A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome

Segura‐Cabrera, Aldo; García-Pérez, Carlos A.; Guo, Xianwu; Rodríguez‐Pérez, Mario A.

doi:10.1371/journal.pone.0071526

Cited by 27 publications

(15 citation statements)

References 87 publications

(107 reference statements)

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“…PPIs commonly rely on large interfaces, whilst transient ones involve short linear peptides, as sequence motifs composed of 15 residues or less (Segura-Cabrera et al, 2013 ). Proteins that show a wide range of binding partners are called “hubs.” Hubs having only few interfaces are likely to interact transiently with different partners at different times (date hubs; Han et al, 2004 ), usually via domain–motif interactions (Franzosa and Xia, 2011 ).…”

Section: Modes Of Protein Interactionmentioning

confidence: 99%

Protein–Protein Interactions in Virus–Host Systems

2017

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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.

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Section: Modes Of Protein Interactionmentioning

confidence: 99%

Protein–Protein Interactions in Virus–Host Systems

2017

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“…The lack of gold standard PHI data and the complexity of PHI mechanisms lead to a hard assessment phase, in a way that predicted interactions are rarely supported by a biological basis. Some studies validate their results by measuring the shared interactions with other published materials (Mukhopadhyay et al, 2012 , 2014 ; Segura-Cabrera et al, 2013 ). Here we focus on computational metrics which are widely used in publications to evaluate the accuracy of their results, which are shown in Table 6 .…”

Section: Performance Evaluationmentioning

confidence: 89%

Computational approaches for prediction of pathogen-host protein-protein interactions

2015

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Infectious diseases are still among the major and prevalent health problems, mostly because of the drug resistance of novel variants of pathogens. Molecular interactions between pathogens and their hosts are the key parts of the infection mechanisms. Novel antimicrobial therapeutics to fight drug resistance is only possible in case of a thorough understanding of pathogen-host interaction (PHI) systems. Existing databases, which contain experimentally verified PHI data, suffer from scarcity of reported interactions due to the technically challenging and time consuming process of experiments. These have motivated many researchers to address the problem by proposing computational approaches for analysis and prediction of PHIs. The computational methods primarily utilize sequence information, protein structure and known interactions. Classic machine learning techniques are used when there are sufficient known interactions to be used as training data. On the opposite case, transfer and multitask learning methods are preferred. Here, we present an overview of these computational approaches for predicting PHI systems, discussing their weakness and abilities, with future directions.

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“…Their study shows that the majority of conserved linear motifs in the virus are located in disordered regions. In [32], Segura et al proposed a method to model viral-human interaction network using motif-domain interactions.…”

Section: Computational Approachesmentioning

confidence: 99%

Review of computational methods for virus–host protein interaction prediction: a case study on novel Ebola–human interactions

Dutta

Kundu

Basu

et al. 2017

Briefings in Functional Genomics

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Identification of potential virus-host interactions is useful and vital to control the highly infectious virus-caused diseases. This may contribute toward development of new drugs to treat the viral infections. Recently, database records of clinically and experimentally validated interactions between a small set of human proteins and Ebola virus (EBOV) have been published. Using the information of the known human interaction partners of EBOV, our main objective is to identify a set of proteins that may interact with EBOV proteins. Here, we first review the state-of-the-art, computational methods used for prediction of novel virus-host interactions for infectious diseases followed by a case study on EBOV-human interactions. The assessment result shows that the predicted human host proteins are highly similar with known human interaction partners of EBOV in the context of structure and semantics and are responsible for similar biochemical activities, pathways and host-pathogen relationships.

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A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome

Cited by 27 publications

References 87 publications

Protein–Protein Interactions in Virus–Host Systems

Protein–Protein Interactions in Virus–Host Systems

Computational approaches for prediction of pathogen-host protein-protein interactions

Review of computational methods for virus–host protein interaction prediction: a case study on novel Ebola–human interactions

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