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PreprintCC BYChemRxiv

De novo design of photoenzymes with substrate-recognition-encoded enantioselectivity

  • Zehui Wang1,2
  • Yangjinxiu Zhou1,2
  • Yunhao Li3,4
  • Guojiao Wu1,2
  • Mengwen Shi5,6
  • Siyuan Wang5,6
  • Tengfei Pang1,2
  • Yuqi Peng1,2
  • Jundi Guo1,2
  • Huiyi Zhou1,2
  • Yingru Xu1,2
  • Hongmei Liu1,2
5 more authors
  • Mowei Zhou3,4
  • Xi Chen5,6
  • Pengfei Ji3,4
  • Fangrui Zhong1,2
  • Yuzhou Wu1,2,7,8
8 affiliations
  1. 1State Key Laboratory of Materials Processing and Die and Mould Technology, Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, National Engineering Research Center for Nanomedicine, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering
  2. 2Huazhong University of Science and Technology (HUST
  3. 3Department of Chemistry, Zhejiang Key Laboratory of Low-Carbon Synthesis of Value-Added Chemicals
  4. 4Zhejiang University
  5. 5Key Laboratory of Synthetic and Natural Functional Molecule of the Ministry of Education, College of Chemistry and Materials Science
  6. 6Northwest University
  7. 7Union Hospital
  8. 8Tongji Medical College
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Abstract

Photoenzymes enable stereoselective excited-state transformations beyond the chemical space accessible to natural enzymes, yet their development remains largely dependent on repurposing few privileged protein scaffolds and extensive directed evolution. Although de novo protein design enables tailor-made catalytic architectures, its prevailing transition-state stabilization paradigm is not readily transferable to photoenzymes. Here we establish a substrate-recognition-guided strategy for de novo photoenzyme design, in which the computational construction of substrate-tailored catalytic environments determines stereoselectivity and the genetic incorporation of abiotic thioxanthone photosensitizer endows excited-state reactivity. This approach generated customized photoenzymes for the deracemization of 4-alkenylcyclohexanols that exhibit nanomolar substrate affinity, catalytic efficiencies exceeding 1.5 × 105 M-1 s-1, and up to 99% enantiomeric excess. Crystal structure and kinetic analyses validate the designed model, revealing substrate-recognition-dependent enantioselective energy transfer within the tailored active site. This work establishes substrate recognition as a general design principle for extending de novo enzyme design to excited-state biocatalysis.

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Cite

BibTeXRIS
BibTeX
@misc{wang2026novo,
  title = {{De novo design of photoenzymes with substrate-recognition-encoded enantioselectivity}},
  author = {Zehui Wang and Yangjinxiu Zhou and Yunhao Li and Guojiao Wu and Mengwen Shi and Siyuan Wang and Tengfei Pang and Yuqi Peng and Jundi Guo and Huiyi Zhou and Yingru Xu and Hongmei Liu and Mowei Zhou and Xi Chen and Pengfei Ji and Fangrui Zhong and Yuzhou Wu},
  howpublished = {ChemRxiv},
  year = {2026},
  month = oct,
  doi = {10.26434/chemrxiv.15010510/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010510/v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - De novo design of photoenzymes with substrate-recognition-encoded enantioselectivity
AU  - Zehui Wang
AU  - Yangjinxiu Zhou
AU  - Yunhao Li
AU  - Guojiao Wu
AU  - Mengwen Shi
AU  - Siyuan Wang
AU  - Tengfei Pang
AU  - Yuqi Peng
AU  - Jundi Guo
AU  - Huiyi Zhou
AU  - Yingru Xu
AU  - Hongmei Liu
AU  - Mowei Zhou
AU  - Xi Chen
AU  - Pengfei Ji
AU  - Fangrui Zhong
AU  - Yuzhou Wu
PY  - 2026
DA  - 2026/10/15
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15010510/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010510/v1
AB  - Photoenzymes enable stereoselective excited-state transformations beyond the chemical space accessible to natural enzymes, yet their development remains largely dependent on repurposing few privileged protein scaffolds and extensive directed evolution. Although de novo protein design enables tailor-made catalytic architectures, its prevailing transition-state stabilization paradigm is not readily transferable to photoenzymes. Here we establish a substrate-recognition-guided strategy for de novo photoenzyme design, in which the computational construction of substrate-tailored catalytic environments determines stereoselectivity and the genetic incorporation of abiotic thioxanthone photosensitizer endows excited-state reactivity. This approach generated customized photoenzymes for the deracemization of 4-alkenylcyclohexanols that exhibit nanomolar substrate affinity, catalytic efficiencies exceeding 1.5 × 105 M-1 s-1, and up to 99% enantiomeric excess. Crystal structure and kinetic analyses validate the designed model, revealing substrate-recognition-dependent enantioselective energy transfer within the tailored active site. This work establishes substrate recognition as a general design principle for extending de novo enzyme design to excited-state biocatalysis.
ER  -