51. Combining devs and semantic technologies for modeling the SARS-COV-2 replication machinery
- Author
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Ali Ayadi, Emeline Grellet, Claudia Frydman, Cecilia Zanni-Merk, Lina Fatima Soualmia, Wissame Laddada, India L'Hote, Isabelle Imbert, Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes (LITIS), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), Architecture et fonction des macromolécules biologiques (AFMB), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Modèles et Formalismes à Evénements Discrets (MOFED), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), and ANR-20-COVI-0006,PullCoVapart,Neutraliser le COVID-19 en s'attaquant à son cœur catalytique pour sa réplication(2020)
- Subjects
DEVS ,SARS-CoV-2 replication machinery ,Computer science ,ontology-based model ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,viruses ,discrete event system specification ,COVID-19 ,Computational biology ,computer.software_genre ,Hybrid approach ,Ontology engineering ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,Replication (computing) ,Viral replication ,modeling and simulation ,Infected cell ,Semantic technology ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,computer ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience; The search for inhibitors of SARS-CoV-2 viral replication depends on the understanding of the events taking place at different molecular levels during the viral infection. The macro-molecular level focuses on the interactions among viral and host proteins, while the micro-molecular level focuses on the different biochemical modifications that occur to one or more amino acids on proteins. A hybrid approach for modeling the SARS-CoV-2 viral replication in the micro-and macro-molecular levels is presented in this paper. The proposed approach combines two domains which complement one another, ontology engineering and discrete event system specification (DEVS) modeling.In this approach, biological knowledge at the micro-level of the viral system is capitalized and inferred by ontological models, while the dynamic behavior of SARS-CoV-2 molecular mechanisms and their different state changes in time are modeled by DEVS models. We illustrate the proposed approach through the modeling and simulation of the ribosome, a key molecule of the host cell that all viruses compete for, including the SARS-CoV-2.
- Published
- 2021