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Idrees S, Paudel KR, Hansbro PM. Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions. Arch Microbiol 2024; 206:94. [PMID: 38334822 PMCID: PMC10858152 DOI: 10.1007/s00203-024-03832-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/01/2024] [Accepted: 01/02/2024] [Indexed: 02/10/2024]
Abstract
One of the mechanisms viruses use in hijacking host cellular machinery is mimicking Short Linear Motifs (SLiMs) in host proteins to maintain their life cycle inside host cells. In the face of the escalating volume of virus-host protein-protein interactions (vhPPIs) documented in databases; the accurate prediction of molecular mimicry remains a formidable challenge due to the inherent degeneracy of SLiMs. Consequently, there is a pressing need for computational methodologies to predict new instances of viral mimicry. Our present study introduces a DMI-de-novo pipeline, revealing that vhPPIs catalogued in the VirHostNet3.0 database effectively capture domain-motif interactions (DMIs). Notably, both affinity purification coupled mass spectrometry and yeast two-hybrid assays emerged as good approaches for delineating DMIs. Furthermore, we have identified new vhPPIs mediated by SLiMs across different viruses. Importantly, the de-novo prediction strategy facilitated the recognition of several potential mimicry candidates implicated in the subversion of host cellular proteins. The insights gleaned from this research not only enhance our comprehension of the mechanisms by which viruses co-opt host cellular machinery but also pave the way for the development of novel therapeutic interventions.
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Affiliation(s)
- Sobia Idrees
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia.
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and the University of Technology Sydney, Sydney, NSW, Australia.
| | - Keshav Raj Paudel
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and the University of Technology Sydney, Sydney, NSW, Australia
| | - Philip M Hansbro
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and the University of Technology Sydney, Sydney, NSW, Australia
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Kumar M, Michael S, Alvarado-Valverde J, Zeke A, Lazar T, Glavina J, Nagy-Kanta E, Donagh J, Kalman Z, Pascarelli S, Palopoli N, Dobson L, Suarez C, Van Roey K, Krystkowiak I, Griffin J, Nagpal A, Bhardwaj R, Diella F, Mészáros B, Dean K, Davey N, Pancsa R, Chemes L, Gibson T. ELM-the Eukaryotic Linear Motif resource-2024 update. Nucleic Acids Res 2024; 52:D442-D455. [PMID: 37962385 PMCID: PMC10767929 DOI: 10.1093/nar/gkad1058] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/22/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.
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Affiliation(s)
- Manjeet Kumar
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
| | - Sushama Michael
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
| | - Jesús Alvarado-Valverde
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
- Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, Germany
| | - András Zeke
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - Tamas Lazar
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie, Pleinlaan 2, 1050 Brussels, Belgium
- Structural Biology Brussels, Department of Bioengineering, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
| | - Juliana Glavina
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CP 1650, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad Nacional de San Martín, Av. 25 de Mayo y Francia, CP1650 San Martín, Buenos Aires, Argentina
| | - Eszter Nagy-Kanta
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, Budapest 1083, Hungary
| | - Juan Mac Donagh
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bernal, Buenos Aires, Argentina
| | - Zsofia E Kalman
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, Budapest 1083, Hungary
| | - Stefano Pascarelli
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Nicolas Palopoli
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bernal, Buenos Aires, Argentina
| | - László Dobson
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
- Department of Bioinformatics, Semmelweis University, Tűzoltó u. 7, Budapest 1094, Hungary
| | - Carmen Florencia Suarez
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CP 1650, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad Nacional de San Martín, Av. 25 de Mayo y Francia, CP1650 San Martín, Buenos Aires, Argentina
| | - Kim Van Roey
- Health Services Research, Sciensano, Brussels, Belgium
| | - Izabella Krystkowiak
- Institute of Cancer Research, Chester Beatty Laboratories, 237 Fulham Rd, Chelsea, London SW3 6JB, UK
| | - Juan Esteban Griffin
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bernal, Buenos Aires, Argentina
| | - Anurag Nagpal
- Department of Biological Sciences, BITS Pilani, K. K. Birla Goa campus, Zuarinagar, Goa 403726, India
| | - Rajesh Bhardwaj
- Inselspital, University of Bern, Freiburgstrasse 15, CH-3010 Bern, Switzerland
| | - Francesca Diella
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
| | - Bálint Mészáros
- Department of Structural Biology and Center of Excellence for Data Driven Discovery, St Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Kellie Dean
- School of Biochemistry and Cell Biology, 3.91 Western Gateway Building, University College Cork, Cork, Ireland
| | - Norman E Davey
- Institute of Cancer Research, Chester Beatty Laboratories, 237 Fulham Rd, Chelsea, London SW3 6JB, UK
| | - Rita Pancsa
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - Lucía B Chemes
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CP 1650, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad Nacional de San Martín, Av. 25 de Mayo y Francia, CP1650 San Martín, Buenos Aires, Argentina
| | - Toby J Gibson
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
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Idrees S, Paudel KR, Sadaf T, Hansbro PM. How different viruses perturb host cellular machinery via short linear motifs. EXCLI JOURNAL 2023; 22:1113-1128. [PMID: 38054205 PMCID: PMC10694346 DOI: 10.17179/excli2023-6328] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/18/2023] [Indexed: 12/07/2023]
Abstract
The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.
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Affiliation(s)
- Sobia Idrees
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
- Centre for Inflammation, Centenary Institute and the University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, New South Wales, Australia
| | - Keshav Raj Paudel
- Centre for Inflammation, Centenary Institute and the University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, New South Wales, Australia
| | - Tayyaba Sadaf
- Centre for Inflammation, Centenary Institute and the University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, New South Wales, Australia
| | - Philip M. Hansbro
- Centre for Inflammation, Centenary Institute and the University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, New South Wales, Australia
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