scholarly journals Photoproximity Profiling of Protein-Protein Interactions in Cells

2019 ◽  
Author(s):  
David C. McCutcheon ◽  
Gihoon Lee ◽  
Anthony Carlos ◽  
Jeffrey E. Montgomery ◽  
Raymond E. Moellering
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Live Cells ◽  
High Temporal Resolution ◽  
Protein Protein Interactions ◽  
Redox Stress ◽  
Covalent Interaction ◽  
Protein Protein Interaction ◽  
In Cells

ABSTRACTWe report a novel photoproximity protein interaction (PhotoPPI) profiling method to map protein-protein interactions in vitro and in live cells. This approach utilizes a bioorthogonal, multifunctional chemical probe that can be targeted to a genetically encoded protein of interest (POI) through a modular SNAP-Tag/benzylguanine covalent interaction. A first generation photoproximity probe, PP1, responds to 365 nm light to simultaneously cleave a central nitroveratryl linker and a peripheral diazirine group, resulting in diffusion of a highly reactive carbene nucleophile away from the POI. We demonstrate facile probe loading, and subsequent interaction- and light-dependent proximal labeling of a model protein-protein interaction (PPI) in vitro. Integration of the PhotoPPI workflow with quantitative LC-MS/MS enabled un-biased interaction mapping for the redox regulated sensor protein, KEAP1, for the first time in live cells. We validated known and novel interactions between KEAP1 and the proteins PGAM5 and HK2, among others, under basal cellular conditions. By contrast, comparison of PhotoPPI profiles in cells experiencing metabolic or redox stress confirmed that KEAP1 sheds many basal interactions and becomes associated with known lysosomal trafficking and proteolytic proteins like SQSTM1, CTSD and LGMN. Together, these data establish PhotoPPI as a method capable of tracking the dynamic sub-cellular and protein interaction “social network” of a redox-sensitive protein in cells with high temporal resolution.SYNOPSIS TOC

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 Mapping of the Hepatitis B Virus Reverse Transcriptase TP and RT Domains by Transcomplementation for Nucleotide Priming and by Protein-Protein Interaction

1999 ◽  
Vol 73 (3) ◽  
pp. 1885-1893 ◽  
Author(s):  
Robert E. Lanford ◽  
Young-Ho Kim ◽  
Helen Lee ◽  
Lena Notvall ◽  
Burton Beames
Keyword(s):  
Amino Acids ◽  
Reverse Transcriptase ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Rnase H ◽  
Genome Replication ◽  
Protein Protein Interactions ◽  
Stem Loop ◽  
Protein Protein Interaction

ABSTRACT Hepadnavirus polymerases initiate reverse transcription in a protein-primed reaction. We previously described a complementation assay for analysis of the roles of the TP and RT domains of HBV reverse transcriptase (pol) in the priming reaction. Independently expressed TP and RT domains form a complex functional for in vitro priming reactions. To map the minimal functional TP and RT domains, we prepared baculoviruses expressing amino- and carboxyl-terminal deletions of both the TP and RT domains and analyzed the proteins for the ability to participate in transcomplementation for the priming reaction. The minimal TP domain spanned amino acids 20 to 175; however, very little activity was observed without a TP domain spanning amino acids 1 to 199. The minimal RT domain spanned amino acids 300 to 775; however, little activity was observed unless the carboxyl end of the RT domain extended to amino acid 800. Thus, most of the RNase H domain was required. In previous studies, we observed a TP inhibitory domain between amino acids 199 and 344. The current analysis narrowed this domain to residues 300 to 334, which is a portion of the minimal RT domain. In addition, the ability of TP and RT deletion mutants to form stable TP-RT complexes was examined in coimmunoprecipitation assays. The minimal TP and RT domains capable of protein-protein interaction were considerably smaller than the domains required for functional interaction in the transcomplementation assays, and unlike priming activity, TP-RT interaction did not require the epsilon RNA stem-loop. These studies help to further define the complex protein-protein interactions required in HBV genome replication.

scholarly journals BRET-based RAS biosensors that show a novel small molecule is an inhibitor of RAS-effector protein-protein interactions

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Nicolas Bery ◽  
Abimael Cruz-Migoni ◽  
Carole JR Bataille ◽  
Camilo E Quevedo ◽  
Hanna Tulmin ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Human Cancers ◽  
Ras Family ◽  
Ras Inhibitors ◽  
In Cells

