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Results for “Protein Interaction Mapping”

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At least 19 recordsLinked to original sources
PubMed2001

Towards a protein interaction map of potyviruses: protein interaction matrixes of two potyviruses based on the yeast two-hybrid system.

A map for the interactions of the major proteins from Potato virus A (PVA) and Pea seed-borne mosaic virus (PSbMV) (members of the genus POTYVIRUS:, family POTYVIRIDAE:) was generated using the yeast two-hybrid system (YTHS). Interactions were readily detected with five PVA protein combinations (HC-HC, HC-CI, VPg-VPg, NIa-NIb and CP-CP) and weak but reproducible interactions were detected for seven additional combinations (P1-CI, P3-NIb, NIaPro-NIb, VPg-NIa, VPg-NIaPro, NIaPro-NIa and NIa-NIa). In PSbMV, readily detectable interactions were found in five protein combinations (HC-HC, VPg-VPg, VPg-NIa, NIa-NIa and NIa-NIb) and weaker but reproducible interactions were detected for three additional combinations (P3-NIa, NIa-NIaPro and CP-CP). The self-interactions of HC, VPg, NIa and CP and the interactions of VPg-NIa, NIa-NIaPro and NIa-NIb were, therefore, common for the two potyviruses. The multiple protein interactions revealed in this study shed light on the co-ordinated functions of potyviral proteins involved in virus movement and replication.

Hybridization, Genetic↗
PubMed2001

High-throughput yeast two-hybrid assays for large-scale protein interaction mapping.

Protein-protein interactions play fundamental roles in many biological processes. Hence, protein interaction mapping is becoming a well-established functional genomics approach to generate functional annotations for predicted proteins that so far have remained uncharacterized. The yeast two-hybrid system is currently one of the most standardized protein interaction mapping techniques. Here, we describe the protocols for a semiautomated, high-throughput, Gal4-based yeast two-hybrid system.

Culture Media↗
PubMed2000

Progress and potential of Drosophila protein interaction maps.

Protein-protein interactions mediate many important cellular processes and are central to the mechanisms by which most proteins function. Charting the interactions among the proteins involved in a process has been an essential step in characterising the function of proteins and pathways. The yeast two-hybrid system is one approach to detecting protein interactions that can now be scaled-up to assay large sets of proteins systematically, such as those being identified from genome sequencing efforts. The system has already been extensively used to acquire data that have enabled construction of large protein interaction maps (PIMs). When combined with other data, including data being generated by other functional genomics approaches, PIMs help assign function to new proteins and delineate functional networks. Hypotheses generated in such a manner often must be tested by additional experimentation, preferably in vivo. The model organism Drosophila melanogaster has a wealth of genetic and bioinformatic tools available for such analyses. The proteome predicted from the recently sequenced Drosophila genome indicates that humans have more genes in common with Drosophila than with any other invertebrate model organism characterised to date. Thus, the construction and characterisation of Drosophila PIMs will help define the functions of many conserved genes and pathways, and will provide the pharmaceutical research industry with invaluable data to assist with drug target identification and validation.

Animals↗
PubMed2004

A first-draft human protein-interaction map.

BACKGROUND: Protein-interaction maps are powerful tools for suggesting the cellular functions of genes. Although large-scale protein-interaction maps have been generated for several invertebrate species, projects of a similar scale have not yet been described for any mammal. Because many physical interactions are conserved between species, it should be possible to infer information about human protein interactions (and hence protein function) using model organism protein-interaction datasets. RESULTS: Here we describe a network of over 70,000 predicted physical interactions between around 6,200 human proteins generated using the data from lower eukaryotic protein-interaction maps. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share the same functional annotations, and we show how the network can be used to successfully predict the functions of human proteins. We find that combining interaction datasets from a single organism (but generated using independent assays) and combining interaction datasets from two organisms (but generated using the same assay) are both very effective ways of further improving the accuracy of protein-interaction maps. CONCLUSIONS: The complete network predicts interactions for a third of human genes, including 448 human disease genes and 1,482 genes of unknown function, and so provides a rich framework for biomedical research.

Databases, Protein↗
PubMed2003

Novel approaches to map protein interactions.

Although we now have the sequence of the human genome at hand, we face the challenge of assigning function to the identified genes. Genes usually ascribe their function through proteins, and the role of proteins is to interact with other molecules. Therefore, if we could map the interactions of proteins we would be able to understand protein function. The challenge of mapping protein interactions is vast and many novel approaches have recently been developed for this task using molecular biology, mass spectrometry and chemiproteomic techniques.

Carbohydrate Metabolism↗
PubMed2000

Protein interaction mapping in C. elegans using proteins involved in vulval development.

