Combining Artificial Intelligence and Human Expertise in Pursuit of Novel PolQ Inhibitors.

Ageo Miccoli¹, Annabelle Charnock¹, Alexis Denis², Euan Fordyce¹, Cameron Franklin¹, Ennys Gheyouche², Ian Henderson¹, Christopher Housseman², Allan Jordan^1,3, Maxime Laugeois², Jean-Christophe Meillon², Stuart Onions³, Quentin Perron², Clémentine Pescheteau², Emilie Pihan², Mark Reeves¹, Kirsty Rooney¹, Hannah Rowlands¹, Nicole Scally¹, Christopher Sleigh³, Kamaldeep Sumal³, Franck Le Vaillant², Graeme Walker¹

¹Sygnature Discovery Ltd., Alderley Park, Alderley Edge, Cheshire SK10 4TG, U.K.

²Iktos, 65 Rue de Prony, Paris 75017, France.

³Sygnature Discovery Ltd., BioCity, Pennyfoot St, Nottingham NG1 1GR, U.K.

PubMed PMC DOI PDF

Abstract

Application of generative AI, synergistically with traditional knowledge-based approaches, has expedited the discovery of small-molecule PolQ polymerase domain inhibitors. Leveraging AI-generated ligand designs, a structurally diverse set of compounds were synthesized and evaluated, ultimately identifying a novel oxime-based scaffold as a promising starting point. Although the initial hit demonstr…

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