Kinetics and Evolution-guided Design of High Fidelity CRISPR-Cas Endonucleases

Abstract

Finding high-fidelity CRISPR-Cas variants is critical for both the precision of in vitro DNA detection and the safety of in vivo gene-editing therapeutics. However, the large size of the Cas enzymes and the distinct selection criteria between its natural evolution and clinical practice lead to extensive experimental trials and limited success rate for de novo design, directed evolution and protein language model (PLM)-based filtering. Here, we present a physics-driven, PLM-assisted approach that utilizes atomistic molecular dynamics simulations and automated path searching to efficiently obtain the atom-level kinetic insights, including the transition state structures, for the conformational changes of R-loop formation that dictate the off-target DNA recognition and cleavage by Cas. We show that these kinetic insights can pinpoint the fidelity-diminishing protein residues during the early stage of target recognition. Integrated with PLM-filtering of the mutants on these sites, this approach identified high-fidelity SpyCas9 and FnCas12a variants (4.49-fold and 6.69-fold increase respectively from wild-type), surpassing previously reported counterparts at minimal cost of only a few wet-lab validations (cellular genome-editing and ribonucleoprotein cleavage assays respectively).