouped into 164 often overlapping protein complexes with a particular focus on the family of JmjC-containing lysine demethylases, their partners, and their roles in chromatin remodeling. We show that RCCD1 is a partner of histone H3K36 demethylase KDM8 and demonstrate that both are important for cell-cycle-regulated transcriptional repression in centromeric regions and accurate mitotic division.

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

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Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Interaction between human BAP31 and respiratory syncytial virus small hydrophobic (SH) protein

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Li, Yan; Jain, Neeraj; Limpanawat, Suweeraya; To, Janet; Quistgaard, Esben M.; Nordlund, Par; Thanabalu, Thirumaran; Torres, Jaume

2015-01-01

The small hydrophobic (SH) protein is a short channel-forming polypeptide encoded by the human respiratory syncytial virus (hRSV). Deletion of SH protein leads to the viral attenuation in mice and primates, and delayed apoptosis in infected cells. We have used a membrane-based yeast two-hybrid system (MbY2H) and a library from human lung cDNA to detect proteins that bind SH protein. This led to the identification of a membrane protein, B-cell associated protein 31 (BAP31). Transfected SH protein co-localizes with transfected BAP31 in cells, and pulls down endogenous BAP31. Titration of purified C-terminal endodomain of BAP31 against isotopically labeled SH protein in detergent micelles suggests direct interaction between the two proteins. Given the key role of BAP31 in protein trafficking and its critical involvement in pro- and anti-apoptotic pathways, this novel interaction may constitute a potential drug target. - Highlights: • A yeast two-hybrid system (MbY2H) detected BAP31 as a binder of RSV SH protein. • Transfected SH and BAP31 co-localize in lung epithelial cells. • Endogenous BAP31 is pulled down by RSV SH protein. • BAP31 endodomain interacts with the N-terminal α-helix of SH protein in micelles. • This interaction is proposed to be a potential drug target

Interaction between human BAP31 and respiratory syncytial virus small hydrophobic (SH) protein

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Li, Yan; Jain, Neeraj; Limpanawat, Suweeraya; To, Janet [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Quistgaard, Esben M. [Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm (Sweden); Nordlund, Par [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm (Sweden); Thanabalu, Thirumaran [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Torres, Jaume, E-mail: jtorres@ntu.edu.sg [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore)

2015-08-15

The small hydrophobic (SH) protein is a short channel-forming polypeptide encoded by the human respiratory syncytial virus (hRSV). Deletion of SH protein leads to the viral attenuation in mice and primates, and delayed apoptosis in infected cells. We have used a membrane-based yeast two-hybrid system (MbY2H) and a library from human lung cDNA to detect proteins that bind SH protein. This led to the identification of a membrane protein, B-cell associated protein 31 (BAP31). Transfected SH protein co-localizes with transfected BAP31 in cells, and pulls down endogenous BAP31. Titration of purified C-terminal endodomain of BAP31 against isotopically labeled SH protein in detergent micelles suggests direct interaction between the two proteins. Given the key role of BAP31 in protein trafficking and its critical involvement in pro- and anti-apoptotic pathways, this novel interaction may constitute a potential drug target. - Highlights: • A yeast two-hybrid system (MbY2H) detected BAP31 as a binder of RSV SH protein. • Transfected SH and BAP31 co-localize in lung epithelial cells. • Endogenous BAP31 is pulled down by RSV SH protein. • BAP31 endodomain interacts with the N-terminal α-helix of SH protein in micelles. • This interaction is proposed to be a potential drug target.

Interaction of Proteins Identified in Human Thyroid Cells

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Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

2013-01-01

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

Interaction of Proteins Identified in Human Thyroid Cells

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Jessica Pietsch

2013-01-01

Full Text Available Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains.

The bone morphogenetic protein antagonist gremlin 1 is overexpressed in human cancers and interacts with YWHAH protein

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Namkoong, Hong; Shin, Seung Min; Kim, Hyun Kee; Ha, Seon-Ah; Cho, Goang Won; Hur, Soo Young; Kim, Tae Eung; Kim, Jin Woo

2006-01-01

Basic studies of oncogenesis have demonstrated that either the elevated production of particular oncogene proteins or the occurrence of qualitative abnormalities in oncogenes can contribute to neoplastic cellular transformation. The purpose of our study was to identify an unique gene that shows cancer-associated expression, and characterizes its function related to human carcinogenesis. We used the differential display (DD) RT-PCR method using normal cervical, cervical cancer, metastatic cervical tissues, and cervical cancer cell lines to identify genes overexpressed in cervical cancers and identified gremlin 1 which was overexpressed in cervical cancers. We determined expression levels of gremlin 1 using Northern blot analysis and immunohistochemical study in various types of human normal and cancer tissues. To understand the tumorigenesis pathway of identified gremlin 1 protein, we performed a yeast two-hybrid screen, GST pull down assay, and immunoprecipitation to identify gremlin 1 interacting proteins. DDRT-PCR analysis revealed that gremlin 1 was overexpressed in uterine cervical cancer. We also identified a human gremlin 1 that was overexpressed in various human tumors including carcinomas of the lung, ovary, kidney, breast, colon, pancreas, and sarcoma. PIG-2-transfected HEK 293 cells exhibited growth stimulation and increased telomerase activity. Gremlin 1 interacted with homo sapiens tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, eta polypeptide (14-3-3 eta; YWHAH). YWHAH protein binding site for gremlin 1 was located between residues 61–80 and gremlin 1 binding site for YWHAH was found to be located between residues 1 to 67. Gremlin 1 may play an oncogenic role especially in carcinomas of the uterine cervix, lung, ovary, kidney, breast, colon, pancreas, and sarcoma. Over-expressed gremlin 1 functions by interaction with YWHAH. Therefore, Gremlin 1 and its binding protein YWHAH could be good targets for developing diagnostic and

Human UBL5 protein interacts with coilin and meets the Cajal bodies

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Švéda, Martin; Častorálová, Markéta; Lipov, Jan; Ruml, Tomáš; Knejzlík, Zdeněk

2013-01-01

Highlights: •Localization of the UBL5 protein in Hela cells was determined by fluorescence microscopy and biochemical fractionation. •Colocalization of UBL5 with Cajal bodies was observed. •Interaction of UBL5 with coilin was proven by pull-down. -- Abstract: UBL5 protein, a structural homologue of ubiquitin, was shown to be involved in pre-mRNA splicing and transcription regulation in yeast and Caenorhabditis elegans, respectively. However, role of the UBL5 human orthologue is still elusive. In our study, we observed that endogenous human UBL5 that was localized in the nucleus, partially associates with Cajal bodies (CBs), nuclear domains where spliceosomal components are assembled. Simultaneous expression of exogenous UBL5 and coilin resulted in their nuclear colocalization in HeLa cells. The ability of UBL5 to interact with coilin was proved by GST pull-down assay using coilin that was either in vitro translated or extracted from HEK293T cells. Further, our results showed that the UBL5–coilin interaction was not influenced by coilin phosphorylation. These results suggest that UBL5 could be targeted to CBs via its interaction with coilin. Relation between human UBL5 protein and CBs is in the agreement with current observations about yeast orthologue Hub1 playing important role in alternative splicing

Human UBL5 protein interacts with coilin and meets the Cajal bodies

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Švéda, Martin; Častorálová, Markéta; Lipov, Jan; Ruml, Tomáš; Knejzlík, Zdeněk, E-mail: knejzliz@vscht.cz

2013-06-28

Highlights: •Localization of the UBL5 protein in Hela cells was determined by fluorescence microscopy and biochemical fractionation. •Colocalization of UBL5 with Cajal bodies was observed. •Interaction of UBL5 with coilin was proven by pull-down. -- Abstract: UBL5 protein, a structural homologue of ubiquitin, was shown to be involved in pre-mRNA splicing and transcription regulation in yeast and Caenorhabditis elegans, respectively. However, role of the UBL5 human orthologue is still elusive. In our study, we observed that endogenous human UBL5 that was localized in the nucleus, partially associates with Cajal bodies (CBs), nuclear domains where spliceosomal components are assembled. Simultaneous expression of exogenous UBL5 and coilin resulted in their nuclear colocalization in HeLa cells. The ability of UBL5 to interact with coilin was proved by GST pull-down assay using coilin that was either in vitro translated or extracted from HEK293T cells. Further, our results showed that the UBL5–coilin interaction was not influenced by coilin phosphorylation. These results suggest that UBL5 could be targeted to CBs via its interaction with coilin. Relation between human UBL5 protein and CBs is in the agreement with current observations about yeast orthologue Hub1 playing important role in alternative splicing.

Aquaporin Protein-Protein Interactions

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Jennifer Virginia Roche

2017-10-01

Full Text Available Aquaporins are tetrameric membrane-bound channels that facilitate transport of water and other small solutes across cell membranes. In eukaryotes, they are frequently regulated by gating or trafficking, allowing for the cell to control membrane permeability in a specific manner. Protein–protein interactions play crucial roles in both regulatory processes and also mediate alternative functions such as cell adhesion. In this review, we summarize recent knowledge about aquaporin protein–protein interactions; dividing the interactions into three types: (1 interactions between aquaporin tetramers; (2 interactions between aquaporin monomers within a tetramer (hetero-tetramerization; and (3 transient interactions with regulatory proteins. We particularly focus on the structural aspects of the interactions, discussing the small differences within a conserved overall fold that allow for aquaporins to be differentially regulated in an organism-, tissue- and trigger-specific manner. A deep knowledge about these differences is needed to fully understand aquaporin function and regulation in many physiological processes, and may enable design of compounds targeting specific aquaporins for treatment of human disease.

Interactions of the human MCM-BP protein with MCM complex components and Dbf4.

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Tin Nguyen

Full Text Available MCM-BP was discovered as a protein that co-purified from human cells with MCM proteins 3 through 7; results which were recapitulated in frogs, yeast and plants. Evidence in all of these organisms supports an important role for MCM-BP in DNA replication, including contributions to MCM complex unloading. However the mechanisms by which MCM-BP functions and associates with MCM complexes are not well understood. Here we show that human MCM-BP is capable of interacting with individual MCM proteins 2 through 7 when co-expressed in insect cells and can greatly increase the recovery of some recombinant MCM proteins. Glycerol gradient sedimentation analysis indicated that MCM-BP interacts most strongly with MCM4 and MCM7. Similar gradient analyses of human cell lysates showed that only a small amount of MCM-BP overlapped with the migration of MCM complexes and that MCM complexes were disrupted by exogenous MCM-BP. In addition, large complexes containing MCM-BP and MCM proteins were detected at mid to late S phase, suggesting that the formation of specific MCM-BP complexes is cell cycle regulated. We also identified an interaction between MCM-BP and the Dbf4 regulatory component of the DDK kinase in both yeast 2-hybrid and insect cell co-expression assays, and this interaction was verified by co-immunoprecipitation of endogenous proteins from human cells. In vitro kinase assays showed that MCM-BP was not a substrate for DDK but could inhibit DDK phosphorylation of MCM4,6,7 within MCM4,6,7 or MCM2-7 complexes, with little effect on DDK phosphorylation of MCM2. Since DDK is known to activate DNA replication through phosphorylation of these MCM proteins, our results suggest that MCM-BP may affect DNA replication in part by regulating MCM phosphorylation by DDK.

Interactions of the human MCM-BP protein with MCM complex components and Dbf4.

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Nguyen, Tin; Jagannathan, Madhav; Shire, Kathy; Frappier, Lori

2012-01-01

MCM-BP was discovered as a protein that co-purified from human cells with MCM proteins 3 through 7; results which were recapitulated in frogs, yeast and plants. Evidence in all of these organisms supports an important role for MCM-BP in DNA replication, including contributions to MCM complex unloading. However the mechanisms by which MCM-BP functions and associates with MCM complexes are not well understood. Here we show that human MCM-BP is capable of interacting with individual MCM proteins 2 through 7 when co-expressed in insect cells and can greatly increase the recovery of some recombinant MCM proteins. Glycerol gradient sedimentation analysis indicated that MCM-BP interacts most strongly with MCM4 and MCM7. Similar gradient analyses of human cell lysates showed that only a small amount of MCM-BP overlapped with the migration of MCM complexes and that MCM complexes were disrupted by exogenous MCM-BP. In addition, large complexes containing MCM-BP and MCM proteins were detected at mid to late S phase, suggesting that the formation of specific MCM-BP complexes is cell cycle regulated. We also identified an interaction between MCM-BP and the Dbf4 regulatory component of the DDK kinase in both yeast 2-hybrid and insect cell co-expression assays, and this interaction was verified by co-immunoprecipitation of endogenous proteins from human cells. In vitro kinase assays showed that MCM-BP was not a substrate for DDK but could inhibit DDK phosphorylation of MCM4,6,7 within MCM4,6,7 or MCM2-7 complexes, with little effect on DDK phosphorylation of MCM2. Since DDK is known to activate DNA replication through phosphorylation of these MCM proteins, our results suggest that MCM-BP may affect DNA replication in part by regulating MCM phosphorylation by DDK.

Wiki-pi: a web-server of annotated human protein-protein interactions to aid in discovery of protein function.

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Naoki Orii

Full Text Available Protein-protein interactions (PPIs are the basis of biological functions. Knowledge of the interactions of a protein can help understand its molecular function and its association with different biological processes and pathways. Several publicly available databases provide comprehensive information about individual proteins, such as their sequence, structure, and function. There also exist databases that are built exclusively to provide PPIs by curating them from published literature. The information provided in these web resources is protein-centric, and not PPI-centric. The PPIs are typically provided as lists of interactions of a given gene with links to interacting partners; they do not present a comprehensive view of the nature of both the proteins involved in the interactions. A web database that allows search and retrieval based on biomedical characteristics of PPIs is lacking, and is needed. We present Wiki-Pi (read Wiki-π, a web-based interface to a database of human PPIs, which allows users to retrieve interactions by their biomedical attributes such as their association to diseases, pathways, drugs and biological functions. Each retrieved PPI is shown with annotations of both of the participant proteins side-by-side, creating a basis to hypothesize the biological function facilitated by the interaction. Conceptually, it is a search engine for PPIs analogous to PubMed for scientific literature. Its usefulness in generating novel scientific hypotheses is demonstrated through the study of IGSF21, a little-known gene that was recently identified to be associated with diabetic retinopathy. Using Wiki-Pi, we infer that its association to diabetic retinopathy may be mediated through its interactions with the genes HSPB1, KRAS, TMSB4X and DGKD, and that it may be involved in cellular response to external stimuli, cytoskeletal organization and regulation of molecular activity. The website also provides a wiki-like capability allowing users

Viral Organization of Human Proteins

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Wuchty, Stefan; Siwo, Geoffrey; Ferdig, Michael T.

2010-01-01

Although maps of intracellular interactions are increasingly well characterized, little is known about large-scale maps of host-pathogen protein interactions. The investigation of host-pathogen interactions can reveal features of pathogenesis and provide a foundation for the development of drugs and disease prevention strategies. A compilation of experimentally verified interactions between HIV-1 and human proteins and a set of HIV-dependency factors (HDF) allowed insights into the topology and intricate interplay between viral and host proteins on a large scale. We found that targeted and HDF proteins appear predominantly in rich-clubs, groups of human proteins that are strongly intertwined among each other. These assemblies of proteins may serve as an infection gateway, allowing the virus to take control of the human host by reaching protein pathways and diversified cellular functions in a pronounced and focused way. Particular transcription factors and protein kinases facilitate indirect interactions between HDFs and viral proteins. Discerning the entanglement of directly targeted and indirectly interacting proteins may uncover molecular and functional sites that can provide novel perspectives on the progression of HIV infection and highlight new avenues to fight this virus. PMID:20827298

Quantitative analysis of the interaction between the envelope protein domains and the core protein of human hepatitis B virus

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Choi, Kyoung-Jae; Lim, Chun-Woo; Yoon, Moon-Young; Ahn, Byung-Yoon; Yu, Yeon Gyu

2004-01-01

Interaction between preformed nucleocapsids and viral envelope proteins is critical for the assembly of virus particles in infected cells. The pre-S1 and pre-S2 and cytosolic regions of the human hepatitis B virus envelope protein had been implicated in the interaction with the core protein of nucleocapsids. The binding affinities of specific subdomains of the envelope protein to the core protein were quantitatively measured by both ELISA and BIAcore assay. While a marginal binding was detected with the pre-S1 or pre-S2, the core protein showed high affinities to pre-S with apparent dissociation constants (K D app ) of 7.3 ± 0.9 and 8.2 ± 0.4 μM by ELISA and BIAcore assay, respectively. The circular dichroism analysis suggested that conformational change occurs in pre-S through interaction with core protein. These results substantiate the importance of specific envelope domains in virion assembly, and demonstrate that the interaction between viral proteins can be quantitatively measured in vitro

Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

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Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

2018-01-16

"A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

Human HOX Proteins Use Diverse and Context-Dependent Motifs to Interact with TALE Class Cofactors.

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Dard, Amélie; Reboulet, Jonathan; Jia, Yunlong; Bleicher, Françoise; Duffraisse, Marilyne; Vanaker, Jean-Marc; Forcet, Christelle; Merabet, Samir

2018-03-13

HOX proteins achieve numerous functions by interacting with the TALE class PBX and MEIS cofactors. In contrast to this established partnership in development and disease, how HOX proteins could interact with PBX and MEIS remains unclear. Here, we present a systematic analysis of HOX/PBX/MEIS interaction properties, scanning all paralog groups with human and mouse HOX proteins in vitro and in live cells. We demonstrate that a previously characterized HOX protein motif known to be critical for HOX-PBX interactions becomes dispensable in the presence of MEIS in all except the two most anterior paralog groups. We further identify paralog-specific TALE-binding sites that are used in a highly context-dependent manner. One of these binding sites is involved in the proliferative activity of HOXA7 in breast cancer cells. Together these findings reveal an extraordinary level of interaction flexibility between HOX proteins and their major class of developmental cofactors. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Screening for proteins interacting with MCM7 in human lung cancer library using yeast two hybrid system

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Yuchen HAN

2008-08-01

Full Text Available Background and objective MCM7 is a subunit of the MCM complex that plays a key role in DNA replication initiation. But little is known about its interaction proteins. In this study yeast two hybrid screening was used to identify the MCM7 interacting proteins. Methods Yeast expression vector containing human full length MCM7-pGBKT7 plasmid was constructed, and with a library of cDNAs from human lung cancer-pACT2 plasmid was transformed into yeast strain AH109, and was electively grew in X-a-gal auxotrophy medium SD/-Trp-Leu-His-Ade, and the blue colonies were picked up, the plasmid of the yeast colonies was extracted , and transformed into E. Coli to extract DNA and performed sequence analysis. Results Eleven proteins were identified which could specifically interact with MCM7 proteins, among these five were cytoskeleton proteins, six were enzymes, kinases and related receptors. Conclusion The investigation provides functional clues for further exploration of MCM7 gene.

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

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He Weiming

2010-07-01

Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Duplicability of self-interacting human genes.

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Pérez-Bercoff, Asa

2010-01-01

BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

Quality control methodology for high-throughput protein-protein interaction screening.

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Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

Evaluation of two novel leptospiral proteins for their interaction with human host components.

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Silva, Lucas P; Fernandes, Luis G V; Vieira, Monica L; de Souza, Gisele O; Heinemann, Marcos B; Vasconcellos, Silvio A; Romero, Eliete C; Nascimento, Ana L T O

2016-07-01

Pathogenic species of the genus Leptospira are the etiological agents of leptospirosis, the most widespread zoonosis. Mechanisms involved in leptospiral pathogenesis are not well understood. By data mining the genome sequences of Leptospira interrogans we have identified two proteins predicted to be surface exposed, LIC10821 and LIC10064. Immunofluorescence and proteinase K assays confirmed that the proteins are exposed. Reactivity of the recombinant proteins with human sera has shown that rLIC10821, but not rLIC10064, is recognized by antibodies in confirmed leptospirosis serum samples, suggesting its expression during infection. The rLIC10821 was able to bind laminin, in a dose-dependent fashion, and was called Lsa37 (leptospiral surface adhesin of 37 kDa). Studies with human plasma components demonstrated that rLIC10821 interacts with plasminogen (PLG) and fibrinogen (Fg). The binding of Lsa37 with PLG generates plasmin when PLG activator was added. Fibrin clotting reduction was observed in a thrombin-catalyzed reaction, when Fg was incubated with Lsa37, suggesting that this protein may interfere in the coagulation cascade during the disease. Although LIC10064 protein is more abundant than the corresponding Lsa37, binding activity with all the components tested was not detected. Thus, Lsa37 is a novel versatile adhesin that may mediate Leptospira-host interactions. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identification of New Protein Interactions between Dengue Fever Virus and Its Hosts, Human and Mosquito

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Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L.

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host – dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies. PMID:23326450

Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito.

Science.gov (United States)

Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host - dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.

Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito.

Directory of Open Access Journals (Sweden)

Dumrong Mairiang

Full Text Available The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host - dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.

A conserved mammalian protein interaction network.

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Åsa Pérez-Bercoff

Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Identification of human hnRNP C1/C2 as a dengue virus NS1-interacting protein

International Nuclear Information System (INIS)

Noisakran, Sansanee; Sengsai, Suchada; Thongboonkerd, Visith; Kanlaya, Rattiyaporn; Sinchaikul, Supachok; Chen, Shui-Tein; Puttikhunt, Chunya

2008-01-01

Dengue virus nonstructural protein 1 (NS1) is a key glycoprotein involved in the production of infectious virus and the pathogenesis of dengue diseases. Very little is known how NS1 interacts with host cellular proteins and functions in dengue virus-infected cells. This study aimed at identifying NS1-interacting host cellular proteins in dengue virus-infected cells by employing co-immunoprecipitation, two-dimensional gel electrophoresis, and mass spectrometry. Using lysates of dengue virus-infected human embryonic kidney cells (HEK 293T), immunoprecipitation with an anti-NS1 monoclonal antibody revealed eight isoforms of dengue virus NS1 and a 40-kDa protein, which was subsequently identified by quadrupole time-of-flight tandem mass spectrometry (Q-TOF MS/MS) as human heterogeneous nuclear ribonucleoprotein (hnRNP) C1/C2. Further investigation by co-immunoprecipitation and co-localization confirmed the association of hnRNP C1/C2 and dengue virus NS1 proteins in dengue virus-infected cells. Their interaction may have implications in virus replication and/or cellular responses favorable to survival of the virus in host cells

TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteins

KAUST Repository

Schaefer, Ulf; Schmeier, Sebastian; Bajic, Vladimir B.

2010-01-01

The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF-DNA binding, protein-protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/. © The Author(s) 2010.

TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteins

KAUST Repository

Schaefer, Ulf

2010-10-21

The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF-DNA binding, protein-protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/. © The Author(s) 2010.

