Periodic Reporting for period 3 - ProDAP (Protein Dynamics in Antiviral Processes)
Période du rapport: 2022-04-01 au 2023-09-30
Viruses need to enter cells and interact with cellular proteins to replicate and spread.
ProDAP uses proteomics and transcriptomis to identify virus interacting proteins, proteins that change their interaction profile upon virus infection and gene and proteome signatures that are regulated by these interactions. We established essential tools to study virus-host interactions and protocols that allow us to monitor the synthesis and degradation of proteins. Protein interactons and turnover are indications for involvment of the identified proteins in antiviral processes. Besides systematic analysis of the host protein interactions and turnover we apply screens to functionally classify the identified proteins.
We used the established tools to monitor the interactions and effects of SARS-CoV-2 and SARS-CoV interactions (Stulakov et al., Nature, 2021) and could thereby identify functionally relevant interactions and cellular processes that may contribute to antiviral processes. Moreover, we established technology that leverages the identified virus-host interaction data to identify drugs, which may be used for antiviral treatments.
The protocols and scientific insights of ProDAP can be expanded to a wide variety of different viruses with clinicial and socioeconomic importance. Prospectively our work will aid intelligent design of antiviral treatments based on knowledge of the given pathogen.
ProDAP uses proteomics and transcriptomis to identify virus interacting proteins, proteins that change their interaction profile upon virus infection and gene and proteome signatures that are regulated by these interactions. We established essential tools to study virus-host interactions and protocols that allow us to monitor the synthesis and degradation of proteins. Protein interactons and turnover are indications for involvment of the identified proteins in antiviral processes. Besides systematic analysis of the host protein interactions and turnover we apply screens to functionally classify the identified proteins.
We used the established tools to monitor the interactions and effects of SARS-CoV-2 and SARS-CoV interactions (Stulakov et al., Nature, 2021) and could thereby identify functionally relevant interactions and cellular processes that may contribute to antiviral processes. Moreover, we established technology that leverages the identified virus-host interaction data to identify drugs, which may be used for antiviral treatments.
The protocols and scientific insights of ProDAP can be expanded to a wide variety of different viruses with clinicial and socioeconomic importance. Prospectively our work will aid intelligent design of antiviral treatments based on knowledge of the given pathogen.
ProDAP is using proteomics and transcirptomics technologies in order to identify virus-host inteactions. We establsihed essential tools that allow us to monitor the potential interactions of virus-host interactions based on modelled data. Moreover, we established network approaches that enable us to link the interaction of proteins to their potential functions on transcriptional and proteome level. Collectively, our work allows to reconstruct with great detail, how a virus interacts with its host and how these interactions result in cellular responses that are either promoting or inhibiting virus replication. This data can be used to identify hotspots for therapeutic interventions aiming at limiting virus spread or to modulate specific parts of the immune system in order to promote recovery.
Through ProDAP we could establish the most comprehensive SARS-CoV-2 - host interaction network available to date. All data and underlying bioinformatics pipelines are deposited in publically available repositories. We will expand our knoweldge to additional viruses that will further allow discriminate pan-viral from virus-specific events. Moreover we will use these data to propose potential antiviral therapies, which may be promising to be tested in pre-clinical models.