scholarly journals A protein interaction map for cell polarity development

2001 ◽  
Vol 154 (3) ◽  
pp. 549-576 ◽  
Author(s):  
Becky L. Drees ◽  
Bryan Sundin ◽  
Elizabeth Brazeau ◽  
Juliane P. Caviston ◽  
Guang-Chao Chen ◽  
...  
Keyword(s):  
Cell Polarity ◽  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Open Reading Frames ◽  
Actin Assembly ◽  
Protein Protein Interactions ◽  
Microtubule Organization ◽  
Two Hybrid ◽  
Secretory Apparatus

Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed.

scholarly journals Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sun Sook Chung ◽  
Joseph C F Ng ◽  
Anna Laddach ◽  
N Shaun B Thomas ◽  
Franca Fraternali
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Short Loop ◽  
New Strategy ◽  
Loop Network ◽  
Protein Protein Interaction Network

Abstract Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein–protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein–Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named ‘short loop commonality’ to measure indirect PPIs occurring via common SLM interactions. This detects ‘modules’ of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR–Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

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 High throughput flow cytometry based yeast two-hybrid array approach for large-scale analysis of protein-protein interactions

2011 ◽  
Vol 81A (1) ◽  
pp. 90-98 ◽  
Author(s):  
Jun Chen ◽  
Mark B. Carter ◽  
Bruce S. Edwards ◽  
Hong Cai ◽  
Larry A. Sklar
Keyword(s):  
Flow Cytometry ◽  
High Throughput ◽  
Protein Interactions ◽  
Large Scale ◽  
Scale Analysis ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Large Scale Analysis ◽  
Two Hybrid

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 Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins

Yeast ◽  
2000 ◽  
Vol 1 (2) ◽  
pp. 95-110
Author(s):  
Micheline Fromont-Racine ◽  
Andrew E. Mayes ◽  
Adeline Brunet-Simon ◽  
Jean-Christophe Rain ◽  
Alan Colley ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Genomic Sequence ◽  
Open Reading Frames ◽  
Yeast Genome ◽  
Protein Protein Interactions ◽  
Sm Proteins ◽  
Functional Studies ◽  
Genome Wide ◽  
A Genome ◽  
Two Hybrid

A set of seven structurally related Sm proteins forms the core of the snRNP particles containing the spliceosomal U1, U2, U4 and U5 snRNAs. A search of the genomic sequence of Saccharomyces cerevisiae has identified a number of open reading frames that potentially encode structurally similar proteins termed Lsm (L¯ike Sm¯) proteins. With the aim of analysing all possible interactions between the Lsm proteins and any protein encoded in the yeast genome, we performed exhaustive and iterative genomic two-hybrid screens, starting with the Lsm proteins as baits. Indeed, extensive interactions amongst eight Lsm proteins were found that suggest the existence of a Lsm complex or complexes. These Lsm interactions apparently involve the conserved Sm domain that also mediates interactions between the Sm proteins. The screens also reveal functionally significant interactions with splicing factors, in particular with Prp4 and Prp24, compatible with genetic studies and with the reported association of Lsm proteins with spliceosomal U6 and U4/U6 particles. In addition, interactions with proteins involved in mRNA turnover, such as Mrt1, Dcp1, Dcp2 and Xrn1, point to roles for Lsm complexes in distinct RNA metabolic processes, that are confirmed in independent functional studies. These results provide compelling evidence that two-hybrid screens yield functionally meaningful information about protein–protein interactions and can suggest functions for uncharacterized proteins, especially when they are performed on a genome-wide scale.

scholarly journals Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins

Yeast ◽  
2000 ◽  
Vol 1 (2) ◽  
pp. 95-110 ◽  
Author(s):  
Micheline Fromont-Racine ◽  
Andrew E. Mayes ◽  
Adeline Brunet-Simon ◽  
Jean-Christophe Rain ◽  
Alan Colley ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Genomic Sequence ◽  
Open Reading Frames ◽  
Yeast Genome ◽  
Protein Protein Interactions ◽  
Sm Proteins ◽  
Functional Studies ◽  
Genome Wide ◽  
A Genome ◽  
Two Hybrid

A set of seven structurally related Sm proteins forms the core of the snRNP particles containing the spliceosomal U1, U2, U4 and U5 snRNAs. A search of the genomic sequence ofSaccharomyces cerevisiaehas identified a number of open reading frames that potentially encode structurally similar proteins termed Lsm (L¯ike Sm¯) proteins. With the aim of analysing all possible interactions between the Lsm proteins and any protein encoded in the yeast genome, we performed exhaustive and iterative genomic two-hybrid screens, starting with the Lsm proteins as baits. Indeed, extensive interactions amongst eight Lsm proteins were found that suggest the existence of a Lsm complex or complexes. These Lsm interactions apparently involve the conserved Sm domain that also mediates interactions between the Sm proteins. The screens also reveal functionally significant interactions with splicing factors, in particular with Prp4 and Prp24, compatible with genetic studies and with the reported association of Lsm proteins with spliceosomal U6 and U4/U6 particles. In addition, interactions with proteins involved in mRNA turnover, such as Mrt1, Dcp1, Dcp2 and Xrn1, point to roles for Lsm complexes in distinct RNA metabolic processes, that are confirmed in independent functional studies. These results provide compelling evidence that two-hybrid screens yield functionally meaningful information about protein–protein interactions and can suggest functions for uncharacterized proteins, especially when they are performed on a genome-wide scale.

scholarly journals Reliable identification of protein-protein interactions by crosslinking mass spectrometry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Swantje Lenz ◽  
Ludwig R. Sinn ◽  
Francis J. O’Reilly ◽  
Lutz Fischer ◽  
Fritz Wegner ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Large Scale ◽  
Structural Information ◽  
Protein Complexes ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
False Discovery Rates ◽  
Large Scale Analysis ◽  
Exit Tunnel

AbstractProtein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

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