Role of Receptor-Interacting Protein 140 in human fat cells

Directory of Open Access Journals (Sweden)

Stenson Britta M

2010-01-01

Full Text Available Abstract Background Mice lacking Receptor-interacting protein 140 (RIP140 have reduced body fat which at least partly is mediated through increased lipid and glucose metabolism in adipose tissue. In humans, RIP140 is lower expressed in visceral white adipose tissue (WAT of obese versus lean subjects. We investigated the role of RIP140 in human subcutaneous WAT, which is the major fat depot of the body. Methods Messenger RNA levels of RIP140 were measured in samples of subcutaneous WAT from women with a wide variation in BMI and in different human WAT preparations. RIP140 mRNA was knocked down with siRNA in in vitro differentiated adipocytes and the impact on glucose transport and mRNA levels of target genes determined. Results RIP140 mRNA levels in subcutaneous WAT were decreased among obese compared to lean women and increased by weight-loss, but did not associate with mitochondrial DNA copy number. RIP140 expression increased during adipocyte differentiation in vitro and was higher in isolated adipocytes compared to corresponding pieces of WAT. Knock down of RIP140 increased basal glucose transport and mRNA levels of glucose transporter 4 and uncoupling protein-1. Conclusions Human RIP140 inhibits glucose uptake and the expression of genes promoting energy expenditure in the same fashion as the murine orthologue. Increased levels of human RIP140 in subcutaneous WAT of lean subjects may contribute to economize on energy stores. By contrast, the function and expression pattern does not support that RIP140 regulate human obesity.

Targeting protein-protein interactions for parasite control.

Directory of Open Access Journals (Sweden)

Christina M Taylor

2011-04-01

Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

Protein-protein interactions and cancer: targeting the central dogma.

Science.gov (United States)

Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

Science.gov (United States)

Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

Directory of Open Access Journals (Sweden)

Peng Liu

2015-01-01

Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

Specificity and functional interaction of the polymerase complex proteins of human and avian metapneumoviruses

NARCIS (Netherlands)

M.T. de Graaf (Marieke); S. Herfst (Sander); E.J.A. Schrauwen (Eefje); Y. Choi (Ying); B.G. van den Hoogen (Bernadette); A.D.M.E. Osterhaus (Albert); R.A.M. Fouchier (Ron)

2008-01-01

textabstractHuman metapneumovirus (HMPV) and avian metapneumovirus (AMPV) have a similar genome organization and protein composition, but a different host range. AMPV subgroup C (AMPV-C) is more closely relaled to HMPV than other AMPVs. To investigate the specificity and functional interaction of

Interaction of thorium with human blood proteins: relevance to the development of strategies for actinide decorporation

International Nuclear Information System (INIS)

Ali, Manjoor; Kumar, Amit; Pandey, Badri N.

2016-01-01

Thorium-232 (Th), a naturally-available actinide is emerging as an alternative source of nuclear fuel for energy generation in India and other countries. Therefore, understanding the biological interaction of Th and other lanthanides (Ln) related to Th fuel cycle would enable its efficient utilization with adequate human health and environmental protection. Studies on complexation behavior of Th with human blood proteins would yield a rationale insight for the development of potential chelation based strategies for decorporation of Th. Present study was carried out to characterize the site of interaction of Th/other Ln ions with the two most abundant protein of blood, human serum albumin (HSA) and hemoglobin (Hb). Using various spectroscopic techniques (UV-VIS, FT-IR, Raman, Fluorescence and Circular dichroism), results showed that Th interacts with carbonyl/amide groups of HSA and alters its secondary conformation. These effects of Th were compared with U and Ln ions. Comparing the structural/protein unfolding effects of these metals, ionic potential of metal ions seemed to determine their toxic action at protein level. In blood, Hb is the most abundant Fe-containing protein, transporting oxygen to the various parts of the body. Th and other metal ions were found to interact with peptide and heme sites of Hb depending upon the concentration. Results elucidated that the metal ions,Th and Ce(IV), which charge-ionic-radii-ratio are close to Fe(III), affected heme significantly as compared to metal ions of lower or higher charge-ionic-radii-ratio (La(III), Ce(III) and U(VI)). These results were found consistent to the effect of Th and Ce(IV) on oxygen-binding ability of Hb. In addition, deeper insight about binding characteristics of Th with HSA and Hb would have important implications for the development of decorporating agents for the biomedical management of actinides-induced toxicity. (author)

Interacting proteins on human spermatozoa: adaptive evolution of the binding of semenogelin I to EPPIN.

Directory of Open Access Journals (Sweden)

Erick J R Silva

Full Text Available Semenogelin I (SEMG1 is found in human semen coagulum and on the surface of spermatozoa bound to EPPIN. The physiological significance of the SEMG1/EPPIN interaction on the surface of spermatozoa is its capacity to modulate sperm progressive motility. The present study investigates the hypothesis that the interacting surface of SEMG1 and EPPIN co-evolved within the Hominoidea time scale, as a result of adaptive pressures applied by their roles in sperm protection and reproductive fitness. Our results indicate that some amino acid residues of SEMG1 and EPPIN possess a remarkable deficiency of variation among hominoid primates. We observe a distinct residue change unique to humans within the EPPIN sequence containing a SEMG1 interacting surface, namely His92. In addition, Bayes Empirical Bayes analysis for positive selection indicates that the SEMG1 Cys239 residue underwent positive selection in humans, probably as a consequence of its role in increasing the binding affinity of these interacting proteins. We confirm the critical role of Cys239 residue for SEMG1 binding to EPPIN and inhibition of sperm motility by showing that recombinant SEMG1 mutants in which Cys239 residue was changed to glycine, aspartic acid, histidine, serine or arginine have reduced capacity to interact to EPPIN and to inhibit human sperm motility in vitro. In conclusion, our results indicate that EPPIN and SEMG1 rapidly co-evolved in primates due to their critical role in the modulation of sperm motility in the semen coagulum, providing unique insights into the molecular co-evolution of sperm surface interacting proteins.

A credit-card library approach for disrupting protein-protein interactions.

Science.gov (United States)

Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

2006-04-15

Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

Directory of Open Access Journals (Sweden)

Wuchty Stefan

2006-05-01

Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

Human microcephaly protein RTTN interacts with STIL and is required to build full-length centrioles.

Science.gov (United States)

Chen, Hsin-Yi; Wu, Chien-Ting; Tang, Chieh-Ju C; Lin, Yi-Nan; Wang, Won-Jing; Tang, Tang K

2017-08-15

Mutations in many centriolar protein-encoding genes cause primary microcephaly. Using super-resolution and electron microscopy, we find that the human microcephaly protein, RTTN, is recruited to the proximal end of the procentriole at early S phase, and is located at the inner luminal walls of centrioles. Further studies demonstrate that RTTN directly interacts with STIL and acts downstream of STIL-mediated centriole assembly. CRISPR/Cas9-mediated RTTN gene knockout in p53-deficient cells induce amplification of primitive procentriole bodies that lack the distal-half centriolar proteins, POC5 and POC1B. Additional analyses show that RTTN serves as an upstream effector of CEP295, which mediates the loading of POC1B and POC5 to the distal-half centrioles. Interestingly, the naturally occurring microcephaly-associated mutant, RTTN (A578P), shows a low affinity for STIL binding and blocks centriole assembly. These findings reveal that RTTN contributes to building full-length centrioles and illuminate the molecular mechanism through which the RTTN (A578P) mutation causes primary microcephaly.Mutations in many centriolar protein-encoding genes cause primary microcephaly. Here the authors show that human microcephaly protein RTTN directly interacts with STIL and acts downstream of STIL-mediated centriole assembly, contributing to building full-length centrioles.

Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

Directory of Open Access Journals (Sweden)

Vandepoele Klaas

2009-06-01

Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Evidence for the interaction of the regulatory protein Ki-1/57 with p53 and its interacting proteins

International Nuclear Information System (INIS)

Nery, Flavia C.; Rui, Edmilson; Kuniyoshi, Tais M.; Kobarg, Joerg

2006-01-01

Ki-1/57 is a cytoplasmic and nuclear phospho-protein of 57 kDa and interacts with the adaptor protein RACK1, the transcription factor MEF2C, and the chromatin remodeling factor CHD3, suggesting that it might be involved in the regulation of transcription. Here, we describe yeast two-hybrid studies that identified a total of 11 proteins interacting with Ki-1/57, all of which interact or are functionally associated with p53 or other members of the p53 family of proteins. We further found that Ki-1/57 is able to interact with p53 itself in the yeast two-hybrid system when the interaction was tested directly. This interaction could be confirmed by pull down assays with purified proteins in vitro and by reciprocal co-immunoprecipitation assays from the human Hodgkin analogous lymphoma cell line L540. Furthermore, we found that the phosphorylation of p53 by PKC abolishes its interaction with Ki-1/57 in vitro

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

Science.gov (United States)

Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

2017-12-01

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

Proteomic identification of dysferlin-interacting protein complexes in human vascular endothelium

International Nuclear Information System (INIS)

Leung, Cleo; Utokaparch, Soraya; Sharma, Arpeeta; Yu, Carol; Abraham, Thomas; Borchers, Christoph; Bernatchez, Pascal

2011-01-01

Highlights: ► Bi-directional (inward and outward) movement of GFP-dysferlin in COS-7 cells. ► Dysferlin interacts with key signaling proteins for transcytosis in EC. ► Dysferlin mediates trafficking of vesicles carrying protein cargos in EC. -- Abstract: Dysferlin is a membrane-anchored protein known to facilitate membrane repair in skeletal muscles following mechanical injury. Mutations of dysferlin gene impair sarcolemma integrity, a hallmark of certain forms of muscular dystrophy in patients. Dysferlin contains seven calcium-dependent C2 binding domains, which are required to promote fusion of intracellular membrane vesicles. Emerging evidence reveal the unexpected expression of dysferlin in non-muscle, non-mechanically active tissues, such as endothelial cells, which cast doubts over the belief that ferlin proteins act exclusively as membrane repair proteins. We and others have shown that deficient trafficking of membrane bound proteins in dysferlin-deficient cells, suggesting that dysferlin might mediate trafficking of client proteins. Herein, we describe the intracellular trafficking and movement of GFP-dysferlin positive vesicles in unfixed reconstituted cells using live microscopy. By performing GST pull-down assays followed by mass spectrometry, we identified dysferlin binding protein complexes in human vascular endothelial cells. Together, our data further support the claims that dysferlin not only mediates membrane repair but also trafficking of client proteins, ultimately, help bridging dysferlinopathies to aberrant membrane signaling.

Proteomic identification of dysferlin-interacting protein complexes in human vascular endothelium

Energy Technology Data Exchange (ETDEWEB)

Leung, Cleo; Utokaparch, Soraya; Sharma, Arpeeta; Yu, Carol; Abraham, Thomas; Borchers, Christoph [UBC James Hogg Research Centre, Institute for Heart and Lung Health, Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, British Columbia (Canada); University of Victoria - Genome BC Proteomics Centre, University of Victoria, Victoria, British Columbia (Canada); Bernatchez, Pascal, E-mail: pbernatc@mail.ubc.ca [UBC James Hogg Research Centre, Institute for Heart and Lung Health, Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, British Columbia (Canada); University of Victoria - Genome BC Proteomics Centre, University of Victoria, Victoria, British Columbia (Canada)

2011-11-18

Highlights: Black-Right-Pointing-Pointer Bi-directional (inward and outward) movement of GFP-dysferlin in COS-7 cells. Black-Right-Pointing-Pointer Dysferlin interacts with key signaling proteins for transcytosis in EC. Black-Right-Pointing-Pointer Dysferlin mediates trafficking of vesicles carrying protein cargos in EC. -- Abstract: Dysferlin is a membrane-anchored protein known to facilitate membrane repair in skeletal muscles following mechanical injury. Mutations of dysferlin gene impair sarcolemma integrity, a hallmark of certain forms of muscular dystrophy in patients. Dysferlin contains seven calcium-dependent C2 binding domains, which are required to promote fusion of intracellular membrane vesicles. Emerging evidence reveal the unexpected expression of dysferlin in non-muscle, non-mechanically active tissues, such as endothelial cells, which cast doubts over the belief that ferlin proteins act exclusively as membrane repair proteins. We and others have shown that deficient trafficking of membrane bound proteins in dysferlin-deficient cells, suggesting that dysferlin might mediate trafficking of client proteins. Herein, we describe the intracellular trafficking and movement of GFP-dysferlin positive vesicles in unfixed reconstituted cells using live microscopy. By performing GST pull-down assays followed by mass spectrometry, we identified dysferlin binding protein complexes in human vascular endothelial cells. Together, our data further support the claims that dysferlin not only mediates membrane repair but also trafficking of client proteins, ultimately, help bridging dysferlinopathies to aberrant membrane signaling.

Potential disruption of protein-protein interactions by graphene oxide

International Nuclear Information System (INIS)

Feng, Mei; Kang, Hongsuk; Luan, Binquan; Yang, Zaixing; Zhou, Ruhong

2016-01-01

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide

Energy Technology Data Exchange (ETDEWEB)

Feng, Mei [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Kang, Hongsuk; Luan, Binquan [Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Yang, Zaixing [Institute of Quantitative Biology and Medicine, SRMP and RAD-X, and Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou 215123 (China); Zhou, Ruhong, E-mail: ruhong@us.ibm.com [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Department of Chemistry, Columbia University, New York, New York 10027 (United States)

2016-06-14

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.

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Suyu Mei

Full Text Available Reconstruction of host-pathogen protein interaction networks is of great significance to reveal the underlying microbic pathogenesis. However, the current experimentally-derived networks are generally small and should be augmented by computational methods for less-biased biological inference. From the point of view of computational modelling, data scarcity, data unavailability and negative data sampling are the three major problems for host-pathogen protein interaction networks reconstruction. In this work, we are motivated to address the three concerns and propose a probability weighted ensemble transfer learning model for HIV-human protein interaction prediction (PWEN-TLM, where support vector machine (SVM is adopted as the individual classifier of the ensemble model. In the model, data scarcity and data unavailability are tackled by homolog knowledge transfer. The importance of homolog knowledge is measured by the ROC-AUC metric of the individual classifiers, whose outputs are probability weighted to yield the final decision. In addition, we further validate the assumption that only the homolog knowledge is sufficient to train a satisfactory model for host-pathogen protein interaction prediction. Thus the model is more robust against data unavailability with less demanding data constraint. As regards with negative data construction, experiments show that exclusiveness of subcellular co-localized proteins is unbiased and more reliable than random sampling. Last, we conduct analysis of overlapped predictions between our model and the existing models, and apply the model to novel host-pathogen PPIs recognition for further biological research.

Database of Interacting Proteins (DIP)

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U.S. Department of Health & Human Services — The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent...

Interaction of an atypical Plasmodium falciparum ETRAMP with human apolipoproteins

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Sahasrabudhe Sudhir

2008-10-01

Full Text Available Abstract Background In order to establish a successful infection in the human host, the malaria parasite Plasmodium falciparum must establish interactions with a variety of human proteins on the surface of different cell types, as well as with proteins inside the host cells. To better understand this aspect of malaria pathogenesis, a study was conducted with the goal of identifying interactions between proteins of the parasite and those of its human host. Methods A modified yeast two-hybrid methodology that preferentially selects protein fragments that can be expressed in yeast was used to conduct high-throughput screens with P. falciparum protein fragments against human liver and cerebellum libraries. The resulting dataset was analyzed to exclude interactions that are not likely to occur in the human host during infection. Results An initial set of 2,200 interactions was curated to remove proteins that are unlikely to play a role in pathogenesis based on their annotation or localization, and proteins that behave promiscuously in the two-hybrid assay, resulting in a final dataset of 456 interactions. A cluster that implicates binding between P. falciparum PFE1590w/ETRAMP5, a putative parasitophorous vacuole membrane protein, and human apolipoproteins ApoA, ApoB and ApoE was selected for further analysis. Different isoforms of ApoE, which are associated with different outcomes of malaria infection, were shown to display differential interactions with PFE1590w. Conclusion A dataset of interactions between proteins of P. falciparum and those of its human host was generated. The preferential interaction of the P. falciparum PFE1590w protein with the human ApoE ε3 and ApoE ε4 isoforms, but not the ApoE ε2 isoform, supports the hypothesis that ApoE genotype affects risk of malaria infection. The dataset contains other interactions of potential relevance to disease that may identify possible vaccine candidates and drug targets.

Specificity of molecular interactions in transient protein-protein interaction interfaces.

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Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

Hepatitis C Virus Protein Interaction Network Analysis Based on Hepatocellular Carcinoma.

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Yuewen Han

Full Text Available Epidemiological studies have validated the association between hepatitis C virus (HCV infection and hepatocellular carcinoma (HCC. An increasing number of studies show that protein-protein interactions (PPIs between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment.

Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

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Boucher Charles AB

2010-07-01

Full Text Available Abstract Background The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. Results Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. Conclusions HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

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Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Interaction of C-terminal truncated human alphaA-crystallins with target proteins.

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Anbarasu Kumarasamy

2008-09-01

Full Text Available Significant portion of alphaA-crystallin in human lenses exists as C-terminal residues cleaved at residues 172, 168, and 162. Chaperone activity, determined with alcohol dehydrogenase (ADH and betaL-crystallin as target proteins, was increased in alphaA(1-172 and decreased in alphaA(1-168 and alphaA(1-162. The purpose of this study was to show whether the absence of the C-terminal residues influences protein-protein interactions with target proteins.Our hypothesis is that the chaperone-target protein binding kinetics, otherwise termed subunit exchange rates, are expected to reflect the changes in chaperone activity. To study this, we have relied on fluorescence resonance energy transfer (FRET utilizing amine specific and cysteine specific fluorescent probes. The subunit exchange rate (k for ADH and alphaA(1-172 was nearly the same as that of ADH and alphaA-wt, alphaA(1-168 had lower and alphaA(1-162 had the lowest k values. When betaL-crystallin was used as the target protein, alphaA(1-172 had slightly higher k value than alphaA-wt and alphaA(1-168 and alphaA(1-162 had lower k values. As expected from earlier studies, the chaperone activity of alphaA(1-172 was slightly better than that of alphaA-wt, the chaperone activity of alphaA(1-168 was similar to that of alphaA-wt and alphaA(1-162 had substantially decreased chaperone activity.Cleavage of eleven C-terminal residues including Arg-163 and the C-terminal flexible arm significantly affects the interaction with target proteins. The predominantly hydrophilic flexible arm appears to be needed to keep the chaperone-target protein complex soluble.

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

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Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene

Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

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Li, Xiu-Qing; Xing, Tim; Du, Donglei

2016-01-01

Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity.

Protein disulfide isomerase interacts with tau protein and inhibits its fibrillization.

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Li-Rong Xu

Full Text Available BACKGROUND: Tau protein is implicated in the pathogenesis of neurodegenerative disorders such as tauopathies including Alzheimer disease, and Tau fibrillization is thought to be related to neuronal toxicity. Physiological inhibitors of Tau fibrillization hold promise for developing new strategies for treatment of Alzheimer disease. Because protein disulfide isomerase (PDI is both an enzyme and a chaperone, and implicated in neuroprotection against Alzheimer disease, we want to know whether PDI can prevent Tau fibrillization. In this study, we have investigated the interaction between PDI and Tau protein and the effect of PDI on Tau fibrillization. METHODOLOGY/PRINCIPAL FINDINGS: As evidenced by co-immunoprecipitation and confocal laser scanning microscopy, human PDI interacts and co-locates with some endogenous human Tau on the endoplasmic reticulum of undifferentiated SH-SY5Y neuroblastoma cells. The results from isothermal titration calorimetry show that one full-length human PDI binds to one full-length human Tau (or human Tau fragment Tau244-372 monomer with moderate, micromolar affinity at physiological pH and near physiological ionic strength. As revealed by thioflavin T binding assays, Sarkosyl-insoluble SDS-PAGE, and transmission electron microscopy, full-length human PDI remarkably inhibits both steps of nucleation and elongation of Tau244-372 fibrillization in a concentration-dependent manner. Furthermore, we find that two molecules of the a-domain of human PDI interact with one Tau244-372 molecule with sub-micromolar affinity, and inhibit both steps of nucleation and elongation of Tau244-372 fibrillization more strongly than full-length human PDI. CONCLUSIONS/SIGNIFICANCE: We demonstrate for the first time that human PDI binds to Tau protein mainly through its thioredoxin-like catalytic domain a, forming a 1∶1 complex and preventing Tau misfolding. Our findings suggest that PDI could act as a physiological inhibitor of Tau

Protein annotation from protein interaction networks and Gene Ontology.

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Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens

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Gomez Shawn M

2010-04-01

Full Text Available Abstract Background In the course of infection, viruses such as HIV-1 must enter a cell, travel to sites where they can hijack host machinery to transcribe their genes and translate their proteins, assemble, and then leave the cell again, all while evading the host immune system. Thus, successful infection depends on the pathogen's ability to manipulate the biological pathways and processes of the organism it infects. Interactions between HIV-encoded and human proteins provide one means by which HIV-1 can connect into cellular pathways to carry out these survival processes. Results We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence. Conclusions Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention.

Interactions between whey proteins and salivary proteins as related to astringency of whey protein beverages at low pH.

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Ye, A; Streicher, C; Singh, H

2011-12-01

Whey protein beverages have been shown to be astringent at low pH. In the present study, the interactions between model whey proteins (β-lactoglobulin and lactoferrin) and human saliva in the pH range from 7 to 2 were investigated using particle size, turbidity, and ζ-potential measurements and sodium dodecyl sulfate-PAGE. The correlation between the sensory results of astringency and the physicochemical data was discussed. Strong interactions between β-lactoglobulin and salivary proteins led to an increase in the particle size and turbidity of mixtures of both unheated and heated β-lactoglobulin and human saliva at pH ∼3.4. However, the large particle size and high turbidity that occurred at pH 2.0 were the result of aggregation of human salivary proteins. The intense astringency in whey protein beverages may result from these increases in particle size and turbidity at these pH values and from the aggregation and precipitation of human salivary proteins alone at pH salivary proteins in the interaction is a key factor in the perception of astringency in whey protein beverages. At any pH, the increases in particle size and turbidity were much smaller in mixtures of lactoferrin and saliva, which suggests that aggregation and precipitation may not be the only mechanism linked to the perception of astringency in whey protein. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Stapled peptides as a new technology to investigate protein-protein interactions in human platelets.

