Peer-Reviewed Publication
Sci Adv2026;12(41):eaeh3246.October 9, 2026Journal Article
Machine learning-assisted directed evolution of plant Rubisco.
Julie L McDonald1,2, Jiacheng Lin1, Yunlong Zhao1, Brian L Hie3,4, Rosemary Birch5, Mary Gehring2,6,7,8, Bryan D Bryson7,9, Spencer M Whitney5, Matthew D Shoulders1,10,11, Robert H Wilson1
1Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
2Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
3Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA.
4Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
5Plant Science Division, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia.
6Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA.
7Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
8Howard Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA.
9Ragon Institute of Massachusetts General Hospital, Harvard, and MIT, Cambridge, MA 02139, USA.
10Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
11Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA 02141, USA.
Abstract
Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is foundational to life on Earth, catalyzing carbon dioxide (CO2) fixation to generate biomass. However, Rubisco is a slow and inefficient enzyme that has proven challenging to engineer. We applied the structure-informed machine learning (ML) model ESM-IF1 to identify plausible amino acid sites in the large subunit of Nicotiana tabacum Rubi…
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