scholarly journals Lights, Camera, Interaction: Studying Protein–Protein Interactions of the ER Protein Translocase in Living Cells

2021 ◽  
Vol 22 (19) ◽  
pp. 10358
Author(s):  
Mark Sicking ◽  
Martin Jung ◽  
Sven Lang
Keyword(s):  
Membrane Proteins ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Protein Complexes ◽  
Living Cells ◽  
Ease Of Use ◽  
Protein Protein Interactions ◽  
Regulatory Subunits ◽  
Complex Interactions ◽  
Er Membrane

Various landmark studies have revealed structures and functions of the Sec61/SecY complex in all domains of live demonstrating the conserved nature of this ancestral protein translocase. While the bacterial homolog of the Sec61 complex resides in the plasma membrane, the eukaryotic counterpart manages the transfer of precursor proteins into or across the membrane of the endoplasmic reticulum (ER). Sec61 complexes are accompanied by a set of dynamically recruited auxiliary proteins assisting the transport of certain precursor polypeptides. TRAP and Sec62/Sec63 are two auxiliary protein complexes in mammalian cells that have been characterized by structural and biochemical methods. Using these ER membrane protein complexes for our proof-of-concept study, we aimed to detect interactions of membrane proteins in living mammalian cells under physiological conditions. Bimolecular luminescence complementation and competition was used to demonstrate multiple protein–protein interactions of different topological layouts. In addition to the interaction of the soluble catalytic and regulatory subunits of the cytosolic protein kinase A, we detected interactions of ER membrane proteins that either belong to the same multimeric protein complex (intra-complex interactions: Sec61α–Sec61β, TRAPα–TRAPβ) or protein complexes in juxtaposition (inter-complex interactions: Sec61α–TRAPα, Sec61α–Sec63, and Sec61β–Sec63). In the process, we established further control elements like synthetic peptide complementation for expression profiling of fusion constructs and protease-mediated reporter degradation demonstrating the cytosolic localization of a reporter complementation. Ease of use and flexibility of the approach presented here will spur further research regarding the dynamics of protein–protein interactions in response to changing cellular conditions in living cells.

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 Applications of In-Cell NMR in Structural Biology and Drug Discovery

2019 ◽  
Vol 20 (1) ◽  
pp. 139 ◽  
Author(s):  
CongBao Kang
Keyword(s):  
Drug Discovery ◽  
Conformational Changes ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Structural Information ◽  
Living Cells ◽  
Bacterial Cells ◽  
Protein Protein Interactions ◽  
Nmr Studies ◽  
Post Translational Modifications

In-cell nuclear magnetic resonance (NMR) is a method to provide the structural information of a target at an atomic level under physiological conditions and a full view of the conformational changes of a protein caused by ligand binding, post-translational modifications or protein–protein interactions in living cells. Previous in-cell NMR studies have focused on proteins that were overexpressed in bacterial cells and isotopically labeled proteins injected into oocytes of Xenopus laevis or delivered into human cells. Applications of in-cell NMR in probing protein modifications, conformational changes and ligand bindings have been carried out in mammalian cells by monitoring isotopically labeled proteins overexpressed in living cells. The available protocols and successful examples encourage wide applications of this technique in different fields such as drug discovery. Despite the challenges in this method, progress has been made in recent years. In this review, applications of in-cell NMR are summarized. The successful applications of this method in mammalian and bacterial cells make it feasible to play important roles in drug discovery, especially in the step of target engagement.

Genetically encoded selective cross-linkers and emerging applications

2020 ◽  
Vol 48 (4) ◽  
pp. 1807-1817
Author(s):  
Haiyan Ren
Keyword(s):  
Protein Interactions ◽  
Unnatural Amino Acids ◽  
Protein Complexes ◽  
Living Cells ◽  
Cross Linking ◽  
Protein Protein Interactions ◽  
New Class ◽  
Selective Reaction ◽  
Biological Studies ◽  
Lower Background

There has been a large amount of interest in the development of genetically encoded cross-linkers that target functional groups naturally present in cells. Recently, a new class of unnatural amino acids that specifically react with target residues were developed and genetically incorporated. The selective reaction shows higher cross-linking efficiency, lower background and predictable cross-linking sites. It has been applied to enhance protein/peptide stability, pinpoint protein–protein interactions, stabilize protein complexes, engineer covalent protein inhibitors, identify phosphatases in living cells, etc. These new covalent linkages provide excellent new tools for protein engineering and biological studies. Their applications in biotherapy will provide considerable opportunities for innovating and improving biomolecular medicines.

scholarly journals A rapid and accurate approach for Prediction of interactomes from co-elution data (PrInCE)

2017 ◽  
Author(s):  
R. Greg Stacey ◽  
Michael A. Skinnider ◽  
Nichollas E. Scott ◽  
Leonard J. Foster
Keyword(s):  
Protein Interactions ◽  
Isotope Labeling ◽  
Protein Complexes ◽  
Affinity Purification ◽  
Ease Of Use ◽  
Label Free ◽  
Protein Protein Interactions ◽  
Bioinformatics Pipeline ◽  
Vast Number ◽  
Free Data

