scholarly journals High resolution protein-protein interaction mapping using all-versus-all sequencing (AVA-seq)

2018 ◽  
Author(s):  
Simeon S. Andrews ◽  
Stephanie Schaefer-Ramadan ◽  
Nayra M. Al-Thani ◽  
Ikhlak Ahmed ◽  
Yasmin A. Mohamoud ◽  
...  
Keyword(s):  
High Resolution ◽  
Hybrid Systems ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Large Scale ◽  
Specific Protein ◽  
Next Generation ◽  
Protein Protein Interaction ◽  
Contact Points ◽  
Two Hybrid

AbstractTwo-hybrid systems test for protein-protein interactions and can provide important information for genes with unknown function. Despite their success, two-hybrid systems have remained mostly untouched by improvements from next-generation DNA sequencing. Here we present a method for all-versus-all protein interaction mapping (AVA-seq) that utilizes next-generation sequencing to remove multiple bottlenecks of the two-hybrid process. The method allows for high resolution protein-protein interaction mapping of a small set of proteins, or the potential for lower-resolution mapping of entire proteomes. Features of the system include open-reading frame selection to improve efficiency, high bacterial transformation efficiency, a convergent fusion vector to allow paired-end sequencing of interactors, and the use of protein fragments rather than full-length genes to better resolve specific protein contact points. We demonstrate the system’s strengths and limitations on a set of proteins known to interact in humans and provide a framework for future large-scale projects.

scholarly journals Yeast Two-Hybrid Systems and Protein Interaction Mapping Projects for Yeast and Worm

Yeast ◽  
2000 ◽  
Vol 1 (2) ◽  
pp. 88-94 ◽  
Author(s):  
Albertha J. M. Walhout ◽  
Simon J. Boulton ◽  
Marc Vidal
Keyword(s):  
Hybrid Systems ◽  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Large Scale ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Systematic Analysis ◽  
Technical Features ◽  
Two Hybrid

The availability of complete genome sequences necessitates the development of standardized functional assays to analyse the tens of thousands of predicted gene products in high-throughput experimental settings. Such approaches are collectively referred to as ‘functional genomics’. One approach to investigate the properties of a proteome of interest is by systematic analysis of protein–protein interactions. So far, the yeast two-hybrid system is the most commonly used method for large-scale, high-throughput identification of potential protein–protein interactions. Here, we discuss several technical features of variants of the two-hybrid systems in light of data recently obtained from different protein interaction mapping projects for the budding yeastSaccharomyces cerevisiaeand the nematodeCaenorhabditis elegans.

scholarly journals Yeast Two-Hybrid Systems and Protein Interaction Mapping Projects for Yeast and Worm

Yeast ◽  
2000 ◽  
Vol 1 (2) ◽  
pp. 88-94 ◽  
Author(s):  
Albertha J. M. Walhout ◽  
Simon J. Boulton ◽  
Marc Vidal
Keyword(s):  
Hybrid Systems ◽  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Large Scale ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Systematic Analysis ◽  
Technical Features ◽  
Two Hybrid

The availability of complete genome sequences necessitates the development of standardized functional assays to analyse the tens of thousands of predicted gene products in high-throughput experimental settings. Such approaches are collectively referred to as ‘functional genomics’. One approach to investigate the properties of a proteome of interest is by systematic analysis of protein–protein interactions. So far, the yeast two-hybrid system is the most commonly used method for large-scale, high-throughput identification of potential protein–protein interactions. Here, we discuss several technical features of variants of the two-hybrid systems in light of data recently obtained from different protein interaction mapping projects for the budding yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans.

scholarly journals Proximal Protein Interaction Landscape of RAS Paralogs

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3326 ◽  
Author(s):  
Benoît Béganton ◽  
Etienne Coyaud ◽  
Estelle M. N. Laurent ◽  
Alain Mangé ◽  
Julien Jacquemetton ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Biological Activities ◽  
Mammalian Species ◽  
Variable Region ◽  
Specific Protein ◽  
Protein Networks ◽  
Ras Proteins ◽  
Wild Type ◽  
Protein Protein Interaction

RAS proteins (KRAS, NRAS and HRAS) are frequently activated in different cancer types (e.g., non-small cell lung cancer, colorectal cancer, melanoma and bladder cancer). For many years, their activities were considered redundant due to their high degree of sequence homology (80% identity) and their shared upstream and downstream protein partners. However, the high conservation of the Hyper-Variable-Region across mammalian species, the preferential activation of different RAS proteins in specific tumor types and the specific post-translational modifications and plasma membrane-localization of each paralog suggest they could ensure discrete functions. To gain insights into RAS proteins specificities, we explored their proximal protein–protein interaction landscapes using the proximity-dependent biotin identification technology (BioID) in Flp-In T-REx 293 cell lines stably transfected and inducibly expressing wild type KRAS4B, NRAS or HRAS. We identified more than 800 high-confidence proximal interactors, allowing us to propose an unprecedented comparative analysis of wild type RAS paralogs protein networks. These data bring novel information on poorly characterized RAS functions, e.g., its putative involvement in metabolic pathways, and on shared as well as paralog-specific protein networks that could partially explain the complexity of RAS functions. These networks of protein interactions open numerous avenues to better understand RAS paralogs biological activities.