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Iegre, Jessica; Ahmed, Niaz S; Gaynord, Josephine S; Wu, Yuteng; Herlihy, Kara M; Tan, Yaw Sing; Lopes-Pires, Maria E; Jha, Rupam; Lau, Yu Heng; Sore, Hannah F; Verma, Chandra; O' Donovan, Daniel H; Pugh, Nicholas; Spring, David R

2018-05-28

Platelets are blood cells with numerous crucial pathophysiological roles in hemostasis, cardiovascular thrombotic events and cancer metastasis. Platelet activation requires the engagement of intracellular signalling pathways that involve protein-protein interactions (PPIs). A better understanding of these pathways is therefore crucial for the development of selective anti-platelet drugs. New strategies for studying PPIs in human platelets are required to overcome limitations associated with conventional platelet research methods. For example, small molecule inhibitors can lack selectivity and are often difficult to design and synthesise. Additionally, development of transgenic animal models is costly and time-consuming and conventional recombinant techniques are ineffective due to the lack of a nucleus in platelets. Herein, we describe the generation of a library of novel, functionalised stapled peptides and their first application in the investigation of platelet PPIs. Moreover, the use of platelet-permeable stapled Bim BH3 peptides confirms the part of Bim in phosphatidyl-serine (PS) exposure and reveals a role for the Bim protein in platelet activatory processes. Our work demonstrates that functionalised stapled peptides are a complementary alternative to conventional platelet research methods, and could make a significant contribution to the understanding of platelet signalling pathways and hence to the development of anti-platelet drugs.

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

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Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

Mesoporous silica particles modified with graphitic carbon: interaction with human red blood cells and plasma proteins

Energy Technology Data Exchange (ETDEWEB)

Martinez, Diego Stefani Teodoro; Franqui, Lidiane Silva; Bettini, Jefferson; Strauss, Mathias, E-mail: diego.martinez@lnnano.cnpem.br [Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Campinas, SP (Brazil); Damasceno, Joao Paulo Vita; Mazali, Italo Odone [Universidade Estadual de Campinas (UNICAMP), SP (Brazil)

2016-07-01

Full text: In this work the interaction of the mesoporous silica particles (SBA-15, ∼700 nm) modified with graphitic carbon (SBA-15/C) on human red blood cells (hemolysis) and plasma proteins (protein corona formation) is studied. XPS and CHN analysis showed that the carbon content on the SBA-15/C samples varied from 2 to 10% and was tuned by the functionalization step. The formed carbon structures where associated to graphitic nanodomains coating the pores surface as verified by Raman spectroscopy and {sup 13}C NMR. Advanced TEM/EELS analysis showed that the carbon structures are distributed along the SBA-15 mesopores. SAXS and textural analyses were used to confirm that the porous structure of the silica support is kept after the modification procedure and to calculate the number of graphitic carbon stacked layers coating the mesopores. After incubation of SBA-15 with human red blood cells (RBCs), it was observed a dose-dependent hemolytic effect, probably, due to binding of the material silanol-rich surface to the phosphatidylcholine molecules from the RBC membrane. The graphitic carbon modifications have mitigated this effect, indicating that the graphitic carbon coating protected the silanol groups of the particle surface hindering the hemolysis. Considering the protein corona formation, selective biomolecular interaction of proteins was observed for the different materials using gel electrophoresis (SDS-PAGE) analysis. Besides, graphitic carbon modification decreased the amount of proteins on the corona. Together, the in vitro hemolysis and protein corona assays are promising biological models to understand the influence of silica surface functionalization on their bionano-interactions. Finally, our work contributes to the development of fundamental research on such nanomaterials chemistry in the emerging field of nanobioscience and nanotoxicology. (author)

The crystal structure of the Dachshund domain of human SnoN reveals flexibility in the putative protein interaction surface.

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Tomas Nyman

2010-09-01

Full Text Available The human SnoN is an oncoprotein that interacts with several transcription-regulatory proteins such as the histone-deacetylase, N-CoR containing co-repressor complex and Smad proteins. This study presents the crystal structure of the Dachshund homology domain of human SnoN. The structure reveals a groove composed of conserved residues with characteristic properties of a protein-interaction surface. A comparison of the 12 monomers in the asymmetric unit reveals the presence of two major conformations: an open conformation with a well accessible groove and a tight conformation with a less accessible groove. The variability in the backbone between the open and the tight conformations matches the differences seen in previously determined structures of individual Dachshund homology domains, suggesting a general plasticity within this fold family. The flexibility observed in the putative protein binding groove may enable SnoN to recognize multiple interaction partners.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.

A Human Nuclear Shuttling Protein That Interacts with Human Immunodeficiency Virus Type 1 Matrix Is Packaged into Virions

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Gupta, Kalpana; Ott, David; Hope, Thomas J.; Siliciano, Robert F.; Boeke, Jef D.

2000-01-01

Active nuclear import of the human immunodeficiency virus type 1 (HIV-1) preintegration complex (PIC) is essential for the productive infection of nondividing cells. Nuclear import of the PIC is mediated by the HIV-1 matrix protein, which also plays several critical roles during viral entry and possibly during virion production facilitating the export of Pr55Gag and genomic RNA. Using a yeast two-hybrid screen, we identified a novel human virion-associated matrix-interacting protein (VAN) that is highly conserved in vertebrates and expressed in most human tissues. Its expression is upregulated upon activation of CD4+ T cells. VAN is efficiently incorporated into HIV-1 virions and, like matrix, shuttles between the nucleus and cytoplasm. Furthermore, overexpression of VAN significantly inhibits HIV-1 replication in tissue culture. We propose that VAN regulates matrix nuclear localization and, by extension, both nuclear import of the PIC and export of Pr55Gag and viral genomic RNA during virion production. Our data suggest that this regulatory mechanism reflects a more global process for regulation of nucleocytoplasmic transport. PMID:11090181

Viral Interactions with PDZ Domain-Containing Proteins-An Oncogenic Trait?

Science.gov (United States)

James, Claire D; Roberts, Sally

2016-01-18

Many of the human viruses with oncogenic capabilities, either in their natural host or in experimental systems (hepatitis B and C, human T cell leukaemia virus type 1, Kaposi sarcoma herpesvirus, human immunodeficiency virus, high-risk human papillomaviruses and adenovirus type 9), encode in their limited genome the ability to target cellular proteins containing PSD95/ DLG/ZO-1 (PDZ) interaction modules. In many cases (but not always), the viruses have evolved to bind the PDZ domains using the same short linear peptide motifs found in host protein-PDZ interactions, and in some cases regulate the interactions in a similar fashion by phosphorylation. What is striking is that the diverse viruses target a common subset of PDZ proteins that are intimately involved in controlling cell polarity and the structure and function of intercellular junctions, including tight junctions. Cell polarity is fundamental to the control of cell proliferation and cell survival and disruption of polarity and the signal transduction pathways involved is a key event in tumourigenesis. This review focuses on the oncogenic viruses and the role of targeting PDZ proteins in the virus life cycle and the contribution of virus-PDZ protein interactions to virus-mediated oncogenesis. We highlight how many of the viral associations with PDZ proteins lead to deregulation of PI3K/AKT signalling, benefitting virus replication but as a consequence also contributing to oncogenesis.

Human I-mfa domain proteins specifically interact with KSHV LANA and affect its regulation of Wnt signaling-dependent transcription

Energy Technology Data Exchange (ETDEWEB)

Kusano, Shuichi, E-mail: skusano@m2.kufm.kagoshima-u.ac.jp [Division of Persistent and Oncogenic Viruses, Center for Chronic Viral Diseases, Graduate School of Medical and Dental Sciences, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Eizuru, Yoshito [Division of Persistent and Oncogenic Viruses, Center for Chronic Viral Diseases, Graduate School of Medical and Dental Sciences, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan)

2010-06-04

Kaposi's sarcoma-associated herpes virus (KSHV)-encoded latency-associated nuclear antigen (LANA) protein has been reported to interact with glycogen synthase kinase 3{beta} (GSK-3{beta}) and to negatively regulate its activity, leading to stimulation of GSK-3{beta}-dependent {beta}-catenin degradation. We show here that the I-mfa domain proteins, HIC (human I-mfa domain-containing protein) and I-mfa (inhibitor of MyoD family a), interacted in vivo with LANA through their C-terminal I-mfa domains. This interaction affected the intracellular localization of HIC, inhibited the LANA-dependent transactivation of a {beta}-catenin-regulated reporter construct, and decreased the level of the LANA.GSK-3{beta} complex. These data reveal for the first time that I-mfa domain proteins interact with LANA and negatively regulate LANA-mediated activation of Wnt signaling-dependent transcription by inhibiting the formation of the LANA.GSK-3{beta} complex.

Dengue-2 Structural Proteins Associate with Human Proteins to Produce a Coagulation and Innate Immune Response Biased Interactome

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Soares Luis RB

2011-01-01

Full Text Available Abstract Background Dengue virus infection is a public health threat to hundreds of millions of individuals in the tropical regions of the globe. Although Dengue infection usually manifests itself in its mildest, though often debilitating clinical form, dengue fever, life-threatening complications commonly arise in the form of hemorrhagic shock and encephalitis. The etiological basis for the virus-induced pathology in general, and the different clinical manifestations in particular, are not well understood. We reasoned that a detailed knowledge of the global biological processes affected by virus entry into a cell might help shed new light on this long-standing problem. Methods A bacterial two-hybrid screen using DENV2 structural proteins as bait was performed, and the results were used to feed a manually curated, global dengue-human protein interaction network. Gene ontology and pathway enrichment, along with network topology and microarray meta-analysis, were used to generate hypothesis regarding dengue disease biology. Results Combining bioinformatic tools with two-hybrid technology, we screened human cDNA libraries to catalogue proteins physically interacting with the DENV2 virus structural proteins, Env, cap and PrM. We identified 31 interacting human proteins representing distinct biological processes that are closely related to the major clinical diagnostic feature of dengue infection: haemostatic imbalance. In addition, we found dengue-binding human proteins involved with additional key aspects, previously described as fundamental for virus entry into cells and the innate immune response to infection. Construction of a DENV2-human global protein interaction network revealed interesting biological properties suggested by simple network topology analysis. Conclusions Our experimental strategy revealed that dengue structural proteins interact with human protein targets involved in the maintenance of blood coagulation and innate anti

Nuclear proteins interacting with the promoter region of the human granulocyte/macrophage colony-stimulating factor gene

International Nuclear Information System (INIS)

Shannon, M.F.; Gamble, J.R.; Vadas, M.A.

1988-01-01

The gene for human granulocyte/macrophage colony-stimulating factor (GM-CSF) is expressed in a tissue-specific as well as an activation-dependent manner. The interaction of nuclear proteins with the promoter region of the GM-CSF gene that is likely to be responsible for this pattern of GM-CSF expression was investigated. The authors show that nuclear proteins interact with DNA fragments from the GM-CSF promoter in a cell-specific manner. A region spanning two cytokine-specific sequences, cytokine 1 (CK-1, 5', GAGATTCCAC 3') and cytokine 2 (CK-2, 5' TCAGGTA 3') bound two nuclear proteins from GM-CSF-expressing cells in gel retardation assays. NF-GMb was inducible with phorbol 12-myristate 13-acetate and accompanied induction of GM-CSF message. NF-GMb was absent in cell lines not producing GM-CSF, some of which had other distinct binding proteins. NF-GMa and NF-GMb eluted from a heparin-Sepharose column at 0.3 and 0.6 M KCl, respectively. They hypothesize that the sequences CK-1 and CK-2 bind specific proteins and regulate GM-CSF transcription

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Structure of the SPRY domain of the human RNA helicase DDX1, a putative interaction platform within a DEAD-box protein

Energy Technology Data Exchange (ETDEWEB)

Kellner, Julian N.; Meinhart, Anton, E-mail: anton.meinhart@mpimf-heidelberg.mpg.de [Max Planck Institute for Medical Research, Jahnstrasse 29, 69120 Heidelberg (Germany)

2015-08-25

The structure of the SPRY domain of the human RNA helicase DDX1 was determined at 2.0 Å resolution. The SPRY domain provides a putative protein–protein interaction platform within DDX1 that differs from other SPRY domains in its structure and conserved regions. The human RNA helicase DDX1 in the DEAD-box family plays an important role in RNA processing and has been associated with HIV-1 replication and tumour progression. Whereas previously described DEAD-box proteins have a structurally conserved core, DDX1 shows a unique structural feature: a large SPRY-domain insertion in its RecA-like consensus fold. SPRY domains are known to function as protein–protein interaction platforms. Here, the crystal structure of the SPRY domain of human DDX1 (hDSPRY) is reported at 2.0 Å resolution. The structure reveals two layers of concave, antiparallel β-sheets that stack onto each other and a third β-sheet beneath the β-sandwich. A comparison with SPRY-domain structures from other eukaryotic proteins showed that the general β-sandwich fold is conserved; however, differences were detected in the loop regions, which were identified in other SPRY domains to be essential for interaction with cognate partners. In contrast, in hDSPRY these loop regions are not strictly conserved across species. Interestingly, though, a conserved patch of positive surface charge is found that may replace the connecting loops as a protein–protein interaction surface. The data presented here comprise the first structural information on DDX1 and provide insights into the unique domain architecture of this DEAD-box protein. By providing the structure of a putative interaction domain of DDX1, this work will serve as a basis for further studies of the interaction network within the hetero-oligomeric complexes of DDX1 and of its recruitment to the HIV-1 Rev protein as a viral replication factor.

Macrocyclic peptide inhibitors for the protein-protein interaction of Zaire Ebola virus protein 24 and karyopherin alpha 5.

Science.gov (United States)

Song, Xiao; Lu, Lu-Yi; Passioura, Toby; Suga, Hiroaki

2017-06-21

Ebola virus infection leads to severe hemorrhagic fever in human and non-human primates with an average case fatality rate of 50%. To date, numerous potential therapies are in development, but FDA-approved drugs or vaccines are yet unavailable. Ebola viral protein 24 (VP24) is a multifunctional protein that plays critical roles in the pathogenesis of Ebola virus infection, e.g. innate immune suppression by blocking the interaction between KPNA and PY-STAT1. Here we report macrocyclic peptide inhibitors of the VP24-KPNA5 protein-protein interaction (PPI) by means of the RaPID (Random non-standard Peptides Integrated Discovery) system. These macrocyclic peptides showed remarkably high affinity to recombinant Zaire Ebola virus VP24 (eVP24), with a dissociation constant in the single digit nanomolar range, and could also successfully disrupt the eVP24-KPNA interaction. This work provides for the first time a chemical probe capable of modulating this PPI interaction and is the starting point for the development of unique anti-viral drugs against the Ebola virus.

Uncovering Viral Protein-Protein Interactions and their Role in Arenavirus Life Cycle

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Nora López

2012-09-01

Full Text Available The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.; Dimitrakopoulos, Christos M.; Likothanassis, Spiridon D.; Kleftogiannis, Dimitrios A.; Moschopoulos, Charalampos N.; Alexakos, Christos; Papadimitriou, Stergios; Mavroudi, Seferina P.

2013-01-01

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about

A Cross-Species Study of PI3K Protein-Protein Interactions Reveals the Direct Interaction of P85 and SHP2

Science.gov (United States)

Breitkopf, Susanne B.; Yang, Xuemei; Begley, Michael J.; Kulkarni, Meghana; Chiu, Yu-Hsin; Turke, Alexa B.; Lauriol, Jessica; Yuan, Min; Qi, Jie; Engelman, Jeffrey A.; Hong, Pengyu; Kontaridis, Maria I.; Cantley, Lewis C.; Perrimon, Norbert; Asara, John M.

2016-02-01

Using a series of immunoprecipitation (IP) - tandem mass spectrometry (LC-MS/MS) experiments and reciprocal BLAST, we conducted a fly-human cross-species comparison of the phosphoinositide-3-kinase (PI3K) interactome in a drosophila S2R+ cell line and several NSCLC and human multiple myeloma cell lines to identify conserved interacting proteins to PI3K, a critical signaling regulator of the AKT pathway. Using H929 human cancer cells and drosophila S2R+ cells, our data revealed an unexpected direct binding of Corkscrew, the drosophila ortholog of the non-receptor protein tyrosine phosphatase type II (SHP2) to the Pi3k21B (p60) regulatory subunit of PI3K (p50/p85 human ortholog) but no association with Pi3k92e, the human ortholog of the p110 catalytic subunit. The p85-SHP2 association was validated in human cell lines, and formed a ternary regulatory complex with GRB2-associated-binding protein 2 (GAB2). Validation experiments with knockdown of GAB2 and Far-Western blots proved the direct interaction of SHP2 with p85, independent of adaptor proteins and transfected FLAG-p85 provided evidence that SHP2 binding on p85 occurred on the SH2 domains. A disruption of the SHP2-p85 complex took place after insulin/IGF1 stimulation or imatinib treatment, suggesting that the direct SHP2-p85 interaction was both independent of AKT activation and positively regulates the ERK signaling pathway.

PDZ domain-mediated interactions of G protein-coupled receptors with postsynaptic density protein 95

DEFF Research Database (Denmark)

Møller, Thor C; Wirth, Volker F; Roberts, Nina Ingerslev

2013-01-01

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome. Their signaling is regulated by scaffold proteins containing PDZ domains, but although these interactions are important for GPCR function, they are still poorly understood. We here present...

Specificity and evolvability in eukaryotic protein interaction networks.

Directory of Open Access Journals (Sweden)

Pedro Beltrao

2007-02-01

Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

Interaction Of Calcium Phosphate Nanoparticles With Human Chorionic Gonadotropin Modifies Secondary And Tertiary Protein Structure

Directory of Open Access Journals (Sweden)

Al-Hakeim Hussein K

2015-12-01

Full Text Available Calcium phosphate nanoparticles (CaPNP have good biocompatibility and bioactivity inside human body. In this study, the interaction between CaPNP and human chorionic gonadotropin (hCG was analyzed to determine the changes in the protein structure in the presence of CaPNP and the quantity of protein adsorbed on the CaPNP surface. The results showed a significant adsorption of hCG on the CaPNP nanoparticle surface. The optimal fit was achieved using the Sips isotherm equation with a maximum adsorption capacity of 68.23 µg/mg. The thermodynamic parameters, including ∆H° and ∆G°, of the adsorption process are positive, whereas ∆S° is negative. The circular dichroism results of the adsorption of hCG on CaPNP showed the changes in its secondary structure; such changes include the decomposition of α-helix strand and the increase in β-pleated sheet and random coil percentages. Fluorescence study indicated minimal changes in the tertiary structure near the microenvironment of the aromatic amino acids such as tyrosine and phenyl alanine caused by the interaction forces between the CaPNP and hCG protein. The desorption process showed that the quantity of the hCG desorbed significantly increases as temperature increases, which indicates the weak forces between hCG and the surface.

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

Science.gov (United States)

Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions.

Science.gov (United States)

Yates, Christopher M; Sternberg, Michael J E

2013-11-01

Non-synonymous single nucleotide polymorphisms (nsSNPs) are single base changes leading to a change to the amino acid sequence of the encoded protein. Many of these variants are associated with disease, so nsSNPs have been well studied, with studies looking at the effects of nsSNPs on individual proteins, for example, on stability and enzyme active sites. In recent years, the impact of nsSNPs upon protein-protein interactions has also been investigated, giving a greater insight into the mechanisms by which nsSNPs can lead to disease. In this review, we summarize these studies, looking at the various mechanisms by which nsSNPs can affect protein-protein interactions. We focus on structural changes that can impair interaction, changes to disorder, gain of interaction, and post-translational modifications before looking at some examples of nsSNPs at human-pathogen protein-protein interfaces and the analysis of nsSNPs from a network perspective. © 2013.

A domain-based approach to predict protein-protein interactions

Directory of Open Access Journals (Sweden)

Resat Haluk

2007-06-01

Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

Directory of Open Access Journals (Sweden)

Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

Studies on the interactions of chloroquine diphosphate and phenelzine sulfate drugs with human serum albumin and human hemoglobin proteins by spectroscopic techniques

Energy Technology Data Exchange (ETDEWEB)

Tunç, Sibel, E-mail: stunc@akdeniz.edu.tr; Duman, Osman, E-mail: osmanduman@akdeniz.edu.tr; Bozoğlan, Bahar Kancı

2013-08-15

The interactions of chloroquine diphosphate (CQP) and phenelzine sulfate (PS) drugs with human serum albumin (HSA) and human hemoglobin (HMG) proteins were investigated by various spectroscopic methods. It was found that CQP caused the fluorescence quenching of protein molecules through a static quenching mechanism, but PS did not. The values of Stern–Volmer quenching constant, bimolecular quenching constant, binding constant and number of binding site on the protein molecules were calculated for HSA–CQP and HMG–CQP systems at pH 7.4 and different temperatures. For CQP, there was only one binding site on HSA and HMG proteins and the binding affinity of HSA was higher than that of HMG. The binding constants decreased with increasing temperature. The values of negative enthalpy change and positive entropy change indicated that electrostatic interactions play an important role in the binding processes. In addition, the binding processes were spontaneous and carried out by exothermic reactions. According to Förster resonance energy transfer theory, the average binding distance between proteins and CQP was calculated as 3.72 nm for HSA–CQP system and 3.45 nm for HMG–CQP system. Circular dichroism analysis displayed that the addition of CQP led to a decrease in the α-helix amount of HSA and HMG proteins. -- Highlights: • Unlike PS, CQP was bounded by HSA and HMG proteins. • The fluorescence spectra of HSA and HMG were quenched by CQP through static mechanism. • HSA–CQP and HMG–CQP complexes were stabilized by electrostatic attraction forces. • Binding constants, thermodynamic parameters and binding distances were calculated. • The binding of CQP changed the conformational structure of HSA and HMG proteins.

Development of human protein reference database as an initial platform for approaching systems biology in humans

DEFF Research Database (Denmark)

Peri, Suraj; Navarro, J Daniel; Amanchy, Ramars

2003-01-01

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships...

Our interests in protein-protein interactions

Indian Academy of Sciences (India)

protein interactions. Evolution of P-P partnerships. Evolution of P-P structures. Evolutionary dynamics of P-P interactions. Dynamics of P-P interaction network. Host-pathogen interactions. CryoEM mapping of gigantic protein assemblies.

Next-Generation Sequencing for Binary Protein-Protein Interactions

Directory of Open Access Journals (Sweden)

Bernhard eSuter

2015-12-01

Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

Evolution of protein-protein interactions

Indian Academy of Sciences (India)

Evolution of protein-protein interactions · Our interests in protein-protein interactions · Slide 3 · Slide 4 · Slide 5 · Slide 6 · Slide 7 · Slide 8 · Slide 9 · Slide 10 · Slide 11 · Slide 12 · Slide 13 · Slide 14 · Slide 15 · Slide 16 · Slide 17 · Slide 18 · Slide 19 · Slide 20.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Directory of Open Access Journals (Sweden)

Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

Science.gov (United States)

Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

Science.gov (United States)

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Non-interacting surface solvation and dynamics in protein-protein interactions

NARCIS (Netherlands)

Visscher, Koen M.; Kastritis, Panagiotis L.|info:eu-repo/dai/nl/315886668; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238

2015-01-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo

Construction of high-quality Caco-2 three-frame cDNA library and its application to yeast two-hybrid for the human astrovirus protein-protein interaction.

