ArticleBMC bioinformatics2017
Prediction of virus-host protein-protein interactions mediated by short linear motifs.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- The evolutionary dynamics between viral mimics and host proteins.Molecular systems biology · 2026Article
- Functional and Structural Determinants of Long- and Short-Term Evolution of Herpesvirus Proteins.Molecular biology and evolution · 2025Article
- Predicting Motif-Mediated Interactions Based on Viral Genomic Composition.International journal of molecular sciences · 2025Article
- mimicINT: A workflow for microbe-host protein interaction inference.F1000Research · 2025Article
- Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions.Archives of microbiology · 2024Article
- Computational Network Inference for Bacterial Interactomics.mSystems · 2022Review
- In silico prediction of HIV-1-host molecular interactions and their directionality.PLoS computational biology · 2022Article
- Host-pathogen protein-nucleic acid interactions: A comprehensive review.Computational and structural biotechnology journal · 2022Review
- Machine Learning and Its Applications for Protozoal Pathogens and Protozoal Infectious Diseases.Frontiers in cellular and infection microbiology · 2022Review
- Dynamic, but Not Necessarily Disordered, Human-Virus Interactions Mediated through SLiMs in Viral Proteins.Viruses · 2021Review
- Elucidating the network features and evolutionary attributes of intra- and interspecific protein-protein interactions between human and pathogenic bacteria.Scientific reports · 2021Article
- Structural determinants driving the binding process between PDZ domain of wild type human PALS1 protein and SLiM sequences of SARS-CoV E proteins.Computational and structural biotechnology journal · 2021Article
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- ML-AdVInfect: A Machine-Learning Based Adenoviral Infection Predictor.Frontiers in molecular biosciences · 2021Article
- Integrative Network Biology Framework Elucidates Molecular Mechanisms of SARS-CoV-2 Pathogenesis.iScience · 2020Article
- HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry.Journal of molecular biology · 2020Article
- Integrative Network Biology Framework Elucidates Molecular Mechanisms of SARS-CoV-2 Pathogenesis.SSRN · 2020Article
- Predicting host taxonomic information from viral genomes: A comparison of feature representations.PLoS computational biology · 2020Article
- Resources to Discover and Use Short Linear Motifs in Viral Proteins.Trends in biotechnology · 2020Review
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3 authors.
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Abstract
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.
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