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Atomic functional site scaffolding in biopolymers with RFdiffusion3

Jasper Butcher, Rohith Krishna, Raktim Mitra, Seth M. Woodbury, Donghyo Kim, Rafael I. Brent, Yanjing Li, Nathaniel Corley, Andrew Favor, An‐Qi Chen, Paul T. Kim, Jonathan Funk, Gabriela Bastidas Reinoso, Kejia Wu, Aiko Muraishi, Helen E. Eisenach, Saman Salike, Simon V. Mathis, Tuscan Rock Thompson, Antonia Ruder, Enisha Sehgal, Andrew Kubaney, Jie Chen, Yuliya Politanska, Brian Coventry, Odin Zhang, Florence J. Hardy, Bo Qiang, Kieran Didi, Maxwell W. Kazman, Lars L. Schaaf, Frank DiMaio, David A. Baker

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Abstract

The catalytic and other sophisticated functions of biomolecules arise from the placement of many atoms in three-dimensional space. Here, we describe a generative artificial intelligence method for biopolymers, RFdiffusion3 (RFD3), which employs free atom diffusion to satisfy complex sets of atomic constraints more rapidly and accurately than previous methods across several challenges from enzyme design to RNA structure design. We demonstrate experimentally the power of the RFD3 pipeline for enzyme design by designing de novo phosphotriesterases with a complex active site architecture incorporating a carbamylated lysine coordinating two metal ions and zinc proteases specific for the transthyretin protein involved in amyloid diseases; in both cases we obtain active catalysts in zero shot 96 construct design campaigns.

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