Science.gov (United States)

Zhao, Wei; Li, Xin; Liu, Wen-Hui; Zhao, Jian; Jin, Yi-Ming; Sui, Ting-Ting

2014-09-01

Human epithelial colorectal adenocarcinoma (Caco-2) cells are widely used as an in vitro model of the human small intestinal mucosa. Caco-2 cells are host cells of the human astrovirus (HAstV) and other enteroviruses. High quality cDNA libraries are pertinent resources and critical tools for protein-protein interaction research, but are currently unavailable for Caco-2 cells. To construct a three-open reading frame, full length-expression cDNA library from the Caco-2 cell line for application to HAstV protein-protein interaction screening, total RNA was extracted from Caco-2 cells. The switching mechanism at the 5' end of the RNA transcript technique was used for cDNA synthesis. Double-stranded cDNA was digested by Sfi I and ligated to reconstruct a pGADT7-Sfi I three-frame vector. The ligation mixture was transformed into Escherichia coli HST08 premium electro cells by electroporation to construct the primary cDNA library. The library capacity was 1.0×10(6)clones. Gel electrophoresis results indicated that the fragments ranged from 0.5kb to 4.2kb. Randomly picked clones show that the recombination rate was 100%. The three-frame primary cDNA library plasmid mixture (5×10(5)cfu) was also transformed into E. coli HST08 premium electro cells, and all clones were harvested to amplify the cDNA library. To detect the sufficiency of the cDNA library, HAstV capsid protein as bait was screened and tested against the Caco-2 cDNA library by a yeast two-hybrid (Y2H) system. A total of 20 proteins were found to interact with the capsid protein. These results showed that a high-quality three-frame cDNA library from Caco-2 cells was successfully constructed. This library was efficient for the application to the Y2H system, and could be used for future research. Copyright © 2014 Elsevier B.V. All rights reserved.

PIWI Proteins and PIWI-Interacting RNA

DEFF Research Database (Denmark)

Han, Yi Neng; Li, Yuan; Xia, Sheng Qiang

2017-01-01

tissue types as well and play important roles in transposon silencing, epigenetic regulation, gene and protein regulation, genome rearrangement, spermatogenesis and germ stem-cell maintenance. PIWI proteins were first discovered in Drosophila and they play roles in spermatogenesis, germline stem-cell......P-Element induced wimpy testis (PIWI)-interacting RNAs (piRNAs) are a type of noncoding RNAs (ncRNAs) and interact with PIWI proteins. piRNAs were primarily described in the germline, but emerging evidence revealed that piRNAs are expressed in a tissue-specific manner among multiple human somatic...... maintenance, self-renewal, retrotransposons silencing and the male germline mobility control. A growing number of studies have demonstrated that several piRNA and PIWI proteins are aberrantly expressed in various kinds of cancers and may probably serve as a novel biomarker and therapeutic target for cancer...

Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

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Susan Khor

Full Text Available 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 reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

Science.gov (United States)

Khor, Susan

2014-01-01

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 reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

A lanthipeptide library used to identify a protein-protein interaction inhibitor.

Science.gov (United States)

Yang, Xiao; Lennard, Katherine R; He, Chang; Walker, Mark C; Ball, Andrew T; Doigneaux, Cyrielle; Tavassoli, Ali; van der Donk, Wilfred A

2018-04-01

In this article we describe the production and screening of a genetically encoded library of 10 6 lanthipeptides in Escherichia coli using the substrate-tolerant lanthipeptide synthetase ProcM. This plasmid-encoded library was combined with a bacterial reverse two-hybrid system for the interaction of the HIV p6 protein with the UEV domain of the human TSG101 protein, which is a critical protein-protein interaction for HIV budding from infected cells. Using this approach, we identified an inhibitor of this interaction from the lanthipeptide library, whose activity was verified in vitro and in cell-based virus-like particle-budding assays. Given the variety of lanthipeptide backbone scaffolds that may be produced with ProcM, this method may be used for the generation of genetically encoded libraries of natural product-like lanthipeptides containing substantial structural diversity. Such libraries may be combined with any cell-based assay to identify lanthipeptides with new biological activities.

Defining the protein interaction network of human malaria parasite Plasmodium falciparum

KAUST Repository

Ramaprasad, Abhinay

2012-02-01

Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

International Nuclear Information System (INIS)

Nielsen, Anders Lade

2009-01-01

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of γ-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as β-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Anders Lade, E-mail: aln@humgen.au.dk [Department of Human Genetics, The Bartholin Building, University of Aarhus, DK-8000 Aarhus C (Denmark)

2009-10-23

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of {gamma}-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as {beta}-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

Interaction between the C-terminal region of human myelin basic protein and calmodulin: analysis of complex formation and solution structure

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Hayashi Nobuhiro

2008-02-01

Full Text Available Abstract Background The myelin sheath is a multilamellar membrane structure wrapped around the axon, enabling the saltatory conduction of nerve impulses in vertebrates. Myelin basic protein, one of the most abundant myelin-specific proteins, is an intrinsically disordered protein that has been shown to bind calmodulin. In this study, we focus on a 19-mer synthetic peptide from the predicted calmodulin-binding segment near the C-terminus of human myelin basic protein. Results The interaction of native human myelin basic protein with calmodulin was confirmed by affinity chromatography. The binding of the myelin basic protein peptide to calmodulin was tested with isothermal titration calorimetry (ITC in different temperatures, and Kd was observed to be in the low μM range, as previously observed for full-length myelin basic protein. Surface plasmon resonance showed that the peptide bound to calmodulin, and binding was accompanied by a conformational change; furthermore, gel filtration chromatography indicated a decrease in the hydrodynamic radius of calmodulin in the presence of the peptide. NMR spectroscopy was used to map the binding area to reside mainly within the hydrophobic pocket of the C-terminal lobe of calmodulin. The solution structure obtained by small-angle X-ray scattering indicates binding of the myelin basic protein peptide into the interlobal groove of calmodulin, while calmodulin remains in an extended conformation. Conclusion Taken together, our results give a detailed structural insight into the interaction of calmodulin with a C-terminal segment of a major myelin protein, the myelin basic protein. The used 19-mer peptide interacts mainly with the C-terminal lobe of calmodulin, and a conformational change accompanies binding, suggesting a novel mode of calmodulin-target protein interaction. Calmodulin does not collapse and wrap around the peptide tightly; instead, it remains in an extended conformation in the solution structure

Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

Science.gov (United States)

LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

2015-01-01

High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

In vitro evaluation of the interactions between human corneal endothelial cells and extracellular matrix proteins

International Nuclear Information System (INIS)

Choi, Jin San; Kim, Eun Young; Kim, Min Jeong; Giegengack, Matthew; Khan, Faraaz A; Soker, Shay; Khang, Gilson

2013-01-01

The corneal endothelium is the innermost cell layer of the cornea and rests on Descemet's membrane consisting of various extracellular matrix (ECM) proteins which can directly affect the cellular behaviors such as cell adhesion, proliferation, polarity, morphogenesis and function. The objective of this study was to investigate the interactions between the ECM environment and human corneal endothelial cells (HCECs), with the ultimate goal to improve cell proliferation and function in vitro. To evaluate the interaction of HCECs with ECM proteins, cells were seeded on ECM-coated tissue culture dishes, including collagen type I (COL I), collagen type IV (COL IV), fibronectin (FN), FNC coating mix (FNC) and laminin (LM). Cell adhesion and proliferation of HCECs on each substratum and expression of CEC markers were studied. The results showed that HCECs plated on the COL I, COL IV, FN and FNC-coated plates had enhanced cell adhesion initially; the number for COL I, COL IV, FN and FNC was significantly higher than the control (P < 0.05). In addition, cells grown on ECM protein-coated dishes showed more compact cellular morphology and CEC marker expression compared to cells seeded on uncoated dishes. Collectively, our results suggest that an adequate ECM protein combination can provide a long-term culture environment for HCECs for corneal endothelium transplantation. (paper)

Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

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Srinivasan Narayanaswamy

2010-06-01

Full Text Available Abstract Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

14-3-3 checkpoint regulatory proteins interact specifically with DNA repair protein human exonuclease 1 (hEXO1) via a semi-conserved motif

DEFF Research Database (Denmark)

Andersen, Sofie Dabros; Keijzers, Guido; Rampakakis, Emmanouil

2012-01-01

Human exonuclease 1 (hEXO1) acts directly in diverse DNA processing events, including replication, mismatch repair (MMR), and double strand break repair (DSBR), and it was also recently described to function as damage sensor and apoptosis inducer following DNA damage. In contrast, 14-3-3 proteins...... are specifically induced by replication inhibition leading to protein ubiquitination and degradation. We demonstrate direct and robust interaction between hEXO1 and six of the seven 14-3-3 isoforms in vitro, suggestive of a novel protein interaction network between DNA repair and cell cycle control. Binding...... and most likely a second unidentified binding motif. 14-3-3 associations do not appear to directly influence hEXO1 in vitro nuclease activity or in vitro DNA replication initiation. Moreover, specific phosphorylation variants, including hEXO1 S746A, are efficiently imported to the nucleus; to associate...

Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

Science.gov (United States)

Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

2010-07-01

The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

Bioinformatic Prediction of WSSV-Host Protein-Protein Interaction

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Zheng Sun

2014-01-01

Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

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Ching-Tai Chen

Full Text Available Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins and were tested on an independent dataset (consisting of 142 proteins. The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Science.gov (United States)

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

HCVpro: Hepatitis C virus protein interaction database

KAUST Repository

Kwofie, Samuel K.

2011-12-01

It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers. In furtherance of these goals, we have developed the hepatitis C virus protein interaction database (HCVpro) by integrating manually verified hepatitis C virus-virus and virus-human protein interactions curated from literature and databases. HCVpro is a comprehensive and integrated HCV-specific knowledgebase housing consolidated information on PPIs, functional genomics and molecular data obtained from a variety of virus databases (VirHostNet, VirusMint, HCVdb and euHCVdb), and from BIND and other relevant biology repositories. HCVpro is further populated with information on hepatocellular carcinoma (HCC) related genes that are mapped onto their encoded cellular proteins. Incorporated proteins have been mapped onto Gene Ontologies, canonical pathways, Online Mendelian Inheritance in Man (OMIM) and extensively cross-referenced to other essential annotations. The database is enriched with exhaustive reviews on structure and functions of HCV proteins, current state of drug and vaccine development and links to recommended journal articles. Users can query the database using specific protein identifiers (IDs), chromosomal locations of a gene, interaction detection methods, indexed PubMed sources as well as HCVpro, BIND and VirusMint IDs. The use of HCVpro is free and the resource can be accessed via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. © 2011 Elsevier B.V.

Innate Defense against Influenza A Virus: Activity of Human Neutrophil Defensins and Interactions of Defensins with Surfactant Protein D

DEFF Research Database (Denmark)

Hartshorn, Kevan L.; White, Mitchell R.; Tecle, Tesfaldet

2006-01-01

Surfactant protein D (SP-D) plays important roles in innate host defense against influenza A virus (IAV) infection, in part by modifying interactions with neutrophils. Human neutrophil defensins (HNPs) inhibit infectivity of enveloped viruses, including IAV. Our goal in this study...

Topology-function conservation in protein-protein interaction networks.

Science.gov (United States)

Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

2015-05-15

Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations

DEFF Research Database (Denmark)

Kirk, Isa Kristina; Weinhold, Nils; Belling, Kirstine González-Izarzugaza

2017-01-01

Gene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies......, gene and protein level alterations have fatal consequences. We used genome-wide protein-protein interaction data to identify chromosome-specific patterns of protein interactions. We found that some chromosomes encode proteins that interact infrequently with each other, chromosome 21 in particular. We...... combined the protein interaction data with transcriptome data from human brain tissue to investigate how this pattern of global interactions may affect cellular function. We identified highly connected proteins that also had coordinated gene expression. These proteins were associated with important...

Specificity and affinity quantification of protein-protein interactions.

Science.gov (United States)

Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

2013-05-01

Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

Innate Defense against Influenza A Virus: Activity of Human Neutrophil Defensins and Interactions of Defensins with Surfactant Protein D

DEFF Research Database (Denmark)

Hartshorn, Kevan L.; White, Mitchell R.; Tecle, Tesfaldet

2006-01-01

Surfactant protein D (SP-D) plays important roles in innate host defense against influenza A virus (IAV) infection, in part by modifying interactions with neutrophils. Human neutrophil defensins (HNPs) inhibit infectivity of enveloped viruses, including IAV. Our goal in this study was to characte......Surfactant protein D (SP-D) plays important roles in innate host defense against influenza A virus (IAV) infection, in part by modifying interactions with neutrophils. Human neutrophil defensins (HNPs) inhibit infectivity of enveloped viruses, including IAV. Our goal in this study...... was to characterize antiviral interactions between SP-D and HNPs. Recombinant and/or natural forms of SP-D and related collectins and HNPs were tested for antiviral activity against two different strains of IAV. HNPs 1 and 2 did not inhibit viral hemagglutination activity, but they interfered...... with the hemagglutination-inhibiting activity of SP-D. HNPs had significant viral neutralizing activity against divergent IAV strains. However, the HNPs generally had competitive effects when combined with SP-D in assays using an SP-D-sensitive IAV strain. In contrast, cooperative antiviral effects were noted in some...

Protein-Protein Interaction Network and Gene Ontology

Science.gov (United States)

Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

The Protein Interaction Network of Bacteriophage Lambda with Its Host, Escherichia coli

Science.gov (United States)

Blasche, Sonja; Wuchty, Stefan; Rajagopala, Seesandra V.

2013-01-01

Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens. PMID:24049175

Dopamine D2L receptor-interacting proteins regulate dopaminergic signaling

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Norifumi Shioda

2017-10-01

Full Text Available Dopamine receptor family proteins include seven transmembrane and trimeric GTP-binding protein-coupled receptors (GPCRs. Among them, the dopamine D2 receptor (D2R is most extensively studied. All clinically used antipsychotic drugs serve as D2R antagonists in the mesolimbic dopamine system, and their ability to block D2R signaling is positively correlated with antipsychotic efficiency. Human genetic studies also show a significant association of DRD2 polymorphisms with disorders including schizophrenia and Parkinson's disease. D2R exists as two alternatively spliced isoforms, the long isoform (D2LR and the short isoform (D2SR, which differ in a 29-amino acid (AA insert in the third cytoplasmic loop. Importantly, previous reports demonstrate functional diversity between the two isoforms in humans. In this review, we focus on binding proteins that specifically interact with the D2LR 29AA insert. We discuss how D2R activities are mediated not only by heterotrimeric G proteins but by D2LR-interacting proteins, which in part regulate diverse D2R activities. Keywords: Dopamine D2L receptor, Antipsychotic drugs, DRD2 polymorphisms, Alternatively spliced isoforms, D2LR-interacting proteins

Information assessment on predicting protein-protein interactions

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Gerstein Mark

2004-10-01

Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes

DEFF Research Database (Denmark)

Brunak, Søren; Bergholdt, R; Brorsson, C

2009-01-01

Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have...

Identification of brain-specific angiogenesis inhibitor 2 as an interaction partner of glutaminase interacting protein

International Nuclear Information System (INIS)

Zencir, Sevil; Ovee, Mohiuddin; Dobson, Melanie J.; Banerjee, Monimoy; Topcu, Zeki; Mohanty, Smita

2011-01-01

Highlights: → Brain-specific angiogenesis inhibitor 2 (BAI2) is a new partner protein for GIP. → BAI2 interaction with GIP was revealed by yeast two-hybrid assay. → Binding of BAI2 to GIP was characterized by NMR, CD and fluorescence. → BAI2 and GIP binding was mediated through the C-terminus of BAI2. -- Abstract: The vast majority of physiological processes in living cells are mediated by protein-protein interactions often specified by particular protein sequence motifs. PDZ domains, composed of 80-100 amino acid residues, are an important class of interaction motif. Among the PDZ-containing proteins, glutaminase interacting protein (GIP), also known as Tax Interacting Protein TIP-1, is unique in being composed almost exclusively of a single PDZ domain. GIP has important roles in cellular signaling, protein scaffolding and modulation of tumor growth and interacts with a number of physiological partner proteins, including Glutaminase L, β-Catenin, FAS, HTLV-1 Tax, HPV16 E6, Rhotekin and Kir 2.3. To identify the network of proteins that interact with GIP, a human fetal brain cDNA library was screened using a yeast two-hybrid assay with GIP as bait. We identified brain-specific angiogenesis inhibitor 2 (BAI2), a member of the adhesion-G protein-coupled receptors (GPCRs), as a new partner of GIP. BAI2 is expressed primarily in neurons, further expanding GIP cellular functions. The interaction between GIP and the carboxy-terminus of BAI2 was characterized using fluorescence, circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy assays. These biophysical analyses support the interaction identified in the yeast two-hybrid assay. This is the first study reporting BAI2 as an interaction partner of GIP.

Detecting protein complexes based on a combination of topological and biological properties in protein-protein interaction network

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Pooja Sharma

2018-06-01

Full Text Available Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexes from raw protein protein interactions (PPIs is an important area of research. Earlier work has been limited mostly to yeast. Such protein complex identification methods, when applied to large human PPIs often give poor performance. We introduce a novel method called CSC to detect protein complexes. The method is evaluated in terms of positive predictive value, sensitivity and accuracy using the datasets of the model organism, yeast and humans. CSC outperforms several other competing algorithms for both organisms. Further, we present a framework to establish the usefulness of CSC in analyzing the influence of a given disease gene in a complex topologically as well as biologically considering eight major association factors. Keywords: Protein complex, Connectivity, Semantic similarity, Contribution

Study of human salivary proline-rich proteins interaction with food tannins.

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Soares, Susana; García-Estévez, Ignacio; Ferrer-Galego, Raúl; Brás, Natércia F; Brandão, Elsa; Silva, Mafalda; Teixeira, Natércia; Fonseca, Fátima; Sousa, Sérgio F; Ferreira-da-Silva, Frederico; Mateus, Nuno; de Freitas, Victor

2018-03-15

In this work, saturation transfer difference-NMR, isothermal microcalorimetry and molecular dynamics simulations have been used to study the individual interactions between basic, glycosylated and acidic proline-rich proteins (bPRPS, gPRPs, aPRPs) and P-B peptide with some representative food tannins [procyanidin B2, procyanidin B2 3'-O-gallate (B2g) and procyanidin trimer (catechin-4-8-catechin-4-8-catechin)]. Results showed that P-B peptide was in general the salivary protein (SP) with higher affinity whereas aPRPs showed lower affinity to the studied procyanidins. Moreover, B2g was the procyanidin with higher affinity for all SP. Hydrophobic and hydrogen bonds were present in all interactions but the major driving force depended on the procyanidin-SP pair. Furthermore, proline clusters or residues in their vicinity were identified as the probable sites of proteins for interaction with procyanidins. For bPRP and aPRP a significant change to less extended conformations was observed, while P-B peptide did not display any structural rearrangement upon procyanidins binding. Copyright © 2017. Published by Elsevier Ltd.

Understanding Protein-Protein Interactions Using Local Structural Features

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Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

From Human-Computer Interaction to Human-Robot Social Interaction

OpenAIRE

Toumi, Tarek; Zidani, Abdelmadjid

2014-01-01

Human-Robot Social Interaction became one of active research fields in which researchers from different areas propose solutions and directives leading robots to improve their interactions with humans. In this paper we propose to introduce works in both human robot interaction and human computer interaction and to make a bridge between them, i.e. to integrate emotions and capabilities concepts of the robot in human computer model to become adequate for human robot interaction and discuss chall...

Evolutionary reprograming of protein-protein interaction specificity.

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Akiva, Eyal; Babbitt, Patricia C

2015-10-22

Using mutation libraries and deep sequencing, Aakre et al. study the evolution of protein-protein interactions using a toxin-antitoxin model. The results indicate probable trajectories via "intermediate" proteins that are promiscuous, thus avoiding transitions via non-interactions. These results extend observations about other biological interactions and enzyme evolution, suggesting broadly general principles. Copyright © 2015 Elsevier Inc. All rights reserved.

Interaction of Protein Phosphatase 1δ with Nucleophosmin in Human Osteoblastic Cells

International Nuclear Information System (INIS)

Haneji, Tatsuji; Teramachi, Jumpei; Hirashima, Kanji; Kimura, Koji; Morimoto, Hiroyuki

2012-01-01

Protein phosphorylation and dephosphorylation has been recognized as an essential mechanism in the regulation of cellular metabolism and function in various tissues. Serine and threonine protein phosphatases (PP) are divided into four categories: PP1, PP2A, PP2B, and PP2C. At least four isoforms of PP1 catalytic subunit in rat, PP1α, PP1γ1, PP1γ2, and PP1δ, were isolated. In the present study, we examined the localization and expression of PP1δ in human osteoblastic Saos-2 cells. Anti-PP1δ antibody recognized a protein present in the nucleolar regions in Saos-2 cells. Cellular fractionation revealed that PP1δ is a 37 kDa protein localized in the nucleolus. Nucleophosmin is a nucleolar phosphoprotein and located mainly in the nucleolus. Staining pattern of nucleophosmin in Saos-2 cells was similar to that of PP1δ. PP1δ and nucleophosmin were specifically stained as dots in the nucleus. Dual fluorescence images revealed that PP1δ and nucleophosmin were localized in the same regions in the nucleolus. Similar distribution patterns of PP1δ and nucleophosmin were observed in osteoblastic MG63 cells. The interaction of PP1δ and nucleophosmin was also shown by immunoprecipitation and Western analysis. These results indicated that PP1δ associate with nucleophosmin directly in the nucleolus and suggested that nucleophosmin is one of the candidate substrate for PP1δ

Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.

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Yim, Soorin; Yu, Hasun; Jang, Dongjin; Lee, Doheon

2018-04-11

Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of 'directions' (i.e. upstream/downstream) and 'signs' (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins. We used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research. We annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

Galectin-1 Is an Interactive Protein of Selenoprotein M in the Brain

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Qiong Liu

2013-11-01

Full Text Available Selenium, an essential trace element for human health, mainly exerts its biological function through selenoproteins. Selenoprotein M (SelM is one of the highly expressed selenoproteins in the brain, but its biological effect and molecular mechanism remain unclear. Thus, the interactive protein of SelM was investigated in this paper to guide further study. In order to avoid protein translational stop, the selenocysteine-encoding UGA inside the open reading frame of SelM was site-directly changed to the cysteine-encoding UGC to generate the SelM' mutant. Meanwhile, its N terminal transmembrane signal peptide was also cut off. This truncated SelM' was used to screen a human fetal brain cDNA library by the yeast two-hybrid system. A new interactive protein of SelM' was found to be galectin-1 (Gal-1. This protein-protein interaction was further verified by the results of fluorescence resonance energy transfer techniques, glutathione S-transferase pull-down and co-immunoprecipitation assays. As Gal-1 plays important roles in preventing neurodegeneration and promoting neuroprotection in the brain, the interaction between SelM' and Gal-1 displays a new direction for studying the biological function of SelM in the human brain.

Mapping Protein-Protein Interactions by Quantitative Proteomics

DEFF Research Database (Denmark)

Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

2010-01-01

spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...... to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions.......Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...

