Dataset Information

Protein-Protein Interactions in Virus-Host Systems.

ABSTRACT: To study virus-host protein interactions, knowledge about viral and host protein architectures and repertoires, their particular evolutionary mechanisms, and information on relevant sources of biological data is essential. The purpose of this review article is to provide a thorough overview about these aspects. Protein domains are basic units defining protein interactions, and the uniqueness of viral domain repertoires, their mode of evolution, and their roles during viral infection make viruses interesting models of study. Mutations at protein interfaces can reduce or increase their binding affinities by changing protein electrostatics and structural properties. During the course of a viral infection, both pathogen and cellular proteins are constantly competing for binding partners. Endogenous interfaces mediating intraspecific interactions-viral-viral or host-host interactions-are constantly targeted and inhibited by exogenous interfaces mediating viral-host interactions. From a biomedical perspective, blocking such interactions is the main mechanism underlying antiviral therapies. Some proteins are able to bind multiple partners, and their modes of interaction define how fast these "hub proteins" evolve. "Party hubs" have multiple interfaces; they establish simultaneous/stable (domain-domain) interactions, and tend to evolve slowly. On the other hand, "date hubs" have few interfaces; they establish transient/weak (domain-motif) interactions by means of short linear peptides (15 or fewer residues), and can evolve faster. Viral infections are mediated by several protein-protein interactions (PPIs), which can be represented as networks (protein interaction networks, PINs), with proteins being depicted as nodes, and their interactions as edges. It has been suggested that viral proteins tend to establish interactions with more central and highly connected host proteins. In an evolutionary arms race, viral and host proteins are constantly changing their interface residues, either to evade or to optimize their binding capabilities. Apart from gaining and losing interactions via rewiring mechanisms, virus-host PINs also evolve via gene duplication (paralogy); conservation (orthology); horizontal gene transfer (HGT) (xenology); and molecular mimicry (convergence). The last sections of this review focus on PPI experimental approaches and their limitations, and provide an overview of sources of biomolecular data for studying virus-host protein interactions.

SUBMITTER: Brito AF

PROVIDER: S-EPMC5562681 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Protein-Protein Interactions in Virus-Host Systems.

Brito Anderson F AF Pinney John W JW

Frontiers in microbiology 20170817

To study virus-host protein interactions, knowledge about viral and host protein architectures and repertoires, their particular evolutionary mechanisms, and information on relevant sources of biological data is essential. The purpose of this review article is to provide a thorough overview about these aspects. Protein domains are basic units defining protein interactions, and the uniqueness of viral domain repertoires, their mode of evolution, and their roles during viral infection make viruses ...[more]

PMID: 28861068

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Project description:BackgroundShort linear motifs in host organisms proteins can be mimicked by viruses to create protein-protein interactions that disable or control metabolic pathways. Given that viral linear motif instances of host motif regular expressions can be found by chance, it is necessary to develop filtering methods of functional linear motifs. We conduct a systematic comparison of linear motifs filtering methods to develop a computational approach for predicting motif-mediated protein-protein interactions between human and the human immunodeficiency virus 1 (HIV-1).ResultsWe implemented three filtering methods to obtain linear motif sets: 1) conserved in viral proteins (C), 2) located in disordered regions (D) and 3) rare or scarce in a set of randomized viral sequences (R). The sets C,D,R are united and intersected. The resulting sets are compared by the number of protein-protein interactions correctly inferred with them - with experimental validation. The comparison is done with HIV-1 sequences and interactions from the National Institute of Allergy and Infectious Diseases (NIAID). The number of correctly inferred interactions allows to rank the interactions by the sets used to deduce them: D∪R and C. The ordering of the sets is descending on the probability of capturing functional interactions. With respect to HIV-1, the sets C∪R, D∪R, C∪D∪R infer all known interactions between HIV1 and human proteins mediated by linear motifs. We found that the majority of conserved linear motifs in the virus are located in disordered regions.ConclusionWe have developed a method for predicting protein-protein interactions mediated by linear motifs between HIV-1 and human proteins. The method only use protein sequences as inputs. We can extend the software developed to any other eukaryotic virus and host in order to find and rank candidate interactions. In future works we will use it to explore possible viral attack mechanisms based on linear motif mimicry.

Project description:Arthropod-borne viruses, such as the members of the genus Alphavirus, are a significant concern to global public health. As obligate intracellular pathogens, RNA viruses must interact with the host cell machinery to establish and complete their life cycles. Despite considerable efforts to define the host-pathogen interactions essential for alphaviral replication, an unbiased and inclusive assessment of alphaviral RNA-protein interactions has not been undertaken. Moreover, the biological and molecular importance of these interactions, in the full context of their molecular function as RNA-binding proteins, has not been fully realized. The data presented here introduce a robust viral RNA-protein discovery method to elucidate the Sindbis virus (SINV) RNA-protein host interface. Cross-link-assisted mRNP purification (CLAMP) assessment revealed an extensive array of host-pathogen interactions centered on the viral RNAs (vRNAs). After prioritization of the host proteins associated with the vRNAs, we identified the site of protein-vRNA interaction by a UV cross-linking and immunoprecipitation sequencing (CLIP-seq) approach and assessed the consequences of the RNA-protein binding event of hnRNP K, hnRNP I, and hnRNP M in regard to viral infection. Here, we demonstrate that mutation of the prioritized hnRNP-vRNA interaction sites effectively disrupts hnRNP-vRNA interaction. Correlating with disrupted hnRNP-vRNA binding, SINV growth kinetics were reduced relative to wild-type parental viral infections in vertebrate and invertebrate tissue culture models of infection. The molecular mechanism leading to reduced viral growth kinetics was found to be dysregulated structural-gene expression. Collectively, this study further defines the scope and importance of the alphavirus host-pathogen vRNA-protein interactions.IMPORTANCE Members of the genus Alphavirus are widely recognized for their potential to cause severe disease. Despite this recognition, there are no antiviral therapeutics, or safe and effective vaccines, currently available to treat alphaviral infection. Alphaviruses utilize the host cell machinery to efficiently establish and complete their life cycle. However, the extent and importance of host-pathogen RNA-protein interactions are woefully undercharacterized. The efforts detailed in this study fill this critical gap, and the significance of this research is 3-fold. First, the data presented here fundamentally expand the scope and understanding of alphavirus host-pathogen interactions. Second, this study identifies the sites of interaction for several prioritized interactions and defines the contribution of the RNA-protein interaction at the molecular level. Finally, these studies build a strategy by which the importance of the given host-pathogen interactions may be assessed in the future, using a mouse model of infection.

Dataset Information

Protein-Protein Interactions in Virus-Host Systems.

Publications

Protein-Protein Interactions in Virus-Host Systems.

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