AbstractBackgroundAn organism’s protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally applied targeted strategies such as yeast two-hybrid or affinity purification-mass spectrometry to assess protein interactions. However, given the vast number of protein complexes, more scalable methods are necessary to accelerate interaction discovery and to construct whole interactomes. We recently developed a complementary technique based on the use of protein correlation profiling (PCP) and stable isotope labeling in amino acids in cell culture (SILAC) to assess chromatographic co-elution as evidence of interacting proteins. Importantly, PCP-SILAC is also capable of measuring protein interactions simultaneously under multiple biological conditions, allowing the detection of treatment-specific changes to an interactome. Given the uniqueness and high dimensionality of co-elution data, new tools are needed to compare protein elution profiles, control false discovery rates, and construct an accurate interactome.ResultsHere we describe a freely available bioinformatics pipeline, PrInCE, for the analysis of co-elution data. PrInCE is a modular, open-source library that is computationally inexpensive, able to use label and label-free data, and capable of detecting tens of thousands of protein-protein interactions. Using a machine learning approach, PrInCE offers greatly reduced run time, better performance, prediction of protein complexes, and greater ease of use over previous bioinformatics tools for co-elution data. PrInCE is implemented in Matlab (version R2015b). Source code and standalone executable programs for Windows and Mac OSX are available at https://github.com/fosterlab/PrInCE, where usage instructions can be found. An example dataset and output are also provided for testing purposes.ConclusionsPrInCE is the first fast and easy-to-use data analysis pipeline that predicts interactomes and protein complexes from co-elution data. PrInCE allows researchers without bioinformatics proficiency to analyze high-throughput co-elution datasets.

Spying on protein interactions in living cells with reconstituted scarlet light

The Analyst ◽  
2018 ◽  
Vol 143 (21) ◽  
pp. 5161-5169 ◽  
Author(s):  
Sheng Wang ◽  
Miao Ding ◽  
Boxin Xue ◽  
Yingping Hou ◽  
Yujie Sun
Keyword(s):  
Protein Interactions ◽  
Mammalian Cells ◽  
Living Cells ◽  
Protein Protein Interactions ◽  
Efficient Detection

A red BiFC system was developed for efficient detection and visualization of protein–protein interactions under 37 °C in live mammalian cells.

scholarly journals Molecular interactions of the M and E integral membrane proteins of SARS-CoV-2

2021 ◽  
Author(s):  
Viviana Monje-Galvan ◽  
Gregory A. Voth
Keyword(s):  
Membrane Proteins ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Integral Membrane Proteins ◽  
Protein Protein Interactions ◽  
Novel Treatments ◽  
Cellular Processes ◽  
Ongoing Work ◽  
Lipid Environment ◽  
Lipid Protein Interactions

AbstractSpecific lipid-protein interactions are key for cellular processes, and even more so for the replication of pathogens. The COVID-19 pandemic has drastically changed our lives and cause the death of nearly three million people worldwide, as of this writing. SARS-CoV-2 is the virus that causes the disease and has been at the center of scientific research over the past year. Most of the research on the virus is focused on key players during its initial attack and entry into the cellular host; namely the S protein, its glycan shield, and its interactions with the ACE2 receptors of human cells. As cases continue to raise around the globe, and new mutants are identified, there is an urgent need to understand the mechanisms of this virus during different stages of its life cycle. Here, we consider two integral membrane proteins of SARS-CoV-2 known to be important for viral assembly and infectivity. We have used microsecond-long all-atom molecular dynamics to examine the lipid-protein and protein-protein interactions of the membrane (M) and envelope (E) structural proteins of SARS-CoV-2 in a complex membrane model. We contrast the two proposed protein complexes for each of these proteins, and quantify their effect on their local lipid environment. This ongoing work also aims to provide molecular-level understanding of the mechanisms of action of this virus to possibly aid in the design of novel treatments.

TMCC3 localizes at the three-way junctions for the proper tubular network of the endoplasmic reticulum

2019 ◽  
Vol 476 (21) ◽  
pp. 3241-3260
Author(s):  
Sindhu Wisesa ◽  
Yasunori Yamamoto ◽  
Toshiaki Sakisaka
Keyword(s):  
Endoplasmic Reticulum ◽  
Membrane Proteins ◽  
Membrane Protein ◽  
Mammalian Cells ◽  
Coiled Coil ◽  
Transmembrane Domains ◽  
Domain Family ◽  
Coiled Coil Domain ◽  
U2os Cells ◽  
Er Membrane

The tubular network of the endoplasmic reticulum (ER) is formed by connecting ER tubules through three-way junctions. Two classes of the conserved ER membrane proteins, atlastins and lunapark, have been shown to reside at the three-way junctions so far and be involved in the generation and stabilization of the three-way junctions. In this study, we report TMCC3 (transmembrane and coiled-coil domain family 3), a member of the TEX28 family, as another ER membrane protein that resides at the three-way junctions in mammalian cells. When the TEX28 family members were transfected into U2OS cells, TMCC3 specifically localized at the three-way junctions in the peripheral ER. TMCC3 bound to atlastins through the C-terminal transmembrane domains. A TMCC3 mutant lacking the N-terminal coiled-coil domain abolished localization to the three-way junctions, suggesting that TMCC3 localized independently of binding to atlastins. TMCC3 knockdown caused a decrease in the number of three-way junctions and expansion of ER sheets, leading to a reduction of the tubular ER network in U2OS cells. The TMCC3 knockdown phenotype was partially rescued by the overexpression of atlastin-2, suggesting that TMCC3 knockdown would decrease the activity of atlastins. These results indicate that TMCC3 localizes at the three-way junctions for the proper tubular ER network.

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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