Protein- protein interaction detection system using fluorescent protein microdomains

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Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

Functional interaction between type III-secreted protein IncA of Chlamydophila psittaci and human G3BP1.

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Borth, Nicole; Litsche, Katrin; Franke, Claudia; Sachse, Konrad; Saluz, Hans Peter; Hänel, Frank

2011-01-31

Chlamydophila (Cp.) psittaci, the causative agent of psittacosis in birds and humans, is the most important zoonotic pathogen of the family Chlamydiaceae. These obligate intracellular bacteria are distinguished by a unique biphasic developmental cycle, which includes proliferation in a membrane-bound compartment termed inclusion. All Chlamydiaceae spp. possess a coding capacity for core components of a Type III secretion apparatus, which mediates specific delivery of anti-host effector proteins either into the chlamydial inclusion membrane or into the cytoplasm of target eukaryotic cells. Here we describe the interaction between Type III-secreted protein IncA of Cp. psittaci and host protein G3BP1 in a yeast two-hybrid system. In GST-pull down and co-immunoprecipitation experiments both in vitro and in vivo interaction between full-length IncA and G3BP1 were shown. Using fluorescence microscopy, the localization of G3BP1 near the inclusion membrane of Cp. psittaci-infected Hep-2 cells was demonstrated. Notably, infection of Hep-2 cells with Cp. psittaci and overexpression of IncA in HEK293 cells led to a decrease in c-Myc protein concentration. This effect could be ascribed to the interaction between IncA and G3BP1 since overexpression of an IncA mutant construct disabled to interact with G3BP1 failed to reduce c-Myc concentration. We hypothesize that lowering the host cell c-Myc protein concentration may be part of a strategy employed by Cp. psittaci to avoid apoptosis and scale down host cell proliferation.

Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions

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Furuya Toshio

2011-02-01

Full Text Available Abstract Background The amount of data on protein-protein interactions (PPIs available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine. Results To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS. Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM. Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV proteins identified to date. Conclusions The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data.

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

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Prashanthi Karyala

2016-09-01

Full Text Available Dengue virus (DENV is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/.

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

Science.gov (United States)

Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma

2016-09-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).

Oligomeric protein structure networks: insights into protein-protein interactions

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Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

Science.gov (United States)

Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Interactions of polyphenols with carbohydrates, lipids and proteins.

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Jakobek, Lidija

2015-05-15

Polyphenols are secondary metabolites in plants, investigated intensively because of their potential positive effects on human health. Their bioavailability and mechanism of positive effects have been studied, in vitro and in vivo. Lately, a high number of studies takes into account the interactions of polyphenols with compounds present in foods, like carbohydrates, proteins or lipids, because these food constituents can have significant effects on the activity of phenolic compounds. This paper reviews the interactions between phenolic compounds and lipids, carbohydrates and proteins and their impact on polyphenol activity. Copyright © 2014 Elsevier Ltd. All rights reserved.

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

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Greenblatt Jack

2006-07-01

Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

Structure homology and interaction redundancy for discovering virus–host protein interactions

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-01-01

Virus–host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication. PMID:24008843

Structure homology and interaction redundancy for discovering virus-host protein interactions.

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-10-01

Virus-host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication.

An ontology-based search engine for protein-protein interactions.

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Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

Human-specific protein isoforms produced by novel splice sites in the human genome after the human-chimpanzee divergence

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Kim Dong Seon

2012-11-01

Full Text Available Abstract Background Evolution of splice sites is a well-known phenomenon that results in transcript diversity during human evolution. Many novel splice sites are derived from repetitive elements and may not contribute to protein products. Here, we analyzed annotated human protein-coding exons and identified human-specific splice sites that arose after the human-chimpanzee divergence. Results We analyzed multiple alignments of the annotated human protein-coding exons and their respective orthologous mammalian genome sequences to identify 85 novel splice sites (50 splice acceptors and 35 donors in the human genome. The novel protein-coding exons, which are expressed either constitutively or alternatively, produce novel protein isoforms by insertion, deletion, or frameshift. We found three cases in which the human-specific isoform conferred novel molecular function in the human cells: the human-specific IMUP protein isoform induces apoptosis of the trophoblast and is implicated in pre-eclampsia; the intronization of a part of SMOX gene exon produces inactive spermine oxidase; the human-specific NUB1 isoform shows reduced interaction with ubiquitin-like proteins, possibly affecting ubiquitin pathways. Conclusions Although the generation of novel protein isoforms does not equate to adaptive evolution, we propose that these cases are useful candidates for a molecular functional study to identify proteomic changes that might bring about novel phenotypes during human evolution.

Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

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Wan Li

Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

Can infrared spectroscopy provide information on protein-protein interactions?

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Haris, Parvez I

2010-08-01

For most biophysical techniques, characterization of protein-protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600-1700 cm(-1)) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with (13)C or (13)C,(15)N has been introduced as a solution to this problem, enabling the study of protein-protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm(-1) towards lower frequency) upon (13)C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein-protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein-protein interactions are provided.

In silico modeling of human α2C-adrenoreceptor interaction with filamin-2.

Directory of Open Access Journals (Sweden)

Marcin Pawlowski

Full Text Available Vascular smooth muscle α2C-adrenoceptors (α2C-ARs mediate vasoconstriction of small blood vessels, especially arterioles. Studies of endogenous receptors in human arteriolar smooth muscle cells (referred to as microVSM and transiently transfected receptors in heterologous HEK293 cells show that the α2C-ARs are perinuclear receptors that translocate to the cell surface under cellular stress and elicit a biological response. Recent studies in microVSM unraveled a crucial role of Rap1A-Rho-ROCK-F-actin pathways in receptor translocation, and identified protein-protein interaction of α2C-ARs with the actin binding protein filamin-2 as an essential step in the process. To better understand the molecular nature and specificity of this interaction, in this study, we constructed comparative models of human α2C-AR and human filamin-2 proteins. Finally, we performed in silico protein-protein docking to provide a structural platform for the investigation of human α2C-AR and filamin-2 interactions. We found that electrostatic interactions seem to play a key role in this complex formation which manifests in interactions between the C-terminal arginines of α2C-ARs (particularly R454 and R456 and negatively charged residues from filamin-2 region between residues 1979 and 2206. Phylogenetic and sequence analysis showed that these interactions have evolved in warm-blooded animals.

Alignment of non-covalent interactions at protein-protein interfaces.

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Hongbo Zhu

Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.

Biospecific protein immobilization for rapid analysis of weak protein interactions using self-interaction nanoparticle spectroscopy.

Science.gov (United States)

Bengali, Aditya N; Tessier, Peter M

2009-10-01

"Reversible" protein interactions govern diverse biological behavior ranging from intracellular transport and toxic protein aggregation to protein crystallization and inactivation of protein therapeutics. Much less is known about weak protein interactions than their stronger counterparts since they are difficult to characterize, especially in a parallel format (in contrast to a sequential format) necessary for high-throughput screening. We have recently introduced a highly efficient approach of characterizing protein self-association, namely self-interaction nanoparticle spectroscopy (SINS; Tessier et al., 2008; J Am Chem Soc 130:3106-3112). This approach exploits the separation-dependent optical properties of gold nanoparticles to detect weak self-interactions between proteins immobilized on nanoparticles. A limitation of our previous work is that differences in the sequence and structure of proteins can lead to significant differences in their affinity to adsorb to nanoparticle surfaces, which complicates analysis of the corresponding protein self-association behavior. In this work we demonstrate a highly specific approach for coating nanoparticles with proteins using biotin-avidin interactions to generate protein-nanoparticle conjugates that report protein self-interactions through changes in their optical properties. Using lysozyme as a model protein that is refractory to characterization by conventional SINS, we demonstrate that surface Plasmon wavelengths for gold-avidin-lysozyme conjugates over a range of solution conditions (i.e., pH and ionic strength) are well correlated with lysozyme osmotic second virial coefficient measurements. Since SINS requires orders of magnitude less protein and time than conventional methods (e.g., static light scattering), we envision this approach will find application in large screens of protein self-association aimed at either preventing (e.g., protein aggregation) or promoting (e.g., protein crystallization) these

Selection of peptides interfering with protein-protein interaction.

Science.gov (United States)

Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

2009-01-01

Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

Yeast Interacting Proteins Database: YLR447C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp...; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act

Gene expression analysis uncovers novel Hedgehog interacting protein (HHIP) effects in human bronchial epithelial cells

Science.gov (United States)

Zhou, Xiaobo; Qiu, Weiliang; Sathirapongsasuti, J. Fah.; Cho, Michael H.; Mancini, John D.; Lao, Taotao; Thibault, Derek M.; Litonjua, Gus; Bakke, Per S.; Gulsvik, Amund; Lomas, David A.; Beaty, Terri H.; Hersh, Craig P.; Anderson, Christopher; Geigenmuller, Ute; Raby, Benjamin A.; Rennard, Stephen I.; Perrella, Mark A.; Choi, Augustine M.K.; Quackenbush, John; Silverman, Edwin K.

2013-01-01

Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis. PMID:23459001

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

Science.gov (United States)

Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

The colloidal state of tannins impacts the nature of their interaction with proteins: the case of salivary proline-rich protein/procyanidins binding.

Science.gov (United States)

Cala, Olivier; Dufourc, Erick J; Fouquet, Eric; Manigand, Claude; Laguerre, Michel; Pianet, Isabelle

2012-12-18

While the definition of tannins has been historically associated with its propensity to bind proteins in a nonspecific way, it is now admitted that specific interaction also occurs. The case of the astringency perception is a good example to illustrate this phenomenon: astringency is commonly described as a tactile sensation induced by the precipitation of a complex composed of proline-rich proteins present in the human saliva and tannins present in beverages such as tea or red wines. In the present work, the interactions between a human saliva protein segment and three different procyanidins (B1, B3, and C2) were investigated at the atomic level by NMR and molecular dynamics. The data provided evidence for (i) an increase in affinity compared to shortest human saliva peptides, which is accounted for by protein "wraping around" the tannin, (ii) a specificity in the interaction below tannin critical micelle concentration (CMC) of ca. 10 mM, with an affinity scale such that C2 > B1 > B3, and (iii) a nonspecific binding above tannin CMC that conducts irremediably to the precipitation of the tannins/protein complex. Such physicochemical findings describe in accurate terms saliva protein-tannin interactions and provide support for a more subtle description by oenologists of wine astringency perception in the mouth.

Novel fusion protein approach for efficient high-throughput screening of small molecule-mediating protein-protein interactions in cells and living animals.

Science.gov (United States)

Paulmurugan, Ramasamy; Gambhir, Sanjiv S

2005-08-15

Networks of protein interactions execute many different intracellular pathways. Small molecules either synthesized within the cell or obtained from the external environment mediate many of these protein-protein interactions. The study of these small molecule-mediated protein-protein interactions is important in understanding abnormal signal transduction pathways in a variety of disorders, as well as in optimizing the process of drug development and validation. In this study, we evaluated the rapamycin-mediated interaction of the human proteins FK506-binding protein (FKBP12) rapamycin-binding domain (FRB) and FKBP12 by constructing a fusion of these proteins with a split-Renilla luciferase or a split enhanced green fluorescent protein (split-EGFP) such that complementation of the reporter fragments occurs in the presence of rapamycin. Different linker peptides in the fusion protein were evaluated for the efficient maintenance of complemented reporter activity. This system was studied in both cell culture and xenografts in living animals. We found that peptide linkers with two or four EAAAR repeat showed higher protein-protein interaction-mediated signal with lower background signal compared with having no linker or linkers with amino acid sequences GGGGSGGGGS, ACGSLSCGSF, and ACGSLSCGSFACGSLSCGSF. A 9 +/- 2-fold increase in signal intensity both in cell culture and in living mice was seen compared with a system that expresses both reporter fragments and the interacting proteins separately. In this fusion system, rapamycin induced heterodimerization of the FRB and FKBP12 moieties occurred rapidly even at very lower concentrations (0.00001 nmol/L) of rapamycin. For a similar fusion system employing split-EGFP, flow cytometry analysis showed significant level of rapamycin-induced complementation.

Interactive protein manipulation

International Nuclear Information System (INIS)

2003-01-01

We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

Directory of Open Access Journals (Sweden)

Baskin Berivan

2003-03-01

Full Text Available Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. Results Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. Conclusions Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

Science.gov (United States)

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

Directory of Open Access Journals (Sweden)

Vincent Vagenende

Full Text Available Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Yeast Interacting Proteins Database: YGR013W, YKL012W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tion U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the formation of the second commitm... PRP40 U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the form...ation of the second commitment complex Rows with this prey as prey (1) Rows with

Molecular tweezers modulate 14-3-3 protein-protein interactions

Science.gov (United States)

Bier, David; Rose, Rolf; Bravo-Rodriguez, Kenny; Bartel, Maria; Ramirez-Anguita, Juan Manuel; Dutt, Som; Wilch, Constanze; Klärner, Frank-Gerrit; Sanchez-Garcia, Elsa; Schrader, Thomas; Ottmann, Christian

2013-03-01

Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins—a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)—in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions.

Comparative interactomics: analysis of arabidopsis 14-3-3 complexes reveals highly conserved 14-3-3 interactions between humans and plants.

Science.gov (United States)

Paul, Anna-Lisa; Liu, Li; McClung, Scott; Laughner, Beth; Chen, Sixue; Ferl, Robert J

2009-04-01

As a first step in the broad characterization of plant 14-3-3 multiprotein complexes in vivo, stringent and specific antibody affinity purification was used to capture 14-3-3s together with their interacting proteins from extracts of Arabidopsis cell suspension cultures. Approximately 120 proteins were identified as potential in vivo 14-3-3 interacting proteins by mass spectrometry of the recovered complexes. Comparison of the proteins in this data set with the 14-3-3 interacting proteins from a similar study in human embryonic kidney cell cultures revealed eight interacting proteins that likely represent reasonably abundant, fundamental 14-3-3 interaction complexes that are highly conserved across all eukaryotes. The Arabidopsis 14-3-3 interaction data set was also compared to a yeast in vivo 14-3-3 interaction data set. Four 14-3-3 interacting proteins are conserved in yeast, humans, and Arabidopsis. Comparisons of the data sets based on biochemical function revealed many additional similarities in the human and Arabidopsis data sets that represent conserved functional interactions, while also leaving many proteins uniquely identified in either Arabidopsis or human cells. In particular, the Arabidopsis interaction data set is enriched for proteins involved in metabolism.

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are

Solution structure of the human signaling protein RACK1

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Papa Priscila F

2010-06-01

Full Text Available Abstract Background The adaptor protein RACK1 (receptor of activated kinase 1 was originally identified as an anchoring protein for protein kinase C. RACK1 is a 36 kDa protein, and is composed of seven WD repeats which mediate its protein-protein interactions. RACK1 is ubiquitously expressed and has been implicated in diverse cellular processes involving: protein translation regulation, neuropathological processes, cellular stress, and tissue development. Results In this study we performed a biophysical analysis of human RACK1 with the aim of obtaining low resolution structural information. Small angle X-ray scattering (SAXS experiments demonstrated that human RACK1 is globular and monomeric in solution and its low resolution structure is strikingly similar to that of an homology model previously calculated by us and to the crystallographic structure of RACK1 isoform A from Arabidopsis thaliana. Both sedimentation velocity and sedimentation equilibrium analytical ultracentrifugation techniques showed that RACK1 is predominantly a monomer of around 37 kDa in solution, but also presents small amounts of oligomeric species. Moreover, hydrodynamic data suggested that RACK1 has a slightly asymmetric shape. The interaction of RACK1 and Ki-1/57 was tested by sedimentation equilibrium. The results suggested that the association between RACK1 and Ki-1/57(122-413 follows a stoichiometry of 1:1. The binding constant (KB observed for RACK1-Ki-1/57(122-413 interaction was of around (1.5 ± 0.2 × 106 M-1 and resulted in a dissociation constant (KD of (0.7 ± 0.1 × 10-6 M. Moreover, the fluorescence data also suggests that the interaction may occur in a cooperative fashion. Conclusion Our SAXS and analytical ultracentrifugation experiments indicated that RACK1 is predominantly a monomer in solution. RACK1 and Ki-1/57(122-413 interact strongly under the tested conditions.

Interactive protein manipulation

Energy Technology Data Exchange (ETDEWEB)

SNCrivelli@lbl.gov

2003-07-01

We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures.

[Detection of protein-protein interactions by FRET and BRET methods].

Science.gov (United States)

Matoulková, E; Vojtěšek, B

2014-01-01

Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

Yeast Interacting Proteins Database: YGL237C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote... expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein

Yeast Interacting Proteins Database: YKL002W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote...xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

Directory of Open Access Journals (Sweden)

Sandip Chakraborty

2016-01-01

Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

International Nuclear Information System (INIS)

Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

2011-01-01

The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations

Tetratricopeptide-motif-mediated interaction of FANCG with recombination proteins XRCC3 and BRCA2.

Science.gov (United States)

Hussain, Shobbir; Wilson, James B; Blom, Eric; Thompson, Larry H; Sung, Patrick; Gordon, Susan M; Kupfer, Gary M; Joenje, Hans; Mathew, Christopher G; Jones, Nigel J

2006-05-10

Fanconi anaemia is an inherited chromosomal instability disorder characterised by cellular sensitivity to DNA interstrand crosslinkers, bone-marrow failure and a high risk of cancer. Eleven FA genes have been identified, one of which, FANCD1, is the breast cancer susceptibility gene BRCA2. At least eight FA proteins form a nuclear core complex required for monoubiquitination of FANCD2. The BRCA2/FANCD1 protein is connected to the FA pathway by interactions with the FANCG and FANCD2 proteins, both of which co-localise with the RAD51 recombinase, which is regulated by BRCA2. These connections raise the question of whether any of the FANC proteins of the core complex might also participate in other complexes involved in homologous recombination repair. We therefore tested known FA proteins for direct interaction with RAD51 and its paralogs XRCC2 and XRCC3. FANCG was found to interact with XRCC3, and this interaction was disrupted by the FA-G patient derived mutation L71P. FANCG was co-immunoprecipitated with both XRCC3 and BRCA2 from extracts of human and hamster cells. The FANCG-XRCC3 and FANCG-BRCA2 interactions did not require the presence of other FA proteins from the core complex, suggesting that FANCG also participates in a DNA repair complex that is downstream and independent of FANCD2 monoubiquitination. Additionally, XRCC3 and BRCA2 proteins co-precipitate in both human and hamster cells and this interaction requires FANCG. The FANCG protein contains multiple tetratricopeptide repeat motifs (TPRs), which function as scaffolds to mediate protein-protein interactions. Mutation of one or more of these motifs disrupted all of the known interactions of FANCG. We propose that FANCG, in addition to stabilising the FA core complex, may have a role in building multiprotein complexes that facilitate homologous recombination repair.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

Science.gov (United States)

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics.

Science.gov (United States)

Yachie, Nozomu; Petsalaki, Evangelia; Mellor, Joseph C; Weile, Jochen; Jacob, Yves; Verby, Marta; Ozturk, Sedide B; Li, Siyang; Cote, Atina G; Mosca, Roberto; Knapp, Jennifer J; Ko, Minjeong; Yu, Analyn; Gebbia, Marinella; Sahni, Nidhi; Yi, Song; Tyagi, Tanya; Sheykhkarimli, Dayag; Roth, Jonathan F; Wong, Cassandra; Musa, Louai; Snider, Jamie; Liu, Yi-Chun; Yu, Haiyuan; Braun, Pascal; Stagljar, Igor; Hao, Tong; Calderwood, Michael A; Pelletier, Laurence; Aloy, Patrick; Hill, David E; Vidal, Marc; Roth, Frederick P

2016-04-22

High-throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome-scale interaction mapping. Here, we report Barcode Fusion Genetics-Yeast Two-Hybrid (BFG-Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG-Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein-pair barcodes that can be quantified via next-generation sequencing. We applied BFG-Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG-Y2H increases the efficiency of protein matrix screening, with quality that is on par with state-of-the-art Y2H methods. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Mass spectrometric analysis of protein interactions

DEFF Research Database (Denmark)

Borch, Jonas; Jørgensen, Thomas J. D.; Roepstorff, Peter

2005-01-01

Mass spectrometry is a powerful tool for identification of interaction partners and structural characterization of protein interactions because of its high sensitivity, mass accuracy and tolerance towards sample heterogeneity. Several tools that allow studies of protein interaction are now...... available and recent developments that increase the confidence of studies of protein interaction by mass spectrometry include quantification of affinity-purified proteins by stable isotope labeling and reagents for surface topology studies that can be identified by mass-contributing reporters (e.g. isotope...... labels, cleavable cross-linkers or fragment ions. The use of mass spectrometers to study protein interactions using deuterium exchange and for analysis of intact protein complexes recently has progressed considerably....

Prediction of interactions between viral and host proteins using supervised machine learning methods.

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Ranjan Kumar Barman

Full Text Available BACKGROUND: Viral-host protein-protein interaction plays a vital role in pathogenesis, since it defines viral infection of the host and regulation of the host proteins. Identification of key viral-host protein-protein interactions (PPIs has great implication for therapeutics. METHODS: In this study, a systematic attempt has been made to predict viral-host PPIs by integrating different features, including domain-domain association, network topology and sequence information using viral-host PPIs from VirusMINT. The three well-known supervised machine learning methods, such as SVM, Naïve Bayes and Random Forest, which are commonly used in the prediction of PPIs, were employed to evaluate the performance measure based on five-fold cross validation techniques. RESULTS: Out of 44 descriptors, best features were found to be domain-domain association and methionine, serine and valine amino acid composition of viral proteins. In this study, SVM-based method achieved better sensitivity of 67% over Naïve Bayes (37.49% and Random Forest (55.66%. However the specificity of Naïve Bayes was the highest (99.52% as compared with SVM (74% and Random Forest (89.08%. Overall, the SVM and Random Forest achieved accuracy of 71% and 72.41%, respectively. The proposed SVM-based method was evaluated on blind dataset and attained a sensitivity of 64%, specificity of 83%, and accuracy of 74%. In addition, unknown potential targets of hepatitis B virus-human and hepatitis E virus-human PPIs have been predicted through proposed SVM model and validated by gene ontology enrichment analysis. Our proposed model shows that, hepatitis B virus "C protein" binds to membrane docking protein, while "X protein" and "P protein" interacts with cell-killing and metabolic process proteins, respectively. CONCLUSION: The proposed method can predict large scale interspecies viral-human PPIs. The nature and function of unknown viral proteins (HBV and HEV, interacting partners of host

Evolutionary diversification of protein-protein interactions by interface add-ons.

