Combining devs and semantic technologies for modeling the SARS-COV-2 replication machinery
Abstract
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.
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