A De Novo CO 2 Reductase Featuring a Cysteine-Ligated Cobalt Porphyrin Cofactor
Curated by Papers for Protein Design Using Deep Learning · 6. Function to Structure · 6.3 RoseTTAFold-based
Abstract
Abstract Modern protein design methods based on deep learning allow generation of customized protein scaffolds with diverse geometries and functionalities. Here, we capitalize on these recent advances to develop hyper-thermostable de novo CO 2 reductases featuring a cobalt porphyrin IX cofactor (CoPPIX). CoPPIX containing enzymes were assembled in vivo through media supplementation with cobalt salts and assessed for photocatalytic CO 2 reductase activity. We identified two cysteine-ligated designs that exhibit high activity (>1000 turnovers at rates of up to 25 min -1 ) while suppressing competing hydrogen evolution pathways. A 2.1 Å crystal structure shows close agreement to the design model with the Co-Cys bond programmed as intended. This study showcases the power of computational protein design in developing artificial enzymes to activate challenging molecules such as CO 2 .