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

  • ACS Omega. 2026 Jul 13;11(29):43300-43308. doi: 10.1021/acsomega.6c01170.
Ageo Miccoli  1 ,  Annabelle Charnock  1 ,  Alexis Denis  2 ,  Euan Fordyce  1 ,  Cameron Franklin  1 ,  Ennys Gheyouche  2 ,  Ian Henderson  1 ,  Christopher Housseman  2 ,  Allan Jordan  1  3 ,  Maxime Laugeois  2 ,  Jean-Christophe Meillon  2 ,  Stuart Onions  3 ,  Quentin Perron  2 ,  Clémentine Pescheteau  2 ,  Emilie Pihan  2 ,  Mark Reeves  1 ,  Kirsty Rooney  1 ,  Hannah Rowlands  1 ,  Nicole Scally  1 ,  Christopher Sleigh  3 ,  Kamaldeep Sumal  3 ,  Franck Le Vaillant  2 ,  Graeme Walker  1
Affiliations
  • 1. Sygnature Discovery Ltd., Alderley Park, Alderley Edge, Cheshire SK10 4TG, U.K.
  • 2. Iktos, 65 Rue de Prony, Paris 75017, France.
  • 3. Sygnature Discovery Ltd., BioCity, Pennyfoot St, Nottingham NG1 1GR, U.K.
PMID: 42540301 DOI: 10.1021/acsomega.6c01170
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 demonstrated only modest biochemical potency, the oxime moietyan unexplored vector in this chemical spaceoffered an opportunity for strategic substitution. Gratifyingly, using this strategy, a highly potent array of functionalized oxime PolQ inhibitors displaying promising initial ADME properties was delivered, underscoring the power of generative AI to unlock new chemical space and accelerate lead optimization.

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