scholarly journals A Quantitative Live-Cell Superresolution Imaging Framework for Measuring the Mobility of Single Molecules at Sites of Virus Assembly

Pathogens ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 972
Author(s):  
Nicholas S. Groves ◽  
Merissa M. Bruns ◽  
Schuyler B. van Engelenburg
Keyword(s):  
Protein Interactions ◽  
Virus Assembly ◽  
Live Cell ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Resolution Limit ◽  
Superresolution Microscopy ◽  
Superresolution Imaging ◽  
Time Invariant ◽  
Hiv 1

The insurgence of superresolution microscopy into the fields of virology and microbiology has begun to enable the mapping of molecular assemblies critical for host–pathogen interfaces that organize on a scale below the resolution limit of the light microscope. It is, however, challenging to completely understand the molecular interactions between host and pathogen from strictly time-invariant observations. Herein, we describe a method using simultaneous dual-color superresolution microscopy to gain both structural and dynamic information about HIV-1 assembly. Specifically, we demonstrate the reconstruction of single virus assembly sites using live-cell photo-activated localization microscopy (PALM) while concurrently assessing the sub-viral mobility of the HIV-1 envelope glycoprotein during interaction with the viral lattice. We propose that our method is broadly applicable to elucidating pathogen and host protein–protein interactions through quantification of the dynamics of these proteins at the nanoscale.

Quantitative analysis of the interactions between HIV-1 integrase and retroviral reverse transcriptases

2008 ◽  
Vol 412 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Alon Herschhorn ◽  
Iris Oz-Gleenberg ◽  
Amnon Hizi
Keyword(s):  
Conformational Changes ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Reaction Model ◽  
Protein Protein Interactions ◽  
Common Site ◽  
Leukaemia Virus ◽  
Reverse Transcriptases ◽  
Interaction Kinetics ◽  
Hiv 1

The RT (reverse transcriptase) of HIV-1 interacts with HIV-1 IN (integrase) and inhibits its enzymatic activities. However, the molecular mechanisms underling these interactions are not well understood. In order to study these mechanisms, we have analysed the interactions of HIV-1 IN with HIV-1 RT and with two other related RTs: those of HIV-2 and MLV (murine-leukaemia virus). All three RTs inhibited HIV-1 IN, albeit to a different extent, suggesting a common site of binding that could be slightly modified for each one of the studied RTs. Using surface plasmon resonance technology, which monitors direct protein–protein interactions, we performed kinetic analyses of the binding of HIV-1 IN to these three RTs and observed interesting binding patterns. The interaction of HIV-1 RT with HIV-1 IN was unique and followed a two-state reaction model. According to this model, the initial IN–RT complex formation was followed by a conformational change in the complex that led to an elevation of the total affinity between these two proteins. In contrast, HIV-2 and MLV RTs interacted with IN in a simple bi-molecular manner, without any apparent secondary conformational changes. Interestingly, HIV-1 and HIV-2 RTs were the most efficient inhibitors of HIV-1 IN activity, whereas HIV-1 and MLV RTs showed the highest affinity towards HIV-1 IN. These modes of direct protein interactions, along with the apparent rate constants calculated and the correlations of the interaction kinetics with the capacity of the RTs to inhibit IN activities, are all discussed.

Peptides that inhibit HIV-1 integrase by blocking its protein-protein interactions

FEBS Journal ◽  
2012 ◽  
Vol 279 (16) ◽  
pp. 2795-2809 ◽  
Author(s):  
Michal Maes ◽  
Abraham Loyter ◽  
Assaf Friedler
Keyword(s):  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Hiv 1

scholarly journals A Field-Proven Yeast Two-Hybrid Protocol Used to Identify Coronavirus–Host Protein–Protein Interactions

2015 ◽  
pp. 213-229 ◽  
Author(s):  
Pierre-Olivier Vidalain ◽  
Yves Jacob ◽  
Marne C. Hagemeijer ◽  
Louis M. Jones ◽  
Grégory Neveu ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Two Hybrid

scholarly journals Chemical toolbox for ‘live’ biochemistry to understand enzymatic functions in living systems

2019 ◽  
Author(s):  
Toru Komatsu ◽  
Yasuteru Urano
Keyword(s):  
Environmental Factors ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Live Cell ◽  
Living Systems ◽  
Protein Protein Interactions ◽  
Redox States ◽  
Recent Advances ◽  
Protein Functions ◽  
Research Tools

Abstract In this review, we present an overview of the recent advances in chemical toolboxes that are used to provide insights into ‘live’ protein functions in living systems. Protein functions are mediated by various factors inside of cells, such as protein−protein interactions, posttranslational modifications, and they are also subject to environmental factors such as pH, redox states and crowding conditions. Obtaining a true understanding of protein functions in living systems is therefore a considerably difficult task. Recent advances in research tools have allowed us to consider ‘live’ biochemistry as a valid approach to precisely understand how proteins function in a live cell context.

Targeting Virus-host Protein Interactions: Feature Extraction and Machine Learning Approaches

2019 ◽  
Vol 20 (3) ◽  
pp. 177-184 ◽  
Author(s):  
Nantao Zheng ◽  
Kairou Wang ◽  
Weihua Zhan ◽  
Lei Deng
Keyword(s):  
Machine Learning ◽  
Computational Methods ◽  
Protein Interactions ◽  
Prediction Models ◽  
Learning Algorithms ◽  
Biological Data ◽  
Machine Learning Algorithms ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Protein Motifs

Background:Targeting critical viral-host Protein-Protein Interactions (PPIs) has enormous application prospects for therapeutics. Using experimental methods to evaluate all possible virus-host PPIs is labor-intensive and time-consuming. Recent growth in computational identification of virus-host PPIs provides new opportunities for gaining biological insights, including applications in disease control. We provide an overview of recent computational approaches for studying virus-host PPI interactions.Methods:In this review, a variety of computational methods for virus-host PPIs prediction have been surveyed. These methods are categorized based on the features they utilize and different machine learning algorithms including classical and novel methods.Results:We describe the pivotal and representative features extracted from relevant sources of biological data, mainly include sequence signatures, known domain interactions, protein motifs and protein structure information. We focus on state-of-the-art machine learning algorithms that are used to build binary prediction models for the classification of virus-host protein pairs and discuss their abilities, weakness and future directions.Conclusion:The findings of this review confirm the importance of computational methods for finding the potential protein-protein interactions between virus and host. Although there has been significant progress in the prediction of virus-host PPIs in recent years, there is a lot of room for improvement in virus-host PPI prediction.

scholarly journals Analysis of Vaccinia Virus−Host Protein−Protein Interactions: Validations of Yeast Two-Hybrid Screenings

2009 ◽  
Vol 8 (9) ◽  
pp. 4311-4318 ◽  
Author(s):  
Leiliang Zhang ◽  
Nancy Y. Villa ◽  
Masmudur M. Rahman ◽  
Sherin Smallwood ◽  
Donna Shattuck ◽  
...  
Keyword(s):  
Vaccinia Virus ◽  
Protein Interactions ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Two Hybrid
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