scholarly journals High-throughput characterization of protein–protein interactions by reprogramming yeast mating

2017 ◽  
Vol 114 (46) ◽  
pp. 12166-12171 ◽  
Author(s):  
David Younger ◽  
Stephanie Berger ◽  
David Baker ◽  
Eric Klavins
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Binding Proteins ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Mating Efficiency ◽  
Extracellular Environment

High-throughput methods for screening protein–protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination ofSaccharomyces cerevisiaecan be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions withKds ranging from below 500 pM to above 300 μM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein–protein interaction networks in a fully defined extracellular environment at a library-on-library scale.

scholarly journals High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating

2017 ◽  
Author(s):  
David Younger ◽  
Stephanie Berger ◽  
David Baker ◽  
Eric Klavins
Keyword(s):  
High Throughput ◽  
Protein Interactions ◽  
Interaction Strength ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Quantitative Characterization ◽  
Mating Efficiency ◽  
Extracellular Environment

AbstractHigh-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination of S. cerevisiae can be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions with KD’s ranging from below 500 pM to above 300 μM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein-protein interaction networks in a fully-defined extracellular environment at a library-on-library scale.Significance StatementDe novo engineering of protein binders often requires experimental screening to select functional variants from a design library. We have achieved high-throughput, quantitative characterization of protein-protein binding interactions without requiring purified recombinant proteins, by linking interaction strength with yeast mating. Using a next-generation sequencing output, we have characterized protein networks consisting of thousands of pairwise interactions in a single tube and have demonstrated the effect of changing the binding environment. This approach addresses an existing bottleneck in protein binder design by enabling the high-throughput and quantitative characterization of binding strength between designed protein libraries and multiple target proteins in a fully defined environment.

High-throughput identification of transient extracellular protein interactions

2010 ◽  
Vol 38 (4) ◽  
pp. 919-922 ◽  
Author(s):  
Gavin J. Wright ◽  
Stephen Martin ◽  
K. Mark Bushell ◽  
Christian Söllner
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Living Cell ◽  
Protein Interaction Networks ◽  
Extracellular Protein ◽  
Interaction Networks ◽  
Receptor Proteins ◽  
Major Class ◽  
Extracellular Environment

Protein interactions are highly diverse in their biochemical nature, varying in affinity and are often dependent on the surrounding biochemical environment. Given this heterogeneity, it seems unlikely that any one method, and particularly those capable of screening for many protein interactions in parallel, will be able to detect all functionally relevant interactions that occur within a living cell. One major class of interactions that are not detected by current popular high-throughput methods are those that occur in the extracellular environment, especially those made by membrane-embedded receptor proteins. In the present article, we discuss some of our recent research in the development of a scalable assay to identify this class of protein interaction and some of the findings from its application in the construction of extracellular protein interaction networks.

scholarly journals PINAWeb: A web-based tool for the comparison of Protein-Protein Interaction Networks Aligners

2021 ◽  
Author(s):  
A. Alcalá ◽  
G. Riera ◽  
I. García ◽  
R. Alberich ◽  
M. Llabrés
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Considerable Effort ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks ◽  
User Friendly

AbstractMotivationSeveral protein-protein interaction networks (PPIN) aligners have been developed during the last 15 years. One of their goals is to help the functional annotation of proteins and the prediction of protein-protein interactions. A correct aligner must preserve the network’s topology as well as the biological coherence. However, this is a trade-off that is hard to achieve. In addition, most aligners require a considerable effort to use in practice and many researchers must choose an aligner without the opportunity to previously compare the performance of different aligners.ResultsWe developed PINAWeb, a user-friendly web-based tool to obtain and compare the results produced by the aligners: AligNet, HubAlign, L-GRAAL, PINALOG and SPINAL. PPINs can be uploaded either from the STRING database or from a user database. The source code of PINAWeb is freely available on GitHub to enable researchers to add other aligners, network databases or alignment score metrics. In addition, PINAWeb provides a report with the analysis for every alignment in terms of topological and functional information scores, as well as the visualization of the alignments’ comparison (agreement/differences) when more than one aligner are considered.Availabilityhttps://bioinfo.uib.es/~recerca/PINAWeb

Evolution in protein interaction networks: co-evolution, rewiring and the role of duplication

2009 ◽  
Vol 37 (4) ◽  
pp. 768-771 ◽  
Author(s):  
David L. Robertson ◽  
Simon C. Lovell
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Functional Change ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Molecular Function ◽  
Specific Interactions ◽  
Protein Protein Interactions ◽  
Working Together

Molecular function is the result of proteins working together, mediated by highly specific interactions. Maintenance and change of protein interactions can thus be considered one of the main links between molecular function and mutation. As a consequence, protein interaction datasets can be used to study functional evolution directly. In terms of constraining change, the co-evolution of interacting molecules is a very subtle process. This has implications for the signal being used to predict protein–protein interactions. In terms of functional change, the ‘rewiring’ of interaction networks, gene duplication is critically important. Interestingly, once duplication has occurred, the genes involved have different probabilities of being retained related to how they were generated. In the present paper, we discuss some of our recent work in this area.

scholarly journals PPI layouts: BioJS components for the display of Protein-Protein Interactions

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 50 ◽  
Author(s):  
Gustavo A. Salazar ◽  
Ayton Meintjes ◽  
Nicola Mulder
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Third Party ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Link Type ◽  
Protein Protein Interaction Networks

Summary: We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. Availability: http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753

scholarly journals AligNet: Alignment of Protein-Protein Interaction Networks

2019 ◽  
Author(s):  
R. Alberich ◽  
A. Alcalá ◽  
M. Llabrés ◽  
F. Rosselló ◽  
G. Valiente
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Biological Information ◽  
Global Alignment ◽  
Alignment Algorithm ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

AbstractOne of the most difficult problems difficult problem in systems biology is to discover protein-protein interactions as well as their associated functions. The analysis and alignment of protein-protein interaction networks (PPIN), which are the standard model to describe protein-protein interactions, has become a key ingredient to obtain functional orthologs as well as evolutionary conserved pathways and protein complexes. Several methods have been proposed to solve the PPIN alignment problem, aimed to match conserved subnetworks or functionally related proteins. However, the right balance between considering network topology and biological information is one of the most difficult and key points in any PPIN alignment algorithm which, unfortunately, remains unsolved. Therefore, in this work, we propose AligNet, a new method and software tool for the pairwise global alignment of PPIN that produces biologically meaningful alignments and more efficient computations than state-of-the-art methods and tools, by achieving a good balance between structural matching and protein function conservation as well as reasonable running times.

scholarly journals Evolution of Protein-protein Interaction Networks in Duplication-Divergence Model

2012 ◽  
Vol 22 (1) ◽  
pp. 7-14
Author(s):  
Bui Phuong Thuy ◽  
Trinh Xuan Hoang
Keyword(s):  
Experimental Data ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Scale Free ◽  
Protein Protein Interaction ◽  
Living Organisms

Protein interacts with one another resulting in complex functions in living organisms. Like many other real-world networks, the networks of protein-protein interactions possess a certain degree of ordering, such as the scale-free property. The latter means that the probability $P$ to find a protein that interacts with $k$ other proteins follows a power law, $P(k) \sim k^{-\gamma}$. Protein interaction networks (PINs) have been studied by using a stochastic model, the duplication-divergence model, which is based on mechanisms of gene duplication and divergence during evolution. In this work, we show that this model can be used to fit experimental data on the PIN of yeast Saccharomyces cerevisae at two different time instances simultaneously. Our study shows that the evolution of PIN given by model is consistent with growing experimental data over time, and that the scale-free property of protein interaction network is robust against random deletion of interactions.

Discovering Interaction Motifs from Protein Interaction Networks

2009 ◽  
pp. 99-116 ◽  
Author(s):  
Hugo Willy
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Protein Patterns ◽  
Protein Protein Interaction ◽  
Family Based ◽  
High Throughput Experiments

Recent breakthroughs in high throughput experiments to determine protein-protein interaction have generated a vast amount of protein interaction data. However, most of the experiments could only answer the question of whether two proteins interact but not the question on the mechanisms by which proteins interact. Such understanding is crucial for understanding the protein interaction of an organism as a whole (the interactome) and even predicting novel protein interactions. Protein interaction usually occurs at some specific sites on the proteins and, given their importance, they are usually well conserved throughout the evolution of the proteins of the same family. Based on this observation, a number of works on finding protein patterns/motifs conserved in interacting proteins have emerged in the last few years. Such motifs are collectively termed as the interaction motifs. This chapter provides a review on the different approaches on finding interaction motifs with a discussion on their implications, potentials and possible areas of improvements in the future.

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