Protein interaction mapping using large-scale two-hybrid analysis has been proposed as a way to functionally annotate large numbers of uncharacterized proteins predicted by complete genome sequences. This approach was examined in Caenorhabditis elegans, starting with 27 proteins involved in vulval development. The resulting map reveals both known and new potential interactions and provides a functional annotation for approximately 100 uncharacterized gene products. A protein interaction mapping project is now feasible for C. elegans on a genome-wide scale and should contribute to the understanding of molecular mechanisms in this organism and in human diseases.

Animals↗
PubMed2001

Protein-protein interaction map inference using interacting domain profile pairs.

UNLABELLED: A number of predictive methods have been designed to predict protein interaction from sequence or expression data. On the experimental front, however, high-throughput proteomics technologies are starting to yield large volumes of protein-protein interaction data. High-quality experimental protein interaction maps constitute the natural dataset upon which to build interaction predictions. Thus the motivation to develop the first interaction-based protein interaction map prediction algorithm. A technique to predict protein-protein interaction maps across organisms is introduced, the 'interaction-domain pair profile' method. The method uses a high-quality protein interaction map with interaction domain information as input to predict an interaction map in another organism. It combines sequence similarity searches with clustering based on interaction patterns and interaction domain information. We apply this approach to the prediction of an interaction map of Escherichia coli from the recently published interaction map of the human gastric pathogen Helicobacter pylori. Results are compared with predictions of a second inference method based only on full-length protein sequence similarity - the "naive" method. The domain-based method is shown to i) eliminate a significant amount of false-positives of the naive method that are the consequences of multi-domain proteins; ii) increase the sensitivity compared to the naive method by identifying new potential interactions. AVAILABILITY: Contact the authors.

Algorithms↗
PubMed2026

SARS-CoV-2 Orf3a protein interaction mapping using unnatural amino acid incorporation.

Mapping transient protein-protein interactions remain a major challenge in studying viral host-pathogen interfaces. While some virus-host interactions are stable and readily captured, the majority are highly dynamic, reflecting the need for viral proteins to engage distinct host factors at different stages of the life cycle. Here, we employ a protein engineering strategy based on the site-specific incorporation of the unnatural acid p-azido-L-phenylalanine (AzF) to enable photo-crosslinking proteomic analysis of the SARS-CoV-2 accessory protein Orf3a in live cells. Genetic installation of AzF at residue K198 of Orf3a permitted UV-induced covalent capture of proximal host interacting proteins, overcoming challenges associated with membrane localization and limited protein abundance. A total of 248 high-confidence Orf3a-interacting proteins were reproducibly identified and subjected to gene ontology analysis, revealing enrichment in innate immune signaling, antiviral defense, RNA processing, and viral replication-associated pathways. Orf3a is an accessory protein that functions as a viroporin and traffics across multiple cellular compartments, and was found to interact with host RNA helicases, RNA-binding proteins, immune regulators, and metabolic enzymes implicated in SARS-CoV-2 infection. Together, these results demonstrate that genetically encoded, site-specific photo-crosslinking enables selective capture of transient interactions that are often missed by nonspecific 254 nm UV crosslinking approaches and highlights Orf3a as a multifunctional protein that engages diverse host pathways. More broadly, this study establishes a generalizable framework for leveraging unnatural amino acid-based protein engineering approaches to interrogate dynamic host-pathogen interactions.

Humans↗
PubMed2001

Use of protein-interaction maps to formulate biological questions.

Protein-interaction mapping approaches generate functional information for large numbers of genes that are predicted from complete genome sequences. This information, released as databases available on the Internet, is likely to transform the way biologists formulate and then address their questions of interest.

Animals↗
PubMed2005

Protein-protein interaction map of the Trypanosoma cruzi ribosomal P protein complex.

The large subunit of the eukaryotic ribosome possesses a long and protruding stalk formed by the ribosomal P proteins. Four out of five ribosomal P proteins of Trypanosoma cruzi, TcP0, TcP1alpha, TcP2alpha, and TcP2beta had been previously characterized. Data mining of the T. cruzi genome data base allowed the identification of the fifth member of this protein group, a novel P1 protein, named P1beta. To gain insight into the assembly of the stalk, a yeast two-hybrid based protein interaction map was generated. A parasite specific profile of interactions amongst the ribosomal P proteins of T. cruzi was evident. The TcP0 protein was able to interact with all both P1 and both P2 proteins. Moreover, the interactions between P2beta with P1alpha as well as with P2alpha were detected, as well as the ability of TcP2beta to homodimerize. A quantitative evaluation of the interactions established that the strongest interacting pair was TcP0-TcP1beta.

