SOURCE-LINKED INTELLIGENCE

Discovery of druggable antiviral targets across viral families through chemical probing

CORDIS · observation · Publication date unknown

c antiviral screening (>350k molecules) against representative, neglected RNA virus families (rhabdo-, alpha-, and bunyaviruses), we will generate rich multiparametric compound fingerprints. Advanced Artificial Intelligence models will be used to exploit the full complexity of the data to guide the selection of molecules that inhibit or modulate viral replication and that are to be used as unique chemical probes. These will then be systematically characterized through complementary methodologies, including genetic mapping, structural modelling and biochemical validation to obtain detailed understanding of their molecular mechanism of action. The outcome will be a first-of-its-kind “Atlas of Druggable Antiviral Targets”, a multidimensional annotation of druggable viral and host targets. Our efforts will expand the antiviral target space, provide new, much needed starting points for (later) target-based drug discovery and hit-to-lead optimization, deepen our understanding of viral replication biology, establish methodologies broadly applicable to other pathogens and ultimately strength

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recordType

award

status

SIGNED

region

EU

value

3302402

unit

EUR