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Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

2017-10-03

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Engineering bacterial surface displayed human norovirus capsid proteins: A novel system to explore interaction between norovirus and ligands

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Mengya eNiu

2015-12-01

Full Text Available Human noroviruses (HuNoVs are major contributors to acute nonbacterial gastroenteritis outbreaks. Many aspects of HuNoVs are poorly understood due to both the current inability to culture HuNoVs, and the lack of efficient small animal models. Surrogates for HuNoVs, such as recombinant viral like particles (VLPs expressed in eukaryotic system or P particles expressed in prokaryotic system, have been used for studies in immunology and interaction between the virus and its receptors. However, it is difficult to use VLPs or P particles to collect or isolate potential ligands binding to these recombinant capsid proteins. In this study, a new strategy was used to collect HuNoVs binding ligands through the use of ice nucleation protein (INP to display recombinant capsid proteins of HuNoVs on bacterial surfaces. The viral protein-ligand complex could be easily separated by a low speed centrifugation step. This system was also used to explore interaction between recombinant capsid proteins of HuNoVs and their receptors. In this system, the VP1 capsid encoding gene (ORF2 and the protruding domain (P domain encoding gene (3’ terminal fragment of ORF2 of HuNoVs GI.1 and GII.4 were fused with 5’ terminal fragment of ice nucleation protein encoding gene (inaQn. The results demonstrated that the recombinant VP1 and P domains of HuNoVs were expressed and anchored on the surface of Escherichia coli BL21 cells after the bacteria were transformed with the corresponding plasmids. Both cell surface displayed VP1 and P domains could be recognized by HuNoVs specific antibodies and interact with the viral histo-blood group antigens receptors. In both cases, displayed P domains had better binding abilities than VP1. This new strategy of using displayed HuNoVs capsid proteins on the bacterial surface could be utilized to separate HuNoVs binding components from complex samples, to investigate interaction between the virus and its receptors, as well as to develop an

ProNormz--an integrated approach for human proteins and protein kinases normalization.

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Subramani, Suresh; Raja, Kalpana; Natarajan, Jeyakumar

2014-02-01

The task of recognizing and normalizing protein name mentions in biomedical literature is a challenging task and important for text mining applications such as protein-protein interactions, pathway reconstruction and many more. In this paper, we present ProNormz, an integrated approach for human proteins (HPs) tagging and normalization. In Homo sapiens, a greater number of biological processes are regulated by a large human gene family called protein kinases by post translational phosphorylation. Recognition and normalization of human protein kinases (HPKs) is considered to be important for the extraction of the underlying information on its regulatory mechanism from biomedical literature. ProNormz distinguishes HPKs from other HPs besides tagging and normalization. To our knowledge, ProNormz is the first normalization system available to distinguish HPKs from other HPs in addition to gene normalization task. ProNormz incorporates a specialized synonyms dictionary for human proteins and protein kinases, a set of 15 string matching rules and a disambiguation module to achieve the normalization. Experimental results on benchmark BioCreative II training and test datasets show that our integrated approach achieve a fairly good performance and outperforms more sophisticated semantic similarity and disambiguation systems presented in BioCreative II GN task. As a freely available web tool, ProNormz is useful to developers as extensible gene normalization implementation, to researchers as a standard for comparing their innovative techniques, and to biologists for normalization and categorization of HPs and HPKs mentions in biomedical literature. URL: http://www.biominingbu.org/pronormz. Copyright © 2013 Elsevier Inc. All rights reserved.

Protein-Glycan Quinary Interactions in Crowding Environment Unveiled by NMR Spectroscopy.

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Diniz, Ana; Dias, Jorge S; Jiménez-Barbero, Jesús; Marcelo, Filipa; Cabrita, Eurico J

2017-09-21

Protein-glycan interactions as modulators for quinary structures in crowding environments were explored. The interaction between human galectin 3 (Gal-3) and distinct macromolecular crowders, such as bovine and human serum albumin (BSA and HSA), Ficoll 70 and PEG3350, was scrutinized. The molecular recognition event of the specific ligand, lactose, by Gal-3 in crowding conditions was evaluated. Gal-3 interactions were monitored by NMR analysing chemical shift perturbation (CSP) and line broadening of 1 H 15 N-HSQC signals. The intensity of the Gal-3 1 H 15 N-HSQC signals decreased in the presence of all crowders, due to the increase in the solution viscosity and to the formation of large protein complexes. When glycosylated containing samples of BSA and HSA were used, signal broadening was more severe than that observed in the presence of the more viscous solutions of PEG3350 and Ficoll 70. However, for the samples containing glycoproteins, the signal intensity of 1 H 15 N-HSQC recovered upon addition of lactose. We show that serum proteins interact with Gal-3, through their α2,3-linked sialylgalactose moieties exposed at their surfaces, competing with lactose for the same binding site. The quinary interaction between Gal-3 and serum glycoproteins, could help to co-localize Gal-3 at the cell surface, and may play a role in adhesion and signalling functions of this protein. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of novel human damage response proteins targeted through yeast orthology.

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J Peter Svensson

Full Text Available Studies in Saccharomyces cerevisiae show that many proteins influence cellular survival upon exposure to DNA damaging agents. We hypothesized that human orthologs of these S. cerevisiae proteins would also be required for cellular survival after treatment with DNA damaging agents. For this purpose, human homologs of S. cerevisiae proteins were identified and mapped onto the human protein-protein interaction network. The resulting human network was highly modular and a series of selection rules were implemented to identify 45 candidates for human toxicity-modulating proteins. The corresponding transcripts were targeted by RNA interference in human cells. The cell lines with depleted target expression were challenged with three DNA damaging agents: the alkylating agents MMS and 4-NQO, and the oxidizing agent t-BuOOH. A comparison of the survival revealed that the majority (74% of proteins conferred either sensitivity or resistance. The identified human toxicity-modulating proteins represent a variety of biological functions: autophagy, chromatin modifications, RNA and protein metabolism, and telomere maintenance. Further studies revealed that MMS-induced autophagy increase the survival of cells treated with DNA damaging agents. In summary, we show that damage recovery proteins in humans can be identified through homology to S. cerevisiae and that many of the same pathways are represented among the toxicity modulators.

New insight into protein-nanomaterial interactions with UV-visible spectroscopy and chemometrics: human serum albumin and silver nanoparticles.

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Wang, Yong; Ni, Yongnian

2014-01-21

In recent years, great efforts have focused on the exploration and fabrication of protein nanoconjugates due to potential applications in many fields including bioanalytical science, biosensors, biocatalysis, biofuel cells and bio-based nanodevices. An important aspect of our understanding of protein nanoconjugates is to quantitatively understand how proteins interact with nanomaterials. In this report, human serum albumin (HSA) and citrate-coated silver nanoparticles (AgNPs) are selected as a case study of protein-nanomaterial interactions. UV-visible spectroscopy together with multivariate curve resolution by alternating least squares (MCR-ALS) algorithm is first exploited for the detailed study of AgNPs-HSA interactions. Introduction of the chemometrics tool allows extracting the kinetic profiles, spectra and distribution diagrams of two major absorbing pure species (AgNPs and AgNPs-HSA conjugate). These resolved profiles are then analysed to give the thermodynamic, kinetic and structural information of HSA binding to AgNPs. Transmission electron microscopy, circular dichroism spectroscopy and Fourier transform infrared spectroscopy are used to further characterize the complex system. Moreover, a sensitive spectroscopic biosensor for HSA is fabricated with the MCR-ALS resolved concentration of absorbing pure species. It is found that the linear range for the HSA nanosensor was from 1.9 nM to 45.0 nM with a detection limit of 0.9 nM. It is believed that the proposed method will play an important role in the fabrication and optimization of a robust nanobiosensor or cross-reactive sensors array for the detection and identification of biocomponents.

Yeast Interacting Proteins Database: YPR103W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors...gulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

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Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

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Jian-Feng Li

Full Text Available Protein-protein interactions (PPIs constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology.

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DeBlasio, Stacy L; Chavez, Juan D; Alexander, Mariko M; Ramsey, John; Eng, Jimmy K; Mahoney, Jaclyn; Gray, Stewart M; Bruce, James E; Cilia, Michelle

2016-02-15

Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection-hallmarks of host-pathogen interactions-were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction

Beta 3 and PDI proteins isolated from human platelets bind with ECwt rotavirus in vitro

International Nuclear Information System (INIS)

Mayorga, Diana; Rubio, Linda; Guerrero-Fonseca, Carlos A; Acosta-Losada, Orlando

2010-01-01

Commercial integrin Beta 3 is currently not available and commercial PDI is too expensive, which is making access difficult to these proteins needed for conducting experiments aimed at the establishment of possible interactions between integrin Beta 3 and PDI and wild type rotavirus strains. Objective. To explore a methodology allowing isolation of proteins Beta 3 and PDI from human platelets to be used as antigens in the generation of rabbit polyclonal antibodies useful in the assessment of interactions between these proteins and rotavirus ECwt. Materials and methods. Proteins Beta 3 and PDI from human platelet lysates were separated using preparative electrophoresis under reducing conditions and then eluted. Interactions of these proteins with rotavirus ECwt were analyzed using co-immunoprecipitation, Western blotting and capture ELISA. Results. Proteins from human platelet lysates were separated by preparative electrophoresis under reducing conditions. The identification of proteins Beta 3 and PDI present in a gel slice was performed through their reaction with commercial antibodies in a Western blotting analysis. Protein purity was established after electro elution from a gel slice. Polyclonal antibodies against protein Beta 3 were generated in rabbit. Incubation of eluted proteins Beta 3 and PDI with rotavirus ECwt showed in co-immunoprecipitation and ELISA assays that these proteins bound virus in vitro. The same binding was showed to occur when rotavirus was incubated with isolated small intestinal villi from suckling mice. Conclusions. Relatively high amounts of proteins Beta 3 and PDI were partially purified from human platelets by preparative electrophoresis. The isolation of these proteins allowed the generation of polyclonal antibodies against Beta 3 in addition to the establishment of the in vitro interaction of proteins Beta 3 and PDI with rotavirus ECwt. This interaction was also demonstrated in vivo after incubating the virus with isolated small

Binding of MCM-interacting proteins to ATP-binding site in MCM6

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Hosoi A

2016-03-01

Full Text Available Atsutoshi Hosoi, Taku Sakairi, Yukio Ishimi Graduate School of Science and Engineering, Ibaraki University, Mito, Ibaraki, Japan Abstract: The function of MCM2–7 complex that is a DNA helicase in DNA replication may be regulated by various MCM-interacting proteins, including CDC45, RPA, TIM, TIPIN, Claspin, MCM10, and MCM-BP. It has been shown by immunoprecipitation that human MCM6 interacts with all these proteins in coexpressed insect cells. To determine the region in MCM6 to interact with these proteins, we prepared various truncated forms of MCM6 and examined the interaction of these MCM6 fragments with the MCM-interacting proteins. All these proteins bound to C-terminal half of MCM6, and CDC45, RPA2, TIM, TIPIN, MCM-BP, and MCM10 bound to the fragments containing ATP-binding motifs. CDC45 and RPA2 bound to the smallest fragment containing Walker motif A. Only MCM-BP is bound to the N-terminal half of MCM6. Site-directed mutagenesis study suggests that hydrophobic interaction is involved in the interaction of MCM6 with CDC45 and TIM. These results suggest a possibility that MCM-interacting proteins regulate MCM2–7 function by modulating the ATP-binding ability of the MCM2–7. Keywords: DNA helicase, DNA replication, checkpoint, MCM2–7 proteins

Intracellular Distribution of Capsid-Associated pUL77 of Human Cytomegalovirus and Interactions with Packaging Proteins and pUL93.

Science.gov (United States)

Köppen-Rung, Pánja; Dittmer, Alexandra; Bogner, Elke

2016-07-01

DNA packaging into procapsids is a common multistep process during viral maturation in herpesviruses. In human cytomegalovirus (HCMV), the proteins involved in this process are terminase subunits pUL56 and pUL89, which are responsible for site-specific cleavage and insertion of the DNA into the procapsid via portal protein pUL104. However, additional viral proteins are required for the DNA packaging process. We have shown previously that the plasmid that encodes capsid-associated pUL77 encodes another potential player during capsid maturation. Pulse-chase experiments revealed that pUL77 is stably expressed during HCMV infection. Time course analysis demonstrated that pUL77 is expressed in the early late part of the infectious cycle. The sequence of pUL77 was analyzed to find nuclear localization sequences (NLSs), revealing monopartite NLSm at the N terminus and bipartite NLSb in the middle of pUL77. The potential NLSs were inserted into plasmid pHM829, which encodes a chimeric protein with β-galactosidase and green fluorescent protein. In contrast to pUL56, neither NLSm nor NLSb was sufficient for nuclear import. Furthermore, we investigated by coimmunoprecipitation whether packaging proteins, as well as pUL93, the homologue protein of herpes simplex virus 1 pUL17, are interaction partners of pUL77. The interactions between pUL77 and packaging proteins, as well as pUL93, were verified. We showed that the capsid-associated pUL77 is another potential player during capsid maturation of HCMV. Protein UL77 (pUL77) is a conserved core protein of HCMV. This study demonstrates for the first time that pUL77 has early-late expression kinetics during the infectious cycle and an intrinsic potential for nuclear translocation. According to its proposed functions in stabilization of the capsid and anchoring of the encapsidated DNA during packaging, interaction with further DNA packaging proteins is required. We identified physical interactions with terminase subunits pUL56 and p

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

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Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

Water-Protein Interactions: The Secret of Protein Dynamics

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Silvia Martini

2013-01-01

Full Text Available Water-protein interactions help to maintain flexible conformation conditions which are required for multifunctional protein recognition processes. The intimate relationship between the protein surface and hydration water can be analyzed by studying experimental water properties measured in protein systems in solution. In particular, proteins in solution modify the structure and the dynamics of the bulk water at the solute-solvent interface. The ordering effects of proteins on hydration water are extended for several angstroms. In this paper we propose a method for analyzing the dynamical properties of the water molecules present in the hydration shells of proteins. The approach is based on the analysis of the effects of protein-solvent interactions on water protons NMR relaxation parameters. NMR relaxation parameters, especially the nonselective (R1NS and selective (R1SE spin-lattice relaxation rates of water protons, are useful for investigating the solvent dynamics at the macromolecule-solvent interfaces as well as the perturbation effects caused by the water-macromolecule interactions on the solvent dynamical properties. In this paper we demonstrate that Nuclear Magnetic Resonance Spectroscopy can be used to determine the dynamical contributions of proteins to the water molecules belonging to their hydration shells.

Structure and function of ameloblastin as an extracellular matrix protein: adhesion, calcium binding, and CD63 interaction in human and mouse.

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Zhang, Xu; Diekwisch, Thomas G H; Luan, Xianghong

2011-12-01

The functional significance of extracellular matrix proteins in the life of vertebrates is underscored by a high level of sequence variability in tandem with a substantial degree of conservation in terms of cell-cell and cell-matrix adhesion interactions. Many extracellular matrix proteins feature multiple adhesion domains for successful attachment to substrates, such as integrin, CD63, and heparin. Here we have used homology and ab initio modeling algorithms to compare mouse ameloblastin (mAMBN) and human ameloblastin (hABMN) isoforms and to analyze their potential for cell adhesion and interaction with other matrix molecules as well as calcium binding. Sequence comparison between mAMBN and hAMBN revealed a 26-amino-acid deletion in mAMBN, corresponding to a helix-loop-helix frameshift. The human AMBN domain (174Q-201G), homologous to the mAMBN 157E-178I helix-loop-helix region, formed a helix-loop motif with an extended loop, suggesting a higher degree of flexibility of hAMBN compared with mAMBN, as confirmed by molecular dynamics simulation. Heparin-binding domains, CD63-interaction domains, and calcium-binding sites in both hAMBN and mAMBN support the concept of AMBN as an extracellular matrix protein. The high level of conservation between AMBN functional domains related to adhesion and differentiation was remarkable when compared with only 61% amino acid sequence homology. © 2011 Eur J Oral Sci.

High pressure as a tool for investigating protein-ligand interactions

International Nuclear Information System (INIS)

Marchal, S; Lange, R; Tortora, P; Balny, C

2004-01-01

In recent years, the application of pressure on biological systems has gained increasing interest. Pressure-induced destabilization of electrostatic and hydrophobic interactions is currently exploited to study conformational protein stability and macromolecular assemblies of proteins. Due to links between severe human pathologies and ordered protein oligomerization into aggregates, which have become apparent, a better knowledge of the molecular and structural determinants that ensure the packing efficiency and stability of such complexes has taken on special importance. Here, we report the effect of pressure on the property of human ataxin-3 of aggregation. The results indicate the importance of its polyglutamine chain length in the stability and the tendency of the protein to form spheroids. Partial unfolding of the protein leading to solvent exposure of hydrophobic domains appears to be a prerequisite in the aggregation process of ataxin-3

Interaction of Citrinin with Human Serum Albumin

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Miklós Poór

2015-12-01

Full Text Available Citrinin (CIT is a mycotoxin produced by several Aspergillus, Penicillium, and Monascus species. CIT occurs worldwide in different foods and drinks and causes health problems for humans and animals. Human serum albumin (HSA is the most abundant plasma protein in human circulation. Albumin forms stable complexes with many drugs and xenobiotics; therefore, HSA commonly plays important role in the pharmacokinetics or toxicokinetics of numerous compounds. However, the interaction of CIT with HSA is poorly characterized yet. In this study, the complex formation of CIT with HSA was investigated using fluorescence spectroscopy and ultrafiltration techniques. For the deeper understanding of the interaction, thermodynamic, and molecular modeling studies were performed as well. Our results suggest that CIT forms stable complex with HSA (logK ~ 5.3 and its primary binding site is located in subdomain IIA (Sudlow’s Site I. In vitro cell experiments also recommend that CIT-HSA interaction may have biological relevance. Finally, the complex formations of CIT with bovine, porcine, and rat serum albumin were investigated, in order to test the potential species differences of CIT-albumin interactions.

Protein-protein interactions in the regulation of WRKY transcription factors.

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Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

Regulation of Nuclear Receptor Interacting Protein 1 (NRIP1) Gene Expression in Response to Weight Loss and Exercise in Humans

DEFF Research Database (Denmark)

De Marinis, Yang Z; Sun, Jiangming; Bompada, Pradeep

2017-01-01

Objective: Nuclear receptor interacting protein 1 (NRIP1) is an important energy regulator, but few studies have addressed its role in humans. This study investigated adipose tissue and skeletal muscle NRIP1 gene expression and serum levels in response to weight loss and exercise in humans. Methods...... network/module. Conclusions: NRIP1 gene expression and serum levels are strongly associated with metabolic states such as obesity, weight loss, different types of exercise, and peripheral tissue insulin resistance, potentially as a mediator of sedentary effects.......: In patients with obesity, adipose tissue NRIP1 mRNA expression increased during weight loss and weight maintenance and showed strong associations with metabolic markers and anthropometric parameters. Serum NRIP1 protein levels also increased after weight loss. In skeletal muscle, imposed rest increased NRIP1...

Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.

Science.gov (United States)

An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu

2017-08-18

Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://219.219.62.123:8888/WELMLAG/ .

Yeast Interacting Proteins Database: YMR280C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available olved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensor... glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, an

Protein-Protein Interaction Databases

DEFF Research Database (Denmark)

Szklarczyk, Damian; Jensen, Lars Juhl

2015-01-01

Years of meticulous curation of scientific literature and increasingly reliable computational predictions have resulted in creation of vast databases of protein interaction data. Over the years, these repositories have become a basic framework in which experiments are analyzed and new directions...

The epsins define a family of proteins that interact with components of the clathrin coat and contain a new protein module

DEFF Research Database (Denmark)

Rosenthal, J A; Chen, H; Slepnev, V I

1999-01-01

Epsin (epsin 1) is an interacting partner for the EH domain-containing region of Eps15 and has been implicated in conjunction with Eps15 in clathrin-mediated endocytosis. We report here the characterization of a similar protein (epsin 2), which we have cloned from human and rat brain libraries. E...... fluorescent protein-epsin 2 mislocalizes components of the clathrin coat and inhibits clathrin-mediated endocytosis. The epsins define a new protein family implicated in membrane dynamics at the cell surface.......Epsin (epsin 1) is an interacting partner for the EH domain-containing region of Eps15 and has been implicated in conjunction with Eps15 in clathrin-mediated endocytosis. We report here the characterization of a similar protein (epsin 2), which we have cloned from human and rat brain libraries...

Structural model for the interaction of a designed Ankyrin Repeat Protein with the human epidermal growth factor receptor 2.

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V Chandana Epa

Full Text Available Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2. HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84-1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions.

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

Science.gov (United States)

Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Characterization of MRP RNA-protein interactions within the perinucleolar compartment.

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Pollock, Callie; Daily, Kelly; Nguyen, Van Trung; Wang, Chen; Lewandowska, Marzena Anna; Bensaude, Olivier; Huang, Sui

2011-03-15

The perinucleolar compartment (PNC) forms in cancer cells and is highly enriched with a subset of polymerase III RNAs and RNA-binding proteins. Here we report that PNC components mitochondrial RNA-processing (MRP) RNA, pyrimidine tract-binding protein (PTB), and CUG-binding protein (CUGBP) interact in vivo, as demonstrated by coimmunoprecipitation and RNA pull-down experiments. Glycerol gradient analyses show that this complex is large and sediments at a different fraction from known MRP RNA-containing complexes, the MRP ribonucleoprotein ribozyme and human telomerase reverse transcriptase. Tethering PNC components to a LacO locus recruits other PNC components, further confirming the in vivo interactions. These interactions are present both in PNC-containing and -lacking cells. High-resolution localization analyses demonstrate that MRP RNA, CUGBP, and PTB colocalize at the PNC as a reticulated network, intertwining with newly synthesized RNA. Furthermore, green fluorescent protein (GFP)-PTB and GFP-CUGBP show a slower rate of fluorescence recovery after photobleaching at the PNC than in the nucleoplasm, illustrating the different molecular interaction of the complexes associated with the PNC. These findings support a working model in which the MRP RNA-protein complex becomes nucleated at the PNC in cancer cells and may play a role in gene expression regulation at the DNA locus that associates with the PNC.

Complete cDNA sequence coding for human docking protein

Energy Technology Data Exchange (ETDEWEB)

Hortsch, M; Labeit, S; Meyer, D I

1988-01-11

Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.

Screening of cellular proteins that interact with the classical swine ...

Indian Academy of Sciences (India)

2014-01-27

Jan 27, 2014 ... to screen for CSFV NS5A interactive proteins in the cDNA library of the swine umbilical vein endothelial cell. (SUVEC). Alignment ... development. The finding of ..... were unknown, the results of the BLAST against the human.

PSAIA – Protein Structure and Interaction Analyzer

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Vlahoviček Kristian

2008-04-01

Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

A Bipartite Network-based Method for Prediction of Long Non-coding RNA–protein Interactions

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Mengqu Ge

2016-02-01

Full Text Available As one large class of non-coding RNAs (ncRNAs, long ncRNAs (lncRNAs have gained considerable attention in recent years. Mutations and dysfunction of lncRNAs have been implicated in human disorders. Many lncRNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here, we introduce a computational method named lncRNA–protein bipartite network inference (LPBNI. LPBNI aims to identify potential lncRNA–interacting proteins, by making full use of the known lncRNA–protein interactions. Leave-one-out cross validation (LOOCV test shows that LPBNI significantly outperforms other network-based methods, including random walk (RWR and protein-based collaborative filtering (ProCF. Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lncRNA–interacting proteins.

