SOURCE-LINKED INTELLIGENCE

AI-driven discovery broad-spectrum antivirals targeting Nucleocytoviricota factories via phase separation modulation

CORDIS · observation · Publication date unknown

is expected to broadly inhibit viral replication while minimizing the development of resistance. This PoC project will design phase-separation grammar-targeting antivirals using AI-driven pipelines. Deep learning models will enable the screening of ultra-large chemical spaces to identify: (i) broad-spectrum inhibitors targeting conserved scaffold proteins across Nucleocytoviricota, and/or (ii) virus-specific antivirals for mpox and ASFV. PSDisrupt’s translational goal is to design and advance lead compounds into preclinical validation and assess their commercial potential. We will: - Discover and design drugs by leveraging high throughput screens and deep learning-based algorithms. - Perform biophysical and cellular assays to validate compound efficacy. - Establish IP protection for novel inhibitors. - Engage with pharmaceutical and biotech partners for licensing and further development. By bridging virology and AI-driven drug design, PSDisrupt pioneers a novel antiviral strategy with broad applications beyond infectious diseases. The AI framework could be adapted to target phase se

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR