Structure and evolution-guided design of minimal RNA-guided nucleases
TL;DR
A protein design strategy is used that couples a structure-guided inverse-folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs, establishing a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.
Abstract
The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome editing capabilities. However, generating diverse multi-domain proteins with robust enzymatic properties remains challenging. Here we use a protein design strategy that couples a structure-guided inverse folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs. High-throughput screening of AI-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant and human cells. Cryo-EM-based structure determination of the most divergent variant revealed new stabilizing contacts in the RNA/DNA interfaces across conformations, demonstrating the design potential of this approach. Together these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.