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

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Mo Min

2008-05-01

Full Text Available Abstract Background The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. Results By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17% showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. Conclusion An

PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

Science.gov (United States)

Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

2011-06-01

Physics approaches focus on uncovering, modeling and quantitating the general principles governing the micro and macro universe. This has always been an important component of biological research, however recent advances in experimental techniques and the accumulation of unprecedented genome-scale experimental data produced by these novel technologies now allow for addressing fundamental questions on a large scale. These relate to molecular interactions, principles of bimolecular recognition, and mechanisms of signal propagation. The functioning of a cell requires a variety of intermolecular interactions including protein-protein, protein-DNA, protein-RNA, hormones, peptides, small molecules, lipids and more. Biomolecules work together to provide specific functions and perturbations in intermolecular communication channels often lead to cellular malfunction and disease. A full understanding of the interactome requires an in-depth grasp of the biophysical principles underlying individual interactions as well as their organization in cellular networks. Phenomena can be described at different levels of abstraction. Computational and systems biology strive to model cellular processes by integrating and analyzing complex data from multiple experimental sources using interdisciplinary tools. As a result, both the causal relationships between the variables and the general features of the system can be discovered, which even without knowing the details of the underlying mechanisms allow for putting forth hypotheses and predicting the behavior of the systems in response to perturbation. And here lies the strength of in silico models which provide control and predictive power. At the same time, the complexity of individual elements and molecules can be addressed by the fields of molecular biophysics, physical biology and structural biology, which focus on the underlying physico-chemical principles and may explain the molecular mechanisms of cellular function. In this issue

DomPep--a general method for predicting modular domain-mediated protein-protein interactions.

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Lei Li

Full Text Available Protein-protein interactions (PPIs are frequently mediated by the binding of a modular domain in one protein to a short, linear peptide motif in its partner. The advent of proteomic methods such as peptide and protein arrays has led to the accumulation of a wealth of interaction data for modular interaction domains. Although several computational programs have been developed to predict modular domain-mediated PPI events, they are often restricted to a given domain type. We describe DomPep, a method that can potentially be used to predict PPIs mediated by any modular domains. DomPep combines proteomic data with sequence information to achieve high accuracy and high coverage in PPI prediction. Proteomic binding data were employed to determine a simple yet novel parameter Ligand-Binding Similarity which, in turn, is used to calibrate Domain Sequence Identity and Position-Weighted-Matrix distance, two parameters that are used in constructing prediction models. Moreover, DomPep can be used to predict PPIs for both domains with experimental binding data and those without. Using the PDZ and SH2 domain families as test cases, we show that DomPep can predict PPIs with accuracies superior to existing methods. To evaluate DomPep as a discovery tool, we deployed DomPep to identify interactions mediated by three human PDZ domains. Subsequent in-solution binding assays validated the high accuracy of DomPep in predicting authentic PPIs at the proteome scale. Because DomPep makes use of only interaction data and the primary sequence of a domain, it can be readily expanded to include other types of modular domains.

Scoring functions for protein-protein interactions.

Science.gov (United States)

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification of Inhibitors of Biological Interactions Involving Intrinsically Disordered Proteins

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Daniela Marasco

2015-04-01

Full Text Available Protein–protein interactions involving disordered partners have unique features and represent prominent targets in drug discovery processes. Intrinsically Disordered Proteins (IDPs are involved in cellular regulation, signaling and control: they bind to multiple partners and these high-specificity/low-affinity interactions play crucial roles in many human diseases. Disordered regions, terminal tails and flexible linkers are particularly abundant in DNA-binding proteins and play crucial roles in the affinity and specificity of DNA recognizing processes. Protein complexes involving IDPs are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to modulate them can produce important lead compounds: in this scenario peptides and/or peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. Here, we propose a panoramic review of the structural features of IDPs and how they regulate molecular recognition mechanisms focusing attention on recently reported drug-design strategies in the field of IDPs.

The role of electrostatics in protein-protein interactions of a monoclonal antibody.

Science.gov (United States)

Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R

2014-07-07

Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.

Detecting protein-protein interactions in living cells

DEFF Research Database (Denmark)

Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche

2009-01-01

to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C......-terminal of the NMDA receptor and PDZ2 of PSD-95 were fused to green fluorescent protein (GFP) and Renilla luciferase (Rluc) and expressed in COS7 cells. A robust and specific BRET signal was obtained by expression of the appropriate partner proteins and subsequently, the assay was used to evaluate a Tat......The PDZ domain mediated interaction between the NMDA receptor and its intracellular scaffolding protein, PSD-95, is a potential target for treatment of ischemic brain diseases. We have recently developed a number of peptide analogues with improved affinity for the PDZ domains of PSD-95 compared...

HIV-1 Nef binds with human GCC185 protein and regulates mannose 6 phosphate receptor recycling

Energy Technology Data Exchange (ETDEWEB)

Kumar, Manjeet; Kaur, Supinder; Nazir, Aamir; Tripathi, Raj Kamal, E-mail: rajkamalcdri@gmail.com

2016-05-20

HIV-1 Nef modulates cellular function that enhances viral replication in vivo which culminate into AIDS pathogenesis. With no enzymatic activity, Nef regulates cellular function through host protein interaction. Interestingly, trans-cellular introduction of recombinant Nef protein in Caenorhabditis elegans results in AIDS like pathogenesis which might share common pathophysiology because the gene sequence of C. elegans and humans share considerable homology. Therefore employing C. elegans based initial screen complemented with sequence based homology search we identified GCC185 as novel host protein interacting with HIV-1 Nef. The detailed molecular characterization revealed N-terminal EEEE{sub 65} acidic domain of Nef as key region for interaction. GCC185 is a tethering protein that binds with Rab9 transport vesicles. Our results show that Nef-GCC185 interaction disrupts Rab9 interaction resulting in delocalization of CI-MPR (cation independent Mannose 6 phosphate receptor) resulting in elevated secretion of hexosaminidase. In agreement with this, our studies identified novel host GCC185 protein that interacts with Nef EEEE65 acidic domain interfering GCC185-Rab9 vesicle membrane fusion responsible for retrograde vesicular transport of CI-MPR from late endosomes to TGN. In light of existing report suggesting critical role of Nef-GCC185 interaction reveals valuable mechanistic insights affecting specific protein transport pathway in docking of late endosome derived Rab9 bearing transport vesicle at TGN elucidating role of Nef during viral pathogenesis. -- Highlights: •Nef, an accessory protein of HIV-1 interacts with host factor and culminates into AIDS pathogenesis. •Using Caenorhabditis elegans based screen system, novel Nef interacting cellular protein GCC185 was identified. •Molecular characterization of Nef and human protein GCC185 revealed Nef EEEE{sub 65} key region interacted with full length GCC185. •Nef impeded the GCC185-Rab 9 interaction and

Globular and disordered – the non-identical twins in protein-protein interactions

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Kaare eTeilum

2015-07-01

Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.

Emergence of modularity and disassortativity in protein-protein interaction networks.

Science.gov (United States)

Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

2010-12-01

In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

Inferring modules from human protein interactome classes

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Chaurasia Gautam

2010-07-01

Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.

Dendrimer-protein interactions versus dendrimer-based nanomedicine.

Science.gov (United States)

Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

2017-04-01

Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of the human GARP (Golgi associated retrograde protein) complex

International Nuclear Information System (INIS)

Liewen, Heike; Meinhold-Heerlein, Ivo; Oliveira, Vasco; Schwarzenbacher, Robert; Luo Guorong; Wadle, Andreas; Jung, Martin; Pfreundschuh, Michael; Stenner-Liewen, Frank

2005-01-01

The Golgi associated retrograde protein complex (GARP) or Vps fifty-three (VFT) complex is part of cellular inter-compartmental transport systems. Here we report the identification of the VFT tethering factor complex and its interactions in mammalian cells. Subcellular fractionation shows that human Vps proteins are found in the smooth membrane/Golgi fraction but not in the cytosol. Immunostaining of human Vps proteins displays a vesicular distribution most concentrated at the perinuclear envelope. Co-staining experiments with endosomal markers imply an endosomal origin of these vesicles. Significant accumulation of VFT complex positive endosomes is found in the vicinity of the Trans Golgi Network area. This is in accordance with a putative role in Golgi associated transport processes. In Saccharomyces cerevisiae, GARP is the main effector of the small GTPase Ypt6p and interacts with the SNARE Tlg1p to facilitate membrane fusion. Accordingly, the human homologue of Ypt6p, Rab6, specifically binds hVps52. In human cells, the 'orphan' SNARE Syntaxin 10 is the genuine binding partner of GARP mediated by hVps52. This reveals a previously unknown function of human Syntaxin 10 in membrane docking and fusion events at the Golgi. Taken together, GARP shows significant conservation between various species but diversification and specialization result in important differences in human cells

Towards a map of the Populus biomass protein-protein interaction network

Energy Technology Data Exchange (ETDEWEB)

Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2015-07-31

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in

Identification of the Specific Interactors of the Human Lariat RNA Debranching Enzyme 1 Protein

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So Masaki

2015-02-01

Full Text Available In eukaryotes, pre-mRNA splicing is an essential step for gene expression. We have been analyzing post-splicing intron turnover steps in higher eukaryotes. Here, we report protein interaction between human Debranching enzyme 1 (hDbr1 and several factors found in the Intron Large (IL complex, which is an intermediate complex of the intron degradation pathway. The hDbr1 protein specifically interacts with xeroderma pigmentosum, complementeation group A (XPA-binding protein 2 (Xab2. We also attempted to identify specific interactors of hDbr1. Co-immunoprecipitation experiments followed by mass spectrometry analysis identified a novel protein as one of the specific interactors of hDbr1. This protein is well conserved among many species and shows the highest similarity to yeast Drn1, so it is designated as human Dbr1 associated ribonuclease 1 (hDrn1. hDrn1 directly interacts with hDbr1 through protein–protein interaction. Furthermore, hDrn1 shuttles between the nucleus and the cytoplasm, as hDbr1 protein does. These findings suggest that hDrn1 has roles in both the nucleus and the cytoplasm, which are highly likely to involve hDbr1.

Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

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Canard Bruno

2011-10-01

Full Text Available Abstract Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4. Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.

Globular and disordered-the non-identical twins in protein-protein interactions

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt

2015-01-01

as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

Structural analysis of recombinant human protein QM

International Nuclear Information System (INIS)

Gualberto, D.C.H.; Fernandes, J.L.; Silva, F.S.; Saraiva, K.W.; Affonso, R.; Pereira, L.M.; Silva, I.D.C.G.

2012-01-01

Full text: The ribosomal protein QM belongs to a family of ribosomal proteins, which is highly conserved from yeast to humans. The presence of the QM protein is necessary for joining the 60S and 40S subunits in a late step of the initiation of mRNA translation. Although the exact extra-ribosomal functions of QM are not yet fully understood, it has been identified as a putative tumor suppressor. This protein was reported to interact with the transcription factor c-Jun and thereby prevent c-Jun actives genes of the cellular growth. In this study, the human QM protein was expressed in bacterial system, in the soluble form and this structure was analyzed by Circular Dichroism and Fluorescence. The results of Circular Dichroism showed that this protein has less alpha helix than beta sheet, as described in the literature. QM protein does not contain a leucine zipper region; however the ion zinc is necessary for binding of QM to c-Jun. Then we analyzed the relationship between the removal of zinc ions and folding of protein. Preliminary results obtained by the technique Fluorescence showed a gradual increase in fluorescence with the addition of increasing concentration of EDTA. This suggests that the zinc is important in the tertiary structure of the protein. More studies are being made for better understand these results. (author)

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

Science.gov (United States)

Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Characterization of MRP RNA–protein interactions within the perinucleolar compartment

Science.gov (United States)

Pollock, Callie; Daily, Kelly; Nguyen, Van Trung; Wang, Chen; Lewandowska, Marzena Anna; Bensaude, Olivier; Huang, Sui

2011-01-01

The perinucleolar compartment (PNC) forms in cancer cells and is highly enriched with a subset of polymerase III RNAs and RNA-binding proteins. Here we report that PNC components mitochondrial RNA–processing (MRP) RNA, pyrimidine tract–binding protein (PTB), and CUG-binding protein (CUGBP) interact in vivo, as demonstrated by coimmunoprecipitation and RNA pull-down experiments. Glycerol gradient analyses show that this complex is large and sediments at a different fraction from known MRP RNA–containing complexes, the MRP ribonucleoprotein ribozyme and human telomerase reverse transcriptase. Tethering PNC components to a LacO locus recruits other PNC components, further confirming the in vivo interactions. These interactions are present both in PNC-containing and -lacking cells. High-resolution localization analyses demonstrate that MRP RNA, CUGBP, and PTB colocalize at the PNC as a reticulated network, intertwining with newly synthesized RNA. Furthermore, green fluorescent protein (GFP)–PTB and GFP-CUGBP show a slower rate of fluorescence recovery after photobleaching at the PNC than in the nucleoplasm, illustrating the different molecular interaction of the complexes associated with the PNC. These findings support a working model in which the MRP RNA–protein complex becomes nucleated at the PNC in cancer cells and may play a role in gene expression regulation at the DNA locus that associates with the PNC. PMID:21233287

Protein complex prediction based on k-connected subgraphs in protein interaction network

OpenAIRE

Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

2010-01-01

Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

The SNARE protein SNAP23 and the SNARE-interacting protein Munc18c in human skeletal muscle are implicated in insulin resistance/type 2 diabetes

DEFF Research Database (Denmark)

Boström, Pontus; Andersson, Linda; Vind, Birgitte

2010-01-01

/cytosolic compartment in the patients with the type 2 diabetes. Expression of the SNARE-interacting protein Munc18c was higher in skeletal muscle from patients with type 2 diabetes. Studies in L6 cells showed that Munc18c promoted the expression of SNAP23. CONCLUSIONS: We have translated our previous in vitro results......OBJECTIVE: Our previous studies suggest that the SNARE protein synaptosomal-associated protein of 23 kDa (SNAP23) is involved in the link between increased lipid levels and insulin resistance in cardiomyocytes. The objective was to determine whether SNAP23 may also be involved in the known...... association between lipid accumulation in skeletal muscle and insulin resistance/type 2 diabetes in humans, as well as to identify a potential regulator of SNAP23. RESEARCH DESIGN AND METHODS: We analyzed skeletal muscle biopsies from patients with type 2 diabetes and healthy, insulin-sensitive control...

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

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Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

2015-12-01

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Building blocks for protein interaction devices

Science.gov (United States)

Grünberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis

2010-01-01

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them. PMID:20215443

Analysis of intraviral protein-protein interactions of the SARS coronavirus ORFeome.

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Albrecht von Brunn

2007-05-01

Full Text Available The severe acute respiratory syndrome coronavirus (SARS-CoV genome is predicted to encode 14 functional open reading frames, leading to the expression of up to 30 structural and non-structural protein products. The functions of a large number of viral ORFs are poorly understood or unknown. In order to gain more insight into functions and modes of action and interaction of the different proteins, we cloned the viral ORFeome and performed a genome-wide analysis for intraviral protein interactions and for intracellular localization. 900 pairwise interactions were tested by yeast-two-hybrid matrix analysis, and more than 65 positive non-redundant interactions, including six self interactions, were identified. About 38% of interactions were subsequently confirmed by CoIP in mammalian cells. Nsp2, nsp8 and ORF9b showed a wide range of interactions with other viral proteins. Nsp8 interacts with replicase proteins nsp2, nsp5, nsp6, nsp7, nsp8, nsp9, nsp12, nsp13 and nsp14, indicating a crucial role as a major player within the replication complex machinery. It was shown by others that nsp8 is essential for viral replication in vitro, whereas nsp2 is not. We show that also accessory protein ORF9b does not play a pivotal role for viral replication, as it can be deleted from the virus displaying normal plaque sizes and growth characteristics in Vero cells. However, it can be expected to be important for the virus-host interplay and for pathogenicity, due to its large number of interactions, by enhancing the global stability of the SARS proteome network, or play some unrealized role in regulating protein-protein interactions. The interactions identified provide valuable material for future studies.

Human-machine interactions

Science.gov (United States)

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

Science.gov (United States)

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

International Nuclear Information System (INIS)

Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

2015-01-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

Energy Technology Data Exchange (ETDEWEB)

Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

2015-03-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

Molecular Analysis of AFP and HSA Interactions with PTEN Protein

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Mingyue Zhu

2015-01-01

Full Text Available Human cytoplasmic alpha-fetoprotein (AFP has been classified as a member of the albuminoid gene family. The protein sequence of AFP has significant homology to that of human serum albumin (HSA, but its biological characteristics are vastly different from HSA. The AFP functions as a regulator in the phosphatidylinositol 3-kinase (PI3K/protein kinase B (AKT pathway, but HSA plays a key role as a transport protein. To probe their molecular mechanisms, we have applied colocalization, coimmunoprecipitation (co-IP, and molecular docking approaches to analyze the differences between AFP and HSA. The data from colocalization and co-IP displayed a strong interaction between AFP and PTEN (phosphatase and tensin homolog, demonstrating that AFP did bind to PTEN, but HSA did not. The molecular docking study further showed that the AFP domains I and III could contact with PTEN. In silicon substitutions of AFP binding site residues at position 490M/K and 105L/R corresponding to residues K490 and R105 in HSA resulted in steric clashes with PTEN residues R150 and K46, respectively. These steric clashes may explain the reason why HSA cannot bind to PTEN. Ultimately, the experimental results and the molecular modeling data from the interactions of AFP and HSA with PTEN will help us to identify targets for designing drugs and vaccines against human hepatocellular carcinoma.

Protein complex prediction based on k-connected subgraphs in protein interaction network

Directory of Open Access Journals (Sweden)

Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

Effect of Astringent Stimuli on Salivary Protein Interactions Elucidated by Complementary Proteomics Approaches.

Science.gov (United States)

Delius, Judith; Médard, Guillaume; Kuster, Bernhard; Hofmann, Thomas

2017-03-15

The interaction of astringent substances with salivary proteins, which results in protein precipitation, is considered a key event in the molecular mechanism underlying the oral sensation of puckering astringency. As the chemical nature of orally active astringents is diverse and the knowledge of their interactions with salivary proteins rather fragmentary, human whole saliva samples were incubated with suprathreshold and isointensity solutions of the astringent polyphenol (-)-epigallocatechin gallate, the multivalent metal salt iron(III) sulfate, the amino-functionalized polysaccharide chitosan, and the basic protein lysozyme. After separation of the precipitated proteins, the proteins affected by the astringents were identified and relatively quantified for the first time by complementary bottom-up and top-down mass spectrometry-based proteomics approaches. Major salivary target proteins, which may be involved in astringency perception, are reported here for each astringent stimulus.

Molecular simulations of lipid-mediated protein-protein interactions

NARCIS (Netherlands)

de Meyer, F.J.M.; Venturoli, M.; Smit, B.

2008-01-01

Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the

Efficient extraction of protein-protein interactions from full-text articles.

Science.gov (United States)

Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

2010-01-01

Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

Science.gov (United States)

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

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Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

Plasminogen and angiostatin interact with heat shock proteins.

Science.gov (United States)

Dudani, Anil K; Mehic, Jelica; Martyres, Anthony

2007-06-01

Previous studies from this laboratory have demonstrated that plasminogen and angiostatin bind to endothelial cell (EC) surface-associated actin via their kringles in a specific manner. Heat shock proteins (hsps) like hsp 27 are constitutively expressed by vascular ECs and regulate actin polymerization, cell growth, and migration. Since many hsps have also been found to be highly abundant on cell surfaces and there is evidence that bacterial surface hsps may interact with human plasminogen, the purpose of this study was to determine whether human plasminogen and angiostatin would interact with human hsps. ELISAs were developed in our laboratory to assess these interactions. It was observed that plasminogen bound to hsps 27, 60, and 70. In all cases, binding was inhibited (85-90%) by excess (50 mM) lysine indicating kringle involvement. Angiostatin predominantly bound to hsp 27 and to hsp 70 in a concentration- and kringle-dependent manner. As observed previously for actin, there was concentration-dependent inhibition of angiostatin's interaction with hsp 27 by plasminogen. In addition, 30-fold molar excess actin inhibited (up to 50%), the interaction of plasminogen with all hsps. However, 30-fold molar excess actin could only inhibit the interaction of angiostatin with hsp 27 by 15-20%. Collectively, these data indicate that (i) while plasminogen interacts specifically with hsp 27, 60, and 70, angiostatin interacts predominantly with hsp 27 and to some extent with hsp 70; (ii) plasminogen only partially displaces angiostatin's binding to hsp 27 and (iii) actin only partially displaces plasminogen/angiostatin binding to hsps. It is conceivable therefore that surface-associated hsps could mediate the binding of these ligands to cells like ECs.

Interaction of human laminin receptor with Sup35, the [PSI⁺] prion-forming protein from S. cerevisiae: a yeast model for studies of LamR interactions with amyloidogenic proteins.

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Christine Pampeno

Full Text Available The laminin receptor (LamR is a cell surface receptor for extracellular matrix laminin, whereas the same protein within the cell interacts with ribosomes, nuclear proteins and cytoskeletal fibers. LamR has been shown to be a receptor for several bacteria and viruses. Furthermore, LamR interacts with both cellular and infectious forms of the prion protein, PrP(C and PrP(Sc. Indeed, LamR is a receptor for PrP(C. Whether LamR interacts with PrP(Sc exclusively in a capacity of the PrP receptor, or LamR specifically recognizes prion determinants of PrP(Sc, is unclear. In order to explore whether LamR has a propensity to interact with prions and amyloids, we examined LamR interaction with the yeast prion-forming protein, Sup35. Sup35 is a translation termination factor with no homology or functional relationship to PrP. Plasmids expressing LamR or LamR fused with the green fluorescent protein (GFP were transformed into yeast strain variants differing by the presence or absence of the prion conformation of Sup35, respectively [PSI⁺] and [psi⁻]. Analyses by immunoprecipitation, centrifugal fractionation and fluorescent microscopy reveal interaction between LamR and Sup35 in [PSI⁺] strains. The presence of [PSI⁺] promotes LamR co-precipitation with Sup35 as well as LamR aggregation. In [PSI⁺] cells, LamR tagged with GFP or mCherry forms bright fluorescent aggregates that co-localize with visible [PSI⁺] foci. The yeast prion model will facilitate studying the interaction of LamR with amyloidogenic prions in a safe and easily manipulated system that may lead to a better understanding and treatment of amyloid diseases.

An analysis pipeline for the inference of protein-protein interaction networks

Energy Technology Data Exchange (ETDEWEB)

Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

2009-12-01

An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

Identification of structural protein-protein interactions of herpes simplex virus type 1.