Amino Acid Sequence↗
PubMed2004

Protein interaction mapping on a functional shotgun sequence of Rickettsia sibirica.

Protein interaction maps can reveal novel pathways and functional complexes, allowing 'guilt by association' annotation of uncharacterized proteins. To address the need for large-scale protein interaction analyses, a bacterial two-hybrid system was coupled with a whole genome shotgun sequencing approach for microbial genome analysis. We report the first large-scale proteomics study using this system, integrating de novo genome sequencing with functional interaction mapping and annotation in a high-throughput format. We apply the approach by shotgun sequencing and annotating the genome of Rickettsia sibirica strain 246, an obligate intracellular human pathogen among the Spotted Fever Group rickettsiae. The bacteria invade endothelial cells and cause lysis after large amounts of progeny have accumulated. Little is known about specific Rickettsial virulence factors and their mode of pathogenicity. Analysis of the combined genomic sequence and protein-protein interaction data for a set of virulence related Type IV secretion system (T4SS) proteins revealed over 250 interactions and will provide insight into the mechanism of Rickettsial pathogenicity.

Bacterial Proteins↗
PubMed2003

A strategy for constructing large protein interaction maps using the yeast two-hybrid system: regulated expression arrays and two-phase mating.

Maps representing the binary interactions among proteins have become valuable tools for understanding how proteins work together to mediate biological processes. One of the most effective methods for detecting biologically important protein interactions has been the yeast two-hybrid system. Here we present an efficient two-hybrid strategy to facilitate construction of protein interaction maps on a genome-wide scale. The strategy begins with two arrays of yeast expressing known proteins fused to either a DNA binding domain (BD), or a transcription activation domain (AD). The fusion proteins are conditionally expressed using regulated promoters that can be repressed during construction and amplification of the yeast arrays. Interaction assays are conducted in two phases. In the first phase, small pools of AD strains are mated with the array of BD strains. In the second phase, individual BD strains are mated with appropriate subsets of the AD array corresponding to positive pools in the first phase. This strategy has several advantages over previously described approaches, including the ability to detect interactions with proteins that inhibit yeast growth or that activate transcription as BD fusions. Moreover, by minimizing the number of mating operations and sequencing reactions needed to test large sets of binary interactions, this strategy is more efficient than either matrix or library screening approaches. We also present a three-dimensional pooling scheme to further increase the efficiency of large-scale two-hybrid analyses.

DNA-Binding Proteins↗
PubMed2002

Protein interaction mapping for target validation: the need for an integrated combinatory process involving complementary approaches.

Identification, selection, validation and prioritization of targets for therapeutic intervention requires understanding of the biological role of individual proteins in cellular pathways. Unraveling the ways in which proteins interact with each other appears to be crucial in achieving that goal. A number of recently described high-throughput approaches for analyzing cellular protein-protein interactions and previously proposed prediction procedures are compared in this review. The relative advantages of each method are discussed in relation to reproducibility, comprehensiveness and biological significance. It is concluded that only a combination of complementary biochemical technologies supported by reliable algorithms, will provide exhaustive maps of protein interactions for a cellular interactome.

Animals↗
PubMed2026

Library-based, multiplexed strategy for mapping protein interaction networks via crosslinking.

BACKGROUND: Protein-protein interactions are fundamental to cellular function, yet resolving their interaction interfaces and dynamic behaviors in native biological contexts remains challenging, particularly for weak or transient interactions. Crosslinking strategies based on noncanonical amino acids offer an effective means to capture such interactions; however, traditional single-site incorporation provides limited coverage and may overlook critical interaction hotspots. RESULTS: By employing a mutagenesis library, multiple interaction partners and cross-linking sites of a target protein can be simultaneously screened in a single experiment, without prior knowledge of its precise structural or functional features, enabling effective and unbiased analysis of its interaction network. In this study, we constructed an amber codon-scanning mutagenesis library of PSMD10, facilitating independent incorporation of the photocrosslinking ncAA p-azido-phenylalanine at multiple distinct residues. This approach allowed us to systematically interrogate and precisely map potential interaction regions across the protein surface. Coupled with crosslinking mass spectrometry, we identified multiple residues involved in intermolecular interactions, as well as previously unreported interaction partners, including T2FA, TBA1C, and ATRIP. CONCLUSIONS: These findings expand our understanding of PSMD10-associated proteasome interactome, demonstrate a multiplexed strategy for in situ mapping of protein interaction interfaces with broad coverage, and offer a valuable platform for developing therapeutics that target protein-protein interactions.

Protein Interaction Mapping↗
PubMed2004

A Drosophila protein-interaction map centered on cell-cycle regulators.

BACKGROUND: Maps depicting binary interactions between proteins can be powerful starting points for understanding biological systems. A proven technology for generating such maps is high-throughput yeast two-hybrid screening. In the most extensive screen to date, a Gal4-based two-hybrid system was used recently to detect over 20,000 interactions among Drosophila proteins. Although these data are a valuable resource for insights into protein networks, they cover only a fraction of the expected number of interactions. RESULTS: To complement the Gal4-based interaction data, we used the same set of Drosophila open reading frames to construct arrays for a LexA-based two-hybrid system. We screened the arrays using a novel pooled mating approach, initially focusing on proteins related to cell-cycle regulators. We detected 1,814 reproducible interactions among 488 proteins. The map includes a large number of novel interactions with potential biological significance. Informative regions of the map could be highlighted by searching for paralogous interactions and by clustering proteins on the basis of their interaction profiles. Surprisingly, only 28 interactions were found in common between the LexA- and Gal4-based screens, even though they had similar rates of true positives. CONCLUSIONS: The substantial number of new interactions discovered here supports the conclusion that previous interaction mapping studies were far from complete and that many more interactions remain to be found. Our results indicate that different two-hybrid systems and screening approaches applied to the same proteome can generate more comprehensive datasets with more cross-validated interactions. The cell-cycle map provides a guide for further defining important regulatory networks in Drosophila and other organisms.

Animals↗
PubMed2003

A protein interaction map of Drosophila melanogaster.

Drosophila melanogaster is a proven model system for many aspects of human biology. Here we present a two-hybrid-based protein-interaction map of the fly proteome. A total of 10,623 predicted transcripts were isolated and screened against standard and normalized complementary DNA libraries to produce a draft map of 7048 proteins and 20,405 interactions. A computational method of rating two-hybrid interaction confidence was developed to refine this draft map to a higher confidence map of 4679 proteins and 4780 interactions. Statistical modeling of the network showed two levels of organization: a short-range organization, presumably corresponding to multiprotein complexes, and a more global organization, presumably corresponding to intercomplex connections. The network recapitulated known pathways, extended pathways, and uncovered previously unknown pathway components. This map serves as a starting point for a systems biology modeling of multicellular organisms, including humans.

Animals↗
PubMed2004

Expansion of protein interaction maps by phage peptide display using MDM2 as a prototypical conformationally flexible target protein.

Expanding on the possible protein interaction partners in a biochemical pathway is one key molecular goal in the post-genomic era. Phage peptide display is a versatile in vitro tool for mapping novel protein-protein interfaces and the advantage of this technique in expanding protein interaction maps is that in vitro manipulation of the bait protein conformational integrity can be controlled carefully. Phage peptide display was used to expand on the possible types of binding proteins for the conformationally responsive protein MDM2. Peptides enriched differ depending upon whether MDM2 is ligand-free, zinc-bound, or RNA-bound, suggesting that MDM2 conformational changes alter the type of peptide ligands enriched. Classes of putative/established MDM2-binding proteins identified by this technique included ubiquitin-modifying enzymes (F-box proteins, UB-ligases, UBC-E1) and apoptotic modifiers (HSP90, GAS1, APAF1, p53). Of the many putative MDM2 proteins that could be examined, the impact of HSP90 on MDM2 activity was studied, since HSP90 has been linked with p53 protein unfolding in human cancers. Zinc ions were required to reconstitute a stable MDM2-HSP90 protein complex. Zinc binding converted MDM2 from a monomer to an oligomer, and activated MDM2 binding to its internal RING finger domain, providing evidence for a conformational change in MDM2 protein when it binds zinc. Reconstitution of an HSP90-MDM2 protein complex in vitro stimulated the unfolding of the p53 tetramer. A p53 DNA-binding inhibitor purified from human cells that is capable of unfolding p53 at ambient temperature in vitro contains co-purifying pools of HSP90 and MDM2. These data highlight the utility of phage peptide display as a powerful in vitro method to identify regulatory proteins that bind to a conformationally flexible protein like MDM2.

Amino Acid Sequence↗
PubMed2002

Functional proteomics: mapping protein-protein interactions and pathways.

The function of a protein is defined by its interactions with other proteins and molecules. Mapping of protein interactions can highlight new functionalities for a known protein or can even define the function of novel proteins. With the draft sequence of the human genome now available, it is possible to perform high-throughput mapping of protein-protein interactions in humans, which is termed as functional proteomics. The developments in functional proteomics are particularly timely since pharmaceutical companies are searching for technologies that will strengthen their genomic efforts and prioritize their drug discovery pipeline. In this article we review recent developments in functional proteomics.

Drug Design↗