The RAS family of proteins is amongst the most highly mutated in human cancers and has so far eluded drug therapy. Currently, much effort is being made to discover mutant RAS inhibitors and in vitro screening for RAS-binding drugs must be followed by cell-based assays. Here, we have developed a robust set of bioluminescence resonance energy transfer (BRET)-based RAS biosensors that enable monitoring of RAS-effector interaction inhibition in living cells. These include KRAS, HRAS and NRAS and a variety of different mutations that mirror those found in human cancers with the major RAS effectors such as CRAF, PI3K and RALGDS. We highlighted the utility of these RAS biosensors by showing a RAS-binding compound is a potent pan-RAS-effector interactions inhibitor in cells. The RAS biosensors represent a useful tool to investigate and characterize the potency of anti-RAS inhibitors in cells and more generally any RAS protein-protein interaction (PPI) in cells.

scholarly journals Kinetic and subcellular analysis of PS-ASO/protein interactions with P54nrb and RNase H1

2019 ◽  
Vol 47 (20) ◽  
pp. 10865-10880 ◽  
Author(s):  
Timothy A Vickers ◽  
Meghdad Rahdar ◽  
Thazha P Prakash ◽  
Stanley T Crooke
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Catalytic Domain ◽  
Live Cells ◽  
Early Event ◽  
Reporter System ◽  
Protein Protein Interaction ◽  
Domain Interactions ◽  
Specific Proteins

Abstract The rapid RNase H1-dependent mislocalization of heterodimer proteins P54nrb and PSF to nucleoli is an early event in the pathway that explains the effects of most toxic phosphorothioate ASOs (PS-ASOs). Using a recently developed NanoLuciferace (NLuc)-based structural complementation reporter system which allows us to observe ASO/protein interactions in real time in live cells, we have determined that safe and toxic PS-ASOs associate with these proteins with kinetics and impact on subcellular localization that differ. Toxic PS-ASOs interact in a complex that includes RNase H1, P54nrb and PSF; but RNase H1/P54nrb complexes were observed in only the cells treated with toxic, but not safe PS-ASOs. In addition, experiments performed in vitro suggest that RNA is also a required component of the complex. The protein–protein interaction between P54nrb and RNase H1 requires the spacer region of RNAse H1, while the P54nrb core domains are required for association with RNase H1. In addition, we have determined that PS-ASOs bind P54nrb via RRM1 and RRM2, while they bind RNase H1 primarily via the hybrid binding domain, however catalytic domain interactions also contribute to overall affinity. These ASO–protein interactions are highly influenced by the chemistry of the PS-ASO binding environment, however little correlation between affinity for specific proteins and PS-ASO toxicity was observed.

An efficient transient assays system using Agrobacterium-mediated transformation of onion (Allium cepa) epidermal cells

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu
Keyword(s):  
Subcellular Localization ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Epidermal Cells ◽  
Cyclin Dependent Kinase ◽  
Protein Subcellular Localization ◽  
Protein Protein Interactions ◽  
Efficient System ◽  
Protein Protein Interaction ◽  
Onion Epidermal Cells

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.

Furan warheads for covalent trapping of weak protein-protein interactions: cross-linking of thymosin β4 to actin

2021 ◽  
Author(s):  
Laia Miret Casals ◽  
Willem Vannecke ◽  
Kurt Hoogewijs ◽  
Gianluca Arauz ◽  
Marina Gay ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
3D Structure ◽  
Cross Linking ◽  
Thymosin Β4 ◽  
Protein Protein Interactions ◽  
Site Specific ◽  
Protein Protein Interaction ◽  
Covalent Trapping

We describe furan as a triggerable ‘warhead’ for site-specific cross-linking using the actin and thymosin β4 (Tβ4)-complex as model of a weak and dynamic protein-protein interaction with known 3D structure...

scholarly journals Assay Systems for Profiling Deubiquitinating Activity

2020 ◽  
Vol 21 (16) ◽  
pp. 5638
Author(s):  
Jinhong Cho ◽  
Jinyoung Park ◽  
Eunice EunKyeong Kim ◽  
Eun Joo Song
Keyword(s):  
Protein Degradation ◽  
Protein Interactions ◽  
Live Cells ◽  
Deubiquitinating Enzyme ◽  
Protein Protein Interactions ◽  
Deubiquitinating Enzymes ◽  
Cell Lysates ◽  
Cellular Processes

Deubiquitinating enzymes regulate various cellular processes, particularly protein degradation, localization, and protein–protein interactions. The dysregulation of deubiquitinating enzyme (DUB) activity has been linked to several diseases; however, the function of many DUBs has not been identified. Therefore, the development of methods to assess DUB activity is important to identify novel DUBs, characterize DUB selectivity, and profile dynamic DUB substrates. Here, we review various methods of evaluating DUB activity using cell lysates or purified DUBs, as well as the types of probes used in these methods. In addition, we introduce some techniques that can deliver DUB probes into the cells and cell-permeable activity-based probes to directly visualize and quantify DUB activity in live cells. This review could contribute to the development of DUB inhibitors by providing important information on the characteristics and applications of various probes used to evaluate and detect DUB activity in vitro and in vivo.

