Detection and analysis of protein–protein interactions in organellar and prokaryotic proteomes by native gel electrophoresis: (Membrane) protein complexes and supercomplexes

2006 ◽  
Vol 27 (13) ◽  
pp. 2759-2781 ◽  
Author(s):  
Frank Krause
Keyword(s):  
Membrane Protein ◽  
Protein Interactions ◽  
Gel Electrophoresis ◽  
Protein Complexes ◽  
Protein Protein Interactions ◽  
Membrane Protein Complexes ◽  
Native Gel

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 Mitochondrial ATP synthase dimers spontaneously self-associate driven by a long-ranged membrane-induced force

2018 ◽  
Author(s):  
Claudio Anselmi ◽  
Karen M. Davies ◽  
José D. Faraldo-Gómez
Keyword(s):  
Atp Synthase ◽  
Protein Interactions ◽  
Simulation Analysis ◽  
Protein Complexes ◽  
Protein Protein Interactions ◽  
Inner Mitochondrial Membrane ◽  
Atp Production ◽  
Mitochondrial Atp Synthase ◽  
Membrane Protein Complexes ◽  
Atp Synthases

AbstractATP synthases populate the inner membranes of mitochondria, where they produce the majority of the ATP required by the cell. Cryo-electron tomograms of these membranes from yeast to vertebrates have consistently revealed a very precise organization of these enzymes. Rather than being scattered throughout the membrane, the ATP synthases form dimers, and these dimers are organized into rows that extend for hundreds of nanometers. These rows are only observed in the membrane invaginations known as cristae, specifically along their sharply curved edges. Although the presence of these macromolecular structures has been irrefutably linked to the proper development of cristae morphology, it has been unclear what drives the formation of the rows and why they are specifically localized in the cristae. We present the result of a quantitative molecular-simulation analysis that strongly suggests that the ATP synthase dimers organize into rows spontaneously, driven by a long-ranged attractive force that results from relief in the overall elastic strain of the membrane. This strain is caused by the V-like shape of the dimers, unique among membrane-protein complexes, which induces a strong deformation in the surrounding membrane. The process of row formation is therefore not a result of protein-protein interactions, or of a specific lipid composition of the membrane. We further hypothesize that once assembled, the ATP synthase dimer rows prime the inner mitochondrial membrane to develop folds and invaginations, by causing macroscopic membrane ridges that ultimately become the cristae edges. In this view, mitochondrial ATP synthases would contribute to the generation of a morphology that maximizes the surface area of the inner membrane, and thus ATP production. Finally, we outline the key experiments that would be required to verify or refute this hypothesis.

scholarly journals Nuclear magnetic resonance (NMR) applied to membrane–protein complexes

2016 ◽  
Vol 49 ◽  
Author(s):  
Mohammed Kaplan ◽  
Cecilia Pinto ◽  
Klaartje Houben ◽  
Marc Baldus
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Membrane Protein ◽  
Protein Interactions ◽  
Protein Transport ◽  
Isotope Labeling ◽  
Protein Complexes ◽  
Cellular Membranes ◽  
Membrane Protein Complexes ◽  
Nuclear Magnetic

AbstractIncreasing evidence suggests that most proteins occur and function in complexes rather than as isolated entities when embedded in cellular membranes. Nuclear magnetic resonance (NMR) provides increasing possibilities to study structure, dynamics and assembly of such systems. In our review, we discuss recent methodological progress to study membrane–protein complexes (MPCs) by NMR, starting with expression, isotope-labeling and reconstitution protocols. We review approaches to deal with spectral complexity and limited spectral spectroscopic sensitivity that are usually encountered in NMR-based studies of MPCs. We highlight NMR applications in various classes of MPCs, including G-protein-coupled receptors, ion channels and retinal proteins and extend our discussion to protein–protein complexes that span entire cellular compartments or orchestrate processes such as protein transport across or within membranes. These examples demonstrate the growing potential of NMR-based studies of MPCs to provide critical insight into the energetics of protein–ligand and protein–protein interactions that underlie essential biological functions in cellular membranes.

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Experimental Studies ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Prediction Tools ◽  
Physiological Processes ◽  
Modern Drug ◽  
Ppi Prediction

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.

Protein Interaction Domains and Post-Translational Modifications: Structural Features and Drug Discovery Applications

2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone
Keyword(s):  
Drug Discovery ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Structural Information ◽  
Protein Complexes ◽  
Structural Features ◽  
Protein Protein Interactions ◽  
Modular Architecture ◽  
Post Translational Modifications ◽  
Interaction Domains

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.

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