scholarly journals The wiring of protein networks: Computational approaches for predicting protein interaction networks

2011 ◽  
Vol 33 (1) ◽  
pp. 8-11
Author(s):  
Hung Xuan Ta ◽  
Liisa Holm
Keyword(s):  
Computational Methods ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Experimental Techniques ◽  
Biological Functions ◽  
Protein Protein Interactions ◽  
Computational Approaches ◽  
Experimental Approaches

A great number of cellular behaviours are mediated by proteins which always carry out their functions by interacting with each other. Unravelling protein–protein interactions (PPIs) is one of the central goals in proteomics, which will decipher the molecular mechanisms underlying the biological functions and thereby help to understand human diseases on a system-wide level. A number of experimental techniques, especially high-throughput approaches, have resulted in a large amount of PPI data that still suffer from incompleteness and contradiction. Moreover, these experimental techniques are expensive, time-consuming and labour-intensive. Computational methods have emerged as complementary tools to experimental approaches to discover PPIs. Promisingly, computational methods can guide, assess and validate experimental data and finally predict novel PPIs.

DISCOVERING PROTEIN–PROTEIN INTERACTIONS

2004 ◽  
Vol 01 (04) ◽  
pp. 711-741 ◽  
Author(s):  
SEE-KIONG NG ◽  
SOON-HENG TAN
Keyword(s):  
Protein Interactions ◽  
Experimental Methods ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Biological Processes ◽  
Protein Protein Interactions ◽  
Comprehensive Description ◽  
New Genes ◽  
Genomics And Proteomics ◽  
Living Organisms

The ongoing genomics and proteomics efforts have helped identify many new genes and proteins in living organisms. However, simply knowing the existence of genes and proteins does not tell us much about the biological processes in which they participate. Many major biological processes are controlled by protein interaction networks. A comprehensive description of protein–protein interactions is therefore necessary to understand the genetic program of life. In this tutorial, we provide an overview of the various current high-throughput methods for discovering protein–protein interactions, covering both the conventional experimental methods and new computational approaches.

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 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.

Crystallography and protein–protein interactions: biological interfaces and crystal contacts

2008 ◽  
Vol 36 (6) ◽  
pp. 1438-1441 ◽  
Author(s):  
Bostjan Kobe ◽  
Gregor Guncar ◽  
Rebecca Buchholz ◽  
Thomas Huber ◽  
Bohumil Maco ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Analytical Ultracentrifugation ◽  
Protein Complexes ◽  
Platelet Glycoprotein ◽  
Protein Protein Interactions ◽  
Computational Approaches ◽  
Biological Interface ◽  
Crystal Contacts ◽  
Experimental Approaches ◽  
Biological Interfaces

Crystallography is commonly used for studying the structures of protein–protein complexes. However, a crystal structure does not define a unique protein–protein interface, and distinguishing a ‘biological interface’ from ‘crystal contacts’ is often not straightforward. A number of computational approaches exist for distinguishing them, but their error rate is high, emphasizing the need to obtain further data on the biological interface using complementary structural and functional approaches. In addition to reviewing the computational and experimental approaches for addressing this problem, we highlight two relevant examples. The first example from our laboratory involves the structure of acyl-CoA thioesterase 7, where each domain of this two-domain protein was crystallized separately, but both yielded a non-functional assembly. The structure of the full-length protein was uncovered using a combination of complementary approaches including chemical cross-linking, analytical ultracentrifugation and mutagenesis. The second example involves the platelet glycoprotein Ibα–thrombin complex. Two groups reported the crystal structures of this complex, but all the interacting interfaces differed between the two structures. Our computational analysis did not fully resolve the reasons for the discrepancies, but provided interesting insights into the system. This review highlights the need to complement crystallographic studies with complementary experimental and computational approaches.

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.

scholarly journals Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yanghe Feng ◽  
Qi Wang ◽  
Tengjiao Wang
Keyword(s):  
Protein Interactions ◽  
Drug Target ◽  
Drug Targets ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Topological Features ◽  
Protein Protein Interaction Networks

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target’s homologue set containing 102 potential target proteins is predicted in the paper.

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.

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