scholarly journals HMNPPID—human malignant neoplasm protein–protein interaction database

2019 ◽  
Vol 13 (S1) ◽  
Author(s):  
Qingqing Li ◽  
Zhihao Yang ◽  
Zhehuan Zhao ◽  
Ling Luo ◽  
Zhiheng Li ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Malignant Neoplasm ◽  
Biomedical Literature ◽  
Malignant Neoplasms ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Interaction Database ◽  
Protein Interaction Database

Abstract Background Protein–protein interaction (PPI) information extraction from biomedical literature helps unveil the molecular mechanisms of biological processes. Especially, the PPIs associated with human malignant neoplasms can unveil the biology behind these neoplasms. However, such PPI database is not currently available. Results In this work, a database of protein–protein interactions associated with 171 kinds of human malignant neoplasms named HMNPPID is constructed. In addition, a visualization program, named VisualPPI, is provided to facilitate the analysis of the PPI network for a specific neoplasm. Conclusions HMNPPID can hopefully become an important resource for the research on PPIs of human malignant neoplasms since it provides readily available data for healthcare professionals. Thus, they do not need to dig into a large amount of biomedical literatures any more, which may accelerate the researches on the PPIs of malignant neoplasms.

scholarly journals How helpful are the protein-protein interaction databases and which ones?

2019 ◽  
Author(s):  
Akhilesh Kumar Bajpai ◽  
Sravanthi Davuluri ◽  
Kriti Tiwary ◽  
Sithalechumi Narayanan ◽  
Sailaja Oguru ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Web Interfaces ◽  
Protein Protein Interaction ◽  
Usage Frequency ◽  
First Time ◽  
Different Tissues ◽  
The Web

AbstractProtein-protein interactions (PPIs) are critical, and so are the databases and tools (resources) concerning PPIs. But in absence of systematic comparisons, biologists/bioinformaticians may be forced to make a subjective selection among such protein interaction databases and tools. In fact, a comprehensive list of such bioinformatics resources has not been reported so far. For the first time, we compiled 375 PPI resources, short-listed and performed preliminary comparison of 125 important ones (both lists available publicly at startbioinfo.com), and then systematically compared human PPIs from 16 carefully-selected databases. General features have been first compared in detail. The coverage of ‘experimentally verified’ vs. all PPIs, as well as those significant in case of disease-associated and other types of genes among the chosen databases has been compared quantitatively. This has been done in two ways: outputs manually obtained using web-interfaces, and all interactions downloaded from the databases. For the first approach, PPIs obtained in response to gene queries using the web interfaces were compared. As a query set, 108 genes associated with different tissues (specific to kidney, testis, and uterus, and ubiquitous) or diseases (breast cancer, lung cancer, Alzheimer’s, cystic fibrosis, diabetes, and cardiomyopathy) were chosen. PPI-coverage for well-studied genes was also compared with that of less-studied ones. For the second approach, the back-end-data from the databases was downloaded and compared. Based on the results, we recommend the use of STRING and UniHI for retrieving the majority of ‘experimentally verified’ protein interactions, and hPRINT and STRING for obtaining maximum number of ‘total’ (experimentally verified as well as predicted) PPIs. The analysis of experimentally verified PPIs found exclusively in each database revealed that STRING contributed about 71% of exclusive hits. Overall, hPRINT, STRING and IID together retrieved ~94% of ‘total’ protein interactions available in the databases. The coverage of certain databases was skewed for some gene-types. The results also indicate that the database usage frequency may not correlate with their advantages, thereby justifying the need for more frequent studies of this nature.

scholarly journals Feature Design for Protein Interface hotspots using KFC2 and Rosetta

2019 ◽  
Author(s):  
Franziska Seeger ◽  
Anna Little ◽  
Yang Chen ◽  
Tina Woolf ◽  
Haiyan Cheng ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Scoring Function ◽  
Selection Strategy ◽  
Support Vector ◽  
Protein Protein Interactions ◽  
Forward Selection ◽  
Protein Protein Interaction ◽  
Combined Features ◽  
Improved Performance

AbstractProtein-protein interactions regulate many essential biological processes and play an important role in health and disease. The process of experimentally charac-terizing protein residues that contribute the most to protein-protein interaction affin-ity and specificity is laborious. Thus, developing models that accurately characterize hotspots at protein-protein interfaces provides important information about how to inhibit therapeutically relevant protein-protein interactions. During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein-protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics. A 2-way and 3-way forward selection strategy was employed to train support vector machine classifiers, as was a reverse feature elimination strategy. From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.

Sign in / Sign up

Export Citation Format

Share Document