<p>De novo protein design is of fundamental interest to synthetic biology, with a plethora of computational methods of various degrees of generality developed in recent years. Here, we introduce AlphaDesign, a hallucination-based computational framework for de novo protein design developed with maximum generality and usability in mind, which combines AlphaFold with autoregressive diffusion models to enable rapid generation and computational validation of proteins with controllable interactions, conformations and oligomeric state without the requirement for class-dependent model re-training or fine-tuning. We apply our framework to design and systematically validate in vivo active inhibitors of a family of bacterial phage defense systems with toxic effectors called retrons, paving the way towards efficient, rational design of novel proteins as biologics.</p>

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AlphaDesign: a de novo protein design framework based on AlphaFold

  • Michael A Jendrusch,
  • Alessio L J Yang,
  • Elisabetta Cacace,
  • Jacob Bobonis,
  • Carlos G P Voogdt,
  • Sarah Kaspar,
  • Kristian Schweimer,
  • Cecilia Perez-Borrajero,
  • Karine Lapouge,
  • Jacob Scheurich,
  • Kim Remans,
  • Janosch Hennig,
  • Athanasios Typas,
  • Jan O Korbel,
  • S Kashif Sadiq

摘要

De novo protein design is of fundamental interest to synthetic biology, with a plethora of computational methods of various degrees of generality developed in recent years. Here, we introduce AlphaDesign, a hallucination-based computational framework for de novo protein design developed with maximum generality and usability in mind, which combines AlphaFold with autoregressive diffusion models to enable rapid generation and computational validation of proteins with controllable interactions, conformations and oligomeric state without the requirement for class-dependent model re-training or fine-tuning. We apply our framework to design and systematically validate in vivo active inhibitors of a family of bacterial phage defense systems with toxic effectors called retrons, paving the way towards efficient, rational design of novel proteins as biologics.