On the structure of protein–protein interaction networks

2003 ◽  
Vol 31 (6) ◽  
pp. 1491-1496 ◽  
Author(s):  
A. Thomas ◽  
R. Cannings ◽  
N.A.M. Monk ◽  
C. Cannings
Keyword(s):  
Power Law ◽  
Protein Interactions ◽  
Large Scale ◽  
Underlying Structure ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Protein Protein Interaction ◽  
Human Proteins ◽  
Approximate Power ◽  
Two Hybrid

We present a simple model for the underlying structure of protein–protein pairwise interaction graphs that is based on the way in which proteins attach to each other in experiments such as yeast two-hybrid assays. We show that data on the interactions of human proteins lend support to this model. The frequency of the number of connections per protein under this model does not follow a power law, in contrast to the reported behaviour of data from large-scale yeast two-hybrid screens of yeast protein–protein interactions. Sampling sub-graphs from the underlying graphs generated with our model, in a way analogous to the sampling performed in large-scale yeast two-hybrid searches, gives degree distributions that differ subtly from the power law and that fit the observed data better than the power law itself. Our results show that the observation of approximate power law behaviour in a sampled sub-graph does not imply that the underlying graph follows a power law.

scholarly journals A SURVEY ON DIFFERENT METHODS USED FOR ANALYSIS OF PROTEIN-PROTEIN INTERACTION NETWORK

2020 ◽  
pp. 446-452
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Large Scale ◽  
3D Structure ◽  
Interaction Network ◽  
Protein Detection ◽  
Human Interaction ◽  
Interaction Networks ◽  
Protein Protein Interaction ◽  
Advantages And Disadvantages

Bio information system is one of the prominent fields for analyzing of biological process. The main objective of Bioinformatics is to identify the disease and analysis the cause for disease. Protein- Protein Interactions (PPI) is used to analyze the structure of protein sequence and visualization in 3D structure. Many methodologies have been used to analysis the cancer causing protein detection using PPI network. Protein-Protein Interaction networks are used for the drug discovery for a particular disease in humans using protein interactions in Human Interaction Networks. There are many advantages and disadvantages while analyzing the different methods, so different analysis and results of large scale data is gathered. It is used for feature directions for the purpose of data modeling and analyzing to be implemented by using different machine learning and deep learning techniques and 3d visualization.Here different analysis methods have been surveyed for the future directions

scholarly journals Development of a cell-free split-luciferase biochemical assay as a tool for screening for inhibitors of challenging protein-protein interaction targets

2020 ◽  
Vol 5 ◽  
pp. 20
Author(s):  
Rachel Cooley ◽  
Neesha Kara ◽  
Ning Sze Hui ◽  
Jonathan Tart ◽  
Chloë Roustan ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Screening ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Large Scale ◽  
Cost Effective ◽  
Biochemical Assay ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Phosphoinositide 3 Kinase

Targeting the interaction of proteins with weak binding affinities or low solubility represents a particular challenge for drug screening. The NanoLucâ ® Binary Technology (NanoBiTâ ®) was originally developed to detect protein-protein interactions in live mammalian cells. Here we report the successful translation of the NanoBit cellular assay into a biochemical, cell-free format using mammalian cell lysates. We show that the assay is suitable for the detection of both strong and weak protein interactions such as those involving the binding of RAS oncoproteins to either RAF or phosphoinositide 3-kinase (PI3K) effectors respectively, and that it is also effective for the study of poorly soluble protein domains such as the RAS binding domain of PI3K. Furthermore, the RAS interaction assay is sensitive and responds to both strong and weak RAS inhibitors. Our data show that the assay is robust, reproducible, cost-effective, and can be adapted for small and large-scale screening approaches. The NanoBit Biochemical Assay offers an attractive tool for drug screening against challenging protein-protein interaction targets, including the interaction of RAS with PI3K.

scholarly journals Development of a cell-free split-luciferase biochemical assay as a tool for screening for inhibitors of challenging protein-protein interaction targets

2020 ◽  
Vol 5 ◽  
pp. 20
Author(s):  
Rachel Cooley ◽  
Neesha Kara ◽  
Ning Sze Hui ◽  
Jonathan Tart ◽  
Chloë Roustan ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Screening ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Large Scale ◽  
Cost Effective ◽  
Biochemical Assay ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Phosphoinositide 3 Kinase

Targeting the interaction of proteins with weak binding affinities or low solubility represents a particular challenge for drug screening. The NanoLuc ® Binary Technology (NanoBiT ®) was originally developed to detect protein-protein interactions in live mammalian cells. Here we report the successful translation of the NanoBit cellular assay into a biochemical, cell-free format using mammalian cell lysates. We show that the assay is suitable for the detection of both strong and weak protein interactions such as those involving the binding of RAS oncoproteins to either RAF or phosphoinositide 3-kinase (PI3K) effectors respectively, and that it is also effective for the study of poorly soluble protein domains such as the RAS binding domain of PI3K. Furthermore, the RAS interaction assay is sensitive and responds to both strong and weak RAS inhibitors. Our data show that the assay is robust, reproducible, cost-effective, and can be adapted for small and large-scale screening approaches. The NanoBit Biochemical Assay offers an attractive tool for drug screening against challenging protein-protein interaction targets, including the interaction of RAS with PI3K.

Negative protein–protein interaction datasets derived from large-scale two-hybrid experiments

Methods ◽  
2012 ◽  
Vol 58 (4) ◽  
pp. 343-348 ◽  
Author(s):  
Leonardo G. Trabuco ◽  
Matthew J. Betts ◽  
Robert B. Russell
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
Two Hybrid
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