Virus–host protein interactions as footprints of human cytomegalovirus replication

2022 ◽  
Vol 52 ◽  
pp. 135-147
Author(s):  
Matthew D Tyl ◽  
Cora N Betsinger ◽  
Ileana M Cristea
Keyword(s):  
Human Cytomegalovirus ◽  
Protein Interactions ◽  
Host Protein

scholarly journals Crystal Structure of the Human Cytomegalovirus pUL50-pUL53 Core Nuclear Egress Complex Provides Insight into a Unique Assembly Scaffold for Virus-Host Protein Interactions

2015 ◽  
Vol 290 (46) ◽  
pp. 27452-27458 ◽  
Author(s):  
Sascha A. Walzer ◽  
Claudia Egerer-Sieber ◽  
Heinrich Sticht ◽  
Madhumati Sevvana ◽  
Katharina Hohl ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Human Cytomegalovirus ◽  
Protein Interactions ◽  
Host Protein ◽  
Nuclear Egress ◽  
Insight Into

scholarly journals Native Structure-Based Peptides as Potential Protein–Protein Interaction Inhibitors of SARS-CoV-2 Spike Protein and Human ACE2 Receptor

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2157
Author(s):  
Norbert Odolczyk ◽  
Ewa Marzec ◽  
Maria Winiewska-Szajewska ◽  
Jarosław Poznański ◽  
Piotr Zielenkiewicz
Keyword(s):  
Drug Development ◽  
Protein Interactions ◽  
Rna Virus ◽  
Antiviral Drug ◽  
Host Protein ◽  
Host Cells ◽  
Cell Surface Receptor ◽  
Short Peptides ◽  
Virus Protein ◽  
Positive Strand Rna

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus that causes severe respiratory syndrome in humans, which is now referred to as coronavirus disease 2019 (COVID-19). Since December 2019, the new pathogen has rapidly spread globally, with over 65 million cases reported to the beginning of December 2020, including over 1.5 million deaths. Unfortunately, currently, there is no specific and effective treatment for COVID-19. As SARS-CoV-2 relies on its spike proteins (S) to bind to a host cell-surface receptor angiotensin-converting enzyme-2(ACE2), and this interaction is proved to be responsible for entering a virus into host cells, it makes an ideal target for antiviral drug development. In this work, we design three very short peptides based on the ACE2 sequence/structure fragments, which may effectively bind to the receptor-binding domain (RBD) of S protein and may, in turn, disrupt the important virus-host protein–protein interactions, blocking early steps of SARS-CoV-2 infection. Two of our peptides bind to virus protein with affinity in nanomolar range, and as very short peptides have great potential for drug development.

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

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.

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