Science.gov (United States)

Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

2008-09-01

In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

Identification of new interacting partners of the shuttling protein ubinuclein (Ubn-1)

Energy Technology Data Exchange (ETDEWEB)

Lupo, Julien [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); CHU de Grenoble, BP217, 38043 Grenoble Cedex 9 (France); Conti, Audrey [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); Sueur, Charlotte [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); CHU de Grenoble, BP217, 38043 Grenoble Cedex 9 (France); Coly, Pierre-Alain [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); Coute, Yohann [CEA, IRTSV, Laboratoire Biologie a Grande Echelle, F-38054 Grenoble (France); INSERM, U1038, F-38054 Grenoble (France); Universite Joseph Fourier, Grenoble 1, F-38000 Grenoble Cedex 09 (France); Hunziker, Walter [Institute of Molecular and Cell Biology, Epithelial Cell Biology Laboratory, Singapore 1386473 (Singapore); Burmeister, Wim P. [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); Germi, Raphaelle [Unit of Virus Host Cell Interactions (UVHCI), UMI 3265 UJF-EMBL-CNRS, 6 rue Jules Horowitz, BP 181, F-38042 Grenoble Cedex 9 (France); CHU de Grenoble, BP217, 38043 Grenoble Cedex 9 (France); Manet, Evelyne; Gruffat, Henri [INSERM U758, Unite de Virologie humaine, Lyon, 46 allee d' Italie F-69007 France (France); Ecole Normale Superieure de Lyon, F-69007 France (France); Universite Lyon1, F-69007, Lyon (France); and others

2012-03-10

We have previously characterized ubinuclein (Ubn-1) as a NACos (Nuclear and Adherent junction Complex components) protein which interacts with viral or cellular transcription factors and the tight junction (TJ) protein ZO-1. The purpose of the present study was to get more insights on the binding partners of Ubn-1, notably those present in the epithelial junctions. Using an in vivo assay of fluorescent protein-complementation assay (PCA), we demonstrated that the N-terminal domains of the Ubn-1 and ZO-1 proteins triggered a functional interaction inside the cell. Indeed, expression of both complementary fragments of venus fused to the N-terminal parts of Ubn-1 and ZO-1 was able to reconstitute a fluorescent venus protein. Furthermore, nuclear expression of the chimeric Ubn-1 triggered nuclear localization of the chimeric ZO-1. We could localize this interaction to the PDZ2 domain of ZO-1 using an in vitro pull-down assay. More precisely, a 184-amino acid region (from amino acids 39 to 223) at the N-terminal region of Ubn-1 was responsible for the interaction with the PDZ2 domain of ZO-1. Co-imunoprecipitation and confocal microscopy experiments also revealed the tight junction protein cingulin as a new interacting partner of Ubn-1. A proteomic approach based on mass spectrometry analysis (MS) was then undertaken to identify further binding partners of GST-Ubn-1 fusion protein in different subcellular fractions of human epithelial HT29 cells. LYRIC (Lysine-rich CEACAM1-associated protein) and RACK-1 (receptor for activated C-kinase) proteins were validated as bona fide interacting partners of Ubn-1. Altogether, these results suggest that Ubn-1 is a scaffold protein influencing protein subcellular localization and is involved in several processes such as cell-cell contact signalling or modulation of gene activity.

Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

Science.gov (United States)

Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

2015-03-26

Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

Setting up a Bioluminescence Resonance Energy Transfer high throughput screening assay to search for protein/protein interaction inhibitors in mammalian cells.

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Cyril eCouturier

2012-09-01

Full Text Available Each step of the cell life and its response or adaptation to its environment are mediated by a network of protein/protein interactions termed interactome. Our knowledge of this network keeps growing due to the development of sensitive techniques devoted to study these interactions. The bioluminescence resonance energy transfer (BRET technique was primarily developed to allow the dynamic monitoring of protein-protein interactions in living cells, and has widely been used to study receptor activation by intra- or extra-molecular conformational changes within receptors and activated complexes in mammal cells. Some interactions are described as crucial in human pathological processes, and a new class of drugs targeting them has recently emerged. The BRET method is well suited to identify inhibitors of protein-protein interactions and here is described why and how to set up and optimize a High Throughput Screening assay based on BRET to search for such inhibitory compounds. The different parameters to take into account when developing such BRET assays in mammal cells are reviewed to give general guidelines: considerations on the targeted interaction, choice of BRET version, inducibility of the interaction, kinetic of the monitored interaction, and of the BRET reading, influence substrate concentration, number of cells and medium composition used on the Z’ factor, and expected interferences for colored or fluorescent compounds.

Differential interaction of Apolipoprotein-E isoforms with insulin receptors modulates brain insulin signaling in mutant human amyloid precursor protein transgenic mice.

Science.gov (United States)

Chan, Elizabeth S; Chen, Christopher; Cole, Gregory M; Wong, Boon-Seng

2015-09-08

It is unclear how human apolipoprotein E4 (ApoE4) increases the risk for Alzheimer's disease (AD). Although Aβ levels can lead to insulin signaling impairment, these experiments were done in the absence of human ApoE. To examine ApoE role, we crossed the human ApoE-targeted replacement mice with mutant human amyloid precursor protein (APP) mice. In 26 week old mice with lower Aβ levels, the expression and phosphorylation of insulin signaling proteins remained comparable among APP, ApoE3xAPP and ApoE4xAPP mouse brains. When the mice aged to 78 weeks, these proteins were markedly reduced in APP and ApoE4xAPP mouse brains. While Aβ can bind to insulin receptor, how ApoE isoforms modulate this interaction remains unknown. Here, we showed that ApoE3 had greater association with insulin receptor as compared to ApoE4, regardless of Aβ42 concentration. In contrast, ApoE4 bound more Aβ42 with increasing peptide levels. Using primary hippocampal neurons, we showed that ApoE3 and ApoE4 neurons are equally sensitive to physiological levels of insulin. However, in the presence of Aβ42, insulin failed to elicit a downstream response only in ApoE4 hippocampal neurons. Taken together, our data show that ApoE genotypes can modulate this Aβ-mediated insulin signaling impairment.

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

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Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new

Movement coordination in applied human-human and human-robot interaction

DEFF Research Database (Denmark)

Schubö, Anna; Vesper, Cordula; Wiesbeck, Mathey

2007-01-01

and describing human-human interaction in terms of goal-oriented movement coordination is considered an important and necessary step for designing and describing human-robot interaction. In the present scenario, trajectories of hand and finger movements were recorded while two human participants performed......The present paper describes a scenario for examining mechanisms of movement coordination in humans and robots. It is assumed that coordination can best be achieved when behavioral rules that shape movement execution in humans are also considered for human-robot interaction. Investigating...... coordination were affected. Implications for human-robot interaction are discussed....

Gains of ubiquitylation sites in highly conserved proteins in the human lineage

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Kim Dong Seon

2012-11-01

Full Text Available Abstract Background Post-translational modification of lysine residues of specific proteins by ubiquitin modulates the degradation, localization, and activity of these target proteins. Here, we identified gains of ubiquitylation sites in highly conserved regions of human proteins that occurred during human evolution. Results We analyzed human ubiquitylation site data and multiple alignments of orthologous mammalian proteins including those from humans, primates, other placental mammals, opossum, and platypus. In our analysis, we identified 281 ubiquitylation sites in 252 proteins that first appeared along the human lineage during primate evolution: one protein had four novel sites; four proteins had three sites each; 18 proteins had two sites each; and the remaining 229 proteins had one site each. PML, which is involved in neurodevelopment and neurodegeneration, acquired three sites, two of which have been reported to be involved in the degradation of PML. Thirteen human proteins, including ERCC2 (also known as XPD and NBR1, gained human-specific ubiquitylated lysines after the human-chimpanzee divergence. ERCC2 has a Lys/Gln polymorphism, the derived (major allele of which confers enhanced DNA repair capacity and reduced cancer risk compared with the ancestral (minor allele. NBR1 and eight other proteins that are involved in the human autophagy protein interaction network gained a novel ubiquitylation site. Conclusions The gain of novel ubiquitylation sites could be involved in the evolution of protein degradation and other regulatory networks. Although gains of ubiquitylation sites do not necessarily equate to adaptive evolution, they are useful candidates for molecular functional analyses to identify novel advantageous genetic modifications and innovative phenotypes acquired during human evolution.

Intercellular protein-protein interactions at synapses.

Science.gov (United States)

Yang, Xiaofei; Hou, Dongmei; Jiang, Wei; Zhang, Chen

2014-06-01

Chemical synapses are asymmetric intercellular junctions through which neurons send nerve impulses to communicate with other neurons or excitable cells. The appropriate formation of synapses, both spatially and temporally, is essential for brain function and depends on the intercellular protein-protein interactions of cell adhesion molecules (CAMs) at synaptic clefts. The CAM proteins link pre- and post-synaptic sites, and play essential roles in promoting synapse formation and maturation, maintaining synapse number and type, accumulating neurotransmitter receptors and ion channels, controlling neuronal differentiation, and even regulating synaptic plasticity directly. Alteration of the interactions of CAMs leads to structural and functional impairments, which results in many neurological disorders, such as autism, Alzheimer's disease and schizophrenia. Therefore, it is crucial to understand the functions of CAMs during development and in the mature neural system, as well as in the pathogenesis of some neurological disorders. Here, we review the function of the major classes of CAMs, and how dysfunction of CAMs relates to several neurological disorders.

Mitochondrial nucleoid interacting proteins support mitochondrial protein synthesis.

Science.gov (United States)

He, J; Cooper, H M; Reyes, A; Di Re, M; Sembongi, H; Litwin, T R; Gao, J; Neuman, K C; Fearnley, I M; Spinazzola, A; Walker, J E; Holt, I J

2012-07-01

Mitochondrial ribosomes and translation factors co-purify with mitochondrial nucleoids of human cells, based on affinity protein purification of tagged mitochondrial DNA binding proteins. Among the most frequently identified proteins were ATAD3 and prohibitin, which have been identified previously as nucleoid components, using a variety of methods. Both proteins are demonstrated to be required for mitochondrial protein synthesis in human cultured cells, and the major binding partner of ATAD3 is the mitochondrial ribosome. Altered ATAD3 expression also perturbs mtDNA maintenance and replication. These findings suggest an intimate association between nucleoids and the machinery of protein synthesis in mitochondria. ATAD3 and prohibitin are tightly associated with the mitochondrial membranes and so we propose that they support nucleic acid complexes at the inner membrane of the mitochondrion.

Phthalic Acid Chemical Probes Synthesized for Protein-Protein Interaction Analysis

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Chin-Jen Wu

2013-06-01

Full Text Available Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP. According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES was deposited on silicon dioxides (SiO2 particles and phthalate chemical probes were manufactured from phthalic acid and APTES–SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

Human mammary progenitor cell fate decisions are products of interactions with combinatorial microenvironments

Energy Technology Data Exchange (ETDEWEB)

LaBarge, Mark A; Nelson, Celeste M; Villadsen, Rene; Fridriksdottir, Agla; Ruth, Jason R; Stampfer, Martha R; Petersen, Ole W; Bissell, Mina J

2008-09-19

In adult tissues, multi-potent progenitor cells are some of the most primitive members of the developmental hierarchies that maintain homeostasis. That progenitors and their more mature progeny share identical genomes, suggests that fate decisions are directed by interactions with extrinsic soluble factors, ECM, and other cells, as well as physical properties of the ECM. To understand regulation of fate decisions, therefore, would require a means of understanding carefully choreographed combinatorial interactions. Here we used microenvironment protein microarrays to functionally identify combinations of cell-extrinsic mammary gland proteins and ECM molecules that imposed specific cell fates on bipotent human mammary progenitor cells. Micropatterned cell culture surfaces were fabricated to distinguish between the instructive effects of cell-cell versus cell-ECM interactions, as well as constellations of signaling molecules; and these were used in conjunction with physiologically relevant 3 dimensional human breast cultures. Both immortalized and primary human breast progenitors were analyzed. We report on the functional ability of those proteins of the mammary gland that maintain quiescence, maintain the progenitor state, and guide progenitor differentiation towards myoepithelial and luminal lineages.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

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Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

Science.gov (United States)

Gowthaman, Ragul; Miller, Sven A; Rogers, Steven; Khowsathit, Jittasak; Lan, Lan; Bai, Nan; Johnson, David K; Liu, Chunjing; Xu, Liang; Anbanandam, Asokan; Aubé, Jeffrey; Roy, Anuradha; Karanicolas, John

2016-05-12

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

Evidence of probabilistic behaviour in protein interaction networks

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Reifman Jaques

2008-01-01

Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

Characterization of the Zebrafish Homolog of Zipper Interacting Protein Kinase

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Brandon W. Carr

2014-06-01

Full Text Available Zipper-interacting protein kinase (ZIPK is a conserved vertebrate-specific regulator of actomyosin contractility in smooth muscle and non-muscle cells. Murine ZIPK has undergone an unusual divergence in sequence and regulation compared to other ZIPK orthologs. In humans, subcellular localization is controlled by phosphorylation of threonines 299 and 300. In contrast, ZIPK subcellular localization in mouse and rat is controlled by interaction with PAR-4. We carried out a comparative biochemical characterization of the regulation of the zebrafish ortholog of ZIPK. Like the human orthologs zebrafish ZIPK undergoes nucleocytoplasmic-shuttling and is abundant in the cytoplasm, unlike the primarily nuclear rat ZIPK. Rat ZIPK, but not human or zebrafish ZIPK, interacts with zebrafish PAR-4. Mutation of the conserved residues required for activation of the mammalian orthologs abrogated activity of the zebrafish ZIPK. In contrast to the human ortholog, mutation of threonine 299 and 300 in the zebrafish ZIPK has no effect on the activity or subcellular localization. Thus, we found that zebrafish ZIPK functions in a manner most similar to the human ZIPK and quite distinct from murine orthologs, yet the regulation of subcellular localization is not conserved.

Human sperm degradation of zona pellucida proteins contributes to fertilization.

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Saldívar-Hernández, Analilia; González-González, María E; Sánchez-Tusié, Ana; Maldonado-Rosas, Israel; López, Pablo; Treviño, Claudia L; Larrea, Fernando; Chirinos, Mayel

2015-09-02

The mammalian oocyte extracellular matrix known as the zona pellucida (ZP) acts as a barrier to accomplish sperm fusion with the female gamete. Although penetration of the ZP is a limiting event to achieve fertilization, this is one of the least comprehended stages of gamete interaction. Even though previous studies suggest that proteases of sperm origin contribute to facilitate the passage of sperm through the ZP, in human this process is not yet fully understood. The aim of this study was to determine the ability of human sperm to degrade recombinant human ZP (rhZPs) proteins and to characterize the proteases involved in this process. Purified rhZP2, rhZP3 and rhZP4 proteins were incubated with capacitated sperm and the proteolytic activity was determined by Western blot analysis. To further characterize the proteases involved, parallel incubations were performed in the presence of the protease inhibitors o-phenanthroline, benzamidine and MG-132 meant to block the activity of metalloproteases, serine proteases and the proteasome, respectively. Additionally, protease inhibitors effect on sperm-ZP binding was evaluated by hemizona assay. The results showed that rhZPs were hydrolyzed in the presence of capacitated sperm. O-phenanthroline inhibited the degradation of rhZP3, MG-132 inhibited the degradation of rhZP4 and benzamidine inhibited the degradation of the three proteins under investigation. Moreover, hemizona assays demonstrated that sperm proteasome inhibition impairs sperm interaction with human native ZP. This study suggests that sperm proteasomes could participate in the degradation of ZP, particularly of the ZP4 protein. Besides, metalloproteases may be involved in specific degradation of ZP3 while serine proteases may contribute to unspecific degradation of the ZP. These findings suggest that localized degradation of ZP proteins by sperm is probably involved in ZP penetration and may be of help in understanding the mechanisms of fertilization in humans.

Interaction of molybdenum with blood serum proteins in vitro

International Nuclear Information System (INIS)

Bibr, B.; Kselikova, M.; Lener, J.

1985-01-01

The interaction of pentavalent and hexavalent 99 Mo compounds with rat and human serum was monitored in vitro by paper electrophoresis after incubation for one hour at 37 0 C. Hexavalent 99 Mo is not capable of interaction and, via sulfur ligands, forms unstable and unspecific bonds to the whole spectrum of serum proteins, in particular to albumin. Pentavalent 99 Mo binds strongly to alpha-2-macroglobulin in a ratio of 2 : 1; according to the nature of the ligand, it forms somewhat unstable bonds to albumin, beta-1-globulin and gamma-2-globulin. (author)

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

Science.gov (United States)

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Comprehensive analysis of interactions between the Src-associated protein in mitosis of 68 kDa and the human Src-homology 3 proteome.

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Benedikt Asbach

Full Text Available The protein Sam68 is involved in many cellular processes such as cell-cycle regulation, RNA metabolism, or signal transduction. Sam68 comprises a central RNA-binding domain flanked by unstructured tails containing docking sites for signalling proteins including seven proline-rich sequences (denoted P0 to P6 as potential SH3-domain binding motifs. To comprehensively assess Sam68-SH3-interactions, we applied a phage-display screening of a library containing all approx. 300 human SH3 domains. Thereby we identified five new (from intersectin 2, the osteoclast stimulating factor OSF, nephrocystin, sorting nexin 9, and CIN85 and seven already known high-confidence Sam68-ligands (mainly from the Src-kinase family, as well as several lower-affinity binders. Interaction of the high-affinity Sam68-binders was confirmed in independent assays in vitro (phage-ELISA, GST-pull-down and in vivo (FACS-based FRET-analysis with CFP- and YFP-tagged proteins. Fine-mapping analyses with peptides established P0, P3, P4, and P5 as exclusive docking-sites for SH3 domains, which showed varying preferences for these motifs. Mutational analyses identified individual residues within the proline-rich motifs being crucial for the interactions. Based on these data, we generated a Sam68-mutant incapable of interacting with SH3 domains any more, as subsequently demonstrated by FRET-analyses. In conclusion, we present a thorough characterization of Sam68's interplay with the SH3 proteome. The observed interaction between Sam68 and OSF complements the known Sam68-Src and OSF-Src interactions. Thus, we propose, that Sam68 functions as a classical scaffold protein in this context, assembling components of an osteoclast-specific signalling pathway.

NatalieQ: A web server for protein-protein interaction network querying

NARCIS (Netherlands)

El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

2014-01-01

Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

Identification of host cell proteins which interact with herpes simplex virus type 1 tegument protein pUL37.

Science.gov (United States)

Kelly, Barbara J; Diefenbach, Eve; Fraefel, Cornel; Diefenbach, Russell J

2012-01-20

The herpes simplex virus type 1 (HSV-1) structural tegument protein pUL37, which is conserved across the Herpesviridae family, is known to be essential for secondary envelopment during the egress of viral particles. To shed light on additional roles of pUL37 during viral replication a yeast two-hybrid screen of a human brain cDNA library was undertaken. This screen identified ten host cell proteins as potential pUL37 interactors. One of the interactors, serine threonine kinase TAOK3, was subsequently confirmed to interact with pUL37 using an in vitro pulldown assay. Such host cell/pUL37 interactions provide further insights into the multifunctional role of this herpesviral tegument protein. Copyright © 2011 Elsevier Inc. All rights reserved.

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

Science.gov (United States)

Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

Biophysical characterization of the complex between human papillomavirus E6 protein and synapse-associated protein 97

DEFF Research Database (Denmark)

Chi, Celestine Ngang; Bach, Anders; Engström, Åke

2011-01-01

The E6 protein of human papillomavirus exhibits complex interaction patterns with several host proteins and their roles in HPV mediated oncogenesis have proved challenging to study. Here we use several biophysical techniques to explore the binding of E6 to the three PDZ domains of the tumor......, this quaternary complex has the same apparent hydrodynamic volume as the unliganded PDZ region, suggesting that a conformational change occurs in the PDZ region upon binding, a conclusion supported by kinetic experiments. Using NMR, we discovered a new mode of interaction between E6 and PDZ: a subset of residues...

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

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Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

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Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells

Full Data of Yeast Interacting Proteins Database (Original Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Yeast Interacting Proteins Database Full Data of Yeast Interacting Proteins Database (Origin...al Version) Data detail Data name Full Data of Yeast Interacting Proteins Database (Original Version) DOI 10....18908/lsdba.nbdc00742-004 Description of data contents The entire data in the Yeast Interacting Proteins Database...eir interactions are required. Several sources including YPD (Yeast Proteome Database, Costanzo, M. C., Hoga...ematic name in the SGD (Saccharomyces Genome Database; http://www.yeastgenome.org /). Bait gene name The gen

From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

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Mu Gao

2009-03-01

Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

Yeast Interacting Proteins Database: YGL127C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ith protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regula...rotein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

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Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

Interaction between holo transferrin and HSA-PPIX complex in the presence of lomefloxacin: An evaluation of PPIX aggregation in protein-protein interactions

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Sattar, Zohreh; Iranfar, Hediye; Asoodeh, Ahmad; Saberi, Mohammad Reza; Mazhari, Mahboobeh; Chamani, Jamshidkhan

2012-11-01

Human serum albumin (HSA) and holo transferrin (TF) are two serum carrier proteins that are able to interact with each other, thereby altering their binding behavior toward their ligands. During the course of this study, the interaction between HSA-PPIX and TF, in the presence and absence of lomefloxacin (LMF), was for the first time investigated using different spectroscopic and molecular modeling techniques. Fluorescence spectroscopy experiments were performed in order to study conformational changes of proteins. The RLS technique was utilized to investigate the effect of LMF on J-aggregation of PPIX, which is the first report of its kind. Our findings present clear-cut evidence for the alteration of interactions between HSA and TF in the presence of PPIX and changes in drug-binding to HSA and HSA-PPIX complex upon interaction with TF. Moreover, molecular modeling studies suggested that the binding site for LMF became switched in the presence of PPIX, and that LMF bound to the site IIA of HSA. The obtained results should give new insight into research in this field and may cast some light on the dynamics of drugs in biological systems.

Rescuing the Rescuer: On the Protein Complex between the Human Mitochondrial Acyl Carrier Protein and ISD11.

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Herrera, María Georgina; Pignataro, María Florencia; Noguera, Martín Ezequiel; Cruz, Karen Magalí; Santos, Javier

2018-05-16

Iron-sulfur clusters are essential cofactors in many biochemical processes. ISD11, one of the subunits of the protein complex that carries out the cluster assembly in mitochondria, is necessary for cysteine desulfurase NFS1 stability and function. Several authors have recently provided evidence showing that ISD11 interacts with the acyl carrier protein (ACP). We carried out the coexpression of human mitochondrial ACP and ISD11 in E. coli. This work shows that ACP and ISD11 form a soluble, structured, and stable complex able to bind to the human NFS1 subunit modulating its activity. Results suggest that ACP plays a key-role in ISD11 folding and stability in vitro. These findings offer the opportunity to study the mechanism of interaction between ISD11 and NFS1.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

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Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365