De Novo Design of a Protein Binder to Probe Gas Channel and Enhance the Oxygen Tolerance of [NiFe]‐Hydrogenase

ABSTRACT [NiFe]‐Hydrogenases display remarkable catalytic efficiency for H 2 production and oxidation but are sensitive to O 2 , which severely restricts their biotechnological applications. The identities and functional relevