scholarly journals Discovery–Versus Hypothesis–Driven Detection of Protein–Protein Interactions and Complexes

2021 ◽  
Vol 22 (9) ◽  
pp. 4450
Author(s):  
Isabell Bludau
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Protein Interactions ◽  
Prior Information ◽  
Protein Complexes ◽  
Functional Modules ◽  
Protein Protein Interactions ◽  
Future Studies ◽  
Protein Protein Interaction ◽  
Selection Of

Protein complexes are the main functional modules in the cell that coordinate and perform the vast majority of molecular functions. The main approaches to identify and quantify the interactome to date are based on mass spectrometry (MS). Here I summarize the benefits and limitations of different MS-based interactome screens, with a focus on untargeted interactome acquisition, such as co-fractionation MS. Specific emphasis is given to the discussion of discovery- versus hypothesis-driven data analysis concepts and their applicability to large, proteome-wide interactome screens. Hypothesis-driven analysis approaches, i.e., complex- or network-centric, are highlighted as promising strategies for comparative studies. While these approaches require prior information from public databases, also reviewed herein, the available wealth of interactomic data continuously increases, thereby providing more exhaustive information for future studies. Finally, guidance on the selection of interactome acquisition and analysis methods is provided to aid the reader in the design of protein-protein interaction studies.

scholarly journals Mass spectrometry-based methods for analysing the mitochondrial interactome in mammalian cells

2019 ◽  
Vol 167 (3) ◽  
pp. 225-231 ◽  
Author(s):  
Takumi Koshiba ◽  
Hidetaka Kosako
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Protein Complexes ◽  
Living Cells ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Protein Protein Interaction ◽  
Membrane Protein Complexes ◽  
Protein Protein Interaction Networks

Abstract Protein–protein interactions are essential biologic processes that occur at inter- and intracellular levels. To gain insight into the various complex cellular functions of these interactions, it is necessary to assess them under physiologic conditions. Recent advances in various proteomic technologies allow to investigate protein–protein interaction networks in living cells. The combination of proximity-dependent labelling and chemical cross-linking will greatly enhance our understanding of multi-protein complexes that are difficult to prepare, such as organelle-bound membrane proteins. In this review, we describe our current understanding of mass spectrometry-based proteomics mapping methods for elucidating organelle-bound membrane protein complexes in living cells, with a focus on protein–protein interactions in mitochondrial subcellular compartments.

scholarly journals PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Stefan Kalkhof ◽  
Stefan Schildbach ◽  
Conny Blumert ◽  
Friedemann Horn ◽  
Martin von Bergen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Isotope Labeling ◽  
Affinity Purification ◽  
Interaction Network ◽  
Mass Spectrometry Data ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Binding Behavior ◽  
Bona Fide

The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

scholarly journals Mass spectrometry-based cross-linking study shows that the Psb28 protein binds to cytochrome b559 in Photosystem II

2017 ◽  
Vol 114 (9) ◽  
pp. 2224-2229 ◽  
Author(s):  
Daniel A. Weisz ◽  
Haijun Liu ◽  
Hao Zhang ◽  
Sundarapandian Thangapandian ◽  
Emad Tajkhorshid ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Photosystem Ii ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Protein Docking ◽  
Cross Linking ◽  
Protein Protein Interactions ◽  
Cytochrome B559 ◽  
Reaction Center Complex ◽  
Assembly Intermediate

Photosystem II (PSII), a large pigment protein complex, undergoes rapid turnover under natural conditions. During assembly of PSII, oxidative damage to vulnerable assembly intermediate complexes must be prevented. Psb28, the only cytoplasmic extrinsic protein in PSII, protects the RC47 assembly intermediate of PSII and assists its efficient conversion into functional PSII. Its role is particularly important under stress conditions when PSII damage occurs frequently. Psb28 is not found, however, in any PSII crystal structure, and its structural location has remained unknown. In this study, we used chemical cross-linking combined with mass spectrometry to capture the transient interaction of Psb28 with PSII. We detected three cross-links between Psb28 and the α- and β-subunits of cytochrome b559, an essential component of the PSII reaction-center complex. These distance restraints enable us to position Psb28 on the cytosolic surface of PSII directly above cytochrome b559, in close proximity to the QB site. Protein–protein docking results also support Psb28 binding in this region. Determination of the Psb28 binding site and other biochemical evidence allow us to propose a mechanism by which Psb28 exerts its protective effect on the RC47 intermediate. This study also shows that isotope-encoded cross-linking with the “mass tags” selection criteria allows confident identification of more cross-linked peptides in PSII than has been previously reported. This approach thus holds promise to identify other transient protein–protein interactions in membrane protein complexes.

scholarly journals Evolutionary diversification of protein–protein interactions by interface add-ons

2017 ◽  
Vol 114 (40) ◽  
pp. E8333-E8342 ◽  
Author(s):  
Maximilian G. Plach ◽  
Florian Semmelmann ◽  
Florian Busch ◽  
Markus Busch ◽  
Leonhard Heizinger ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Evolutionary Strategy ◽  
Structural Level ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Evolutionary Diversification

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein–protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein–protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein–protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein–protein interactions.

scholarly journals PPI-MASS: An Interactive Web Server to Identify Protein-Protein Interactions From Mass Spectrometry-Based Proteomics Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Mariela González-Avendaño ◽  
Simón Zúñiga-Almonacid ◽  
Ian Silva ◽  
Boris Lavanderos ◽  
Felipe Robinson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Web Server ◽  
Target Protein ◽  
Protein Protein Interactions ◽  
Proteomics Data ◽  
Functional Protein ◽  
Web Platform ◽  
The Web

Mass spectrometry-based proteomics methods are widely used to identify and quantify protein complexes involved in diverse biological processes. Specifically, tandem mass spectrometry methods represent an accurate and sensitive strategy for identifying protein-protein interactions. However, most of these approaches provide only lists of peptide fragments associated with a target protein, without performing further analyses to discriminate physical or functional protein-protein interactions. Here, we present the PPI-MASS web server, which provides an interactive analytics platform to identify protein-protein interactions with pharmacological potential by filtering a large protein set according to different biological features. Starting from a list of proteins detected by MS-based methods, PPI-MASS integrates an automatized pipeline to obtain information of each protein from freely accessible databases. The collected data include protein sequence, functional and structural properties, associated pathologies and drugs, as well as location and expression in human tissues. Based on this information, users can manipulate different filters in the web platform to identify candidate proteins to establish physical contacts with a target protein. Thus, our server offers a simple but powerful tool to detect novel protein-protein interactions, avoiding tedious and time-consuming data postprocessing. To test the web server, we employed the interactome of the TRPM4 and TMPRSS11a proteins as a use case. From these data, protein-protein interactions were identified, which have been validated through biochemical and bioinformatic studies. Accordingly, our web platform provides a comprehensive and complementary tool for identifying protein-protein complexes assisting the future design of associated therapies.

scholarly journals Entropy-Based Graph Clustering of PPI Networks for Predicting Overlapping Functional Modules of Proteins

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1271
Author(s):  
Hoyeon Jeong ◽  
Yoonbee Kim ◽  
Yi-Sue Jung ◽  
Dae Ryong Kang ◽  
Young-Rae Cho
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Clustering Algorithms ◽  
Graph Clustering ◽  
Functional Modules ◽  
Protein Protein Interactions ◽  
Overlapping Clusters ◽  
Novel Proteins ◽  
Ppi Networks ◽  
Function Modules

Functional modules can be predicted using genome-wide protein–protein interactions (PPIs) from a systematic perspective. Various graph clustering algorithms have been applied to PPI networks for this task. In particular, the detection of overlapping clusters is necessary because a protein is involved in multiple functions under different conditions. graph entropy (GE) is a novel metric to assess the quality of clusters in a large, complex network. In this study, the unweighted and weighted GE algorithm is evaluated to prove the validity of predicting function modules. To measure clustering accuracy, the clustering results are compared to protein complexes and Gene Ontology (GO) annotations as references. We demonstrate that the GE algorithm is more accurate in overlapping clusters than the other competitive methods. Moreover, we confirm the biological feasibility of the proteins that occur most frequently in the set of identified clusters. Finally, novel proteins for the additional annotation of GO terms are revealed.

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

2020 ◽  
Author(s):  
Swantje Lenz ◽  
Ludwig R. Sinn ◽  
Francis J. O’Reilly ◽  
Lutz Fischer ◽  
Fritz Wegner ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Large Scale ◽  
Protein Complexes ◽  
Estimation Procedure ◽  
Scale Analysis ◽  
Protein Protein Interactions ◽  
False Discovery ◽  
Large Scale Analysis ◽  
False Discovery Rate Estimation

Crosslinking mass spectrometry is widening its scope from structural analyzes of purified multi-protein complexes towards systems-wide analyzes of protein-protein interactions. Assessing the error in these large datasets is currently a challenge. Using a controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate a reliable false-discovery rate estimation procedure for protein-protein interactions identified by crosslinking mass spectrometry.

scholarly journals Synthesis of two new enrichable and MS-cleavable cross-linkers to define protein–protein interactions by mass spectrometry

2015 ◽  
Vol 13 (17) ◽  
pp. 5030-5037 ◽  
Author(s):  
Anthony M. Burke ◽  
Wynne Kandur ◽  
Eric J. Novitsky ◽  
Robyn M. Kaake ◽  
Clinton Yu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Structural Information ◽  
Protein Complexes ◽  
Cross Linking ◽  
Protein Protein Interactions ◽  
The Cross

The cross-linking Mass Spectrometry (XL-MS) technique extracts structural information from protein complexes without requiring highly purified samples, crystallinity, or large amounts of material.

scholarly journals Probing conformational hotspots for the recognition and intervention of protein complexes by lysine reactivity profiling

2021 ◽  
Author(s):  
Zheyi Liu ◽  
Wenxiang Zhang ◽  
Binwen Sun ◽  
Yaolu Ma ◽  
Min He ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Small Molecule ◽  
Protein Interactions ◽  
Isotope Labeling ◽  
Protein Complexes ◽  
Protein Protein Interactions ◽  
Active Compounds

A mass spectrometry-based two-step isotope labeling-lysine reactivity profiling strategy is developed to probe the molecular details of protein–protein interactions and evaluate the conformational interventions by small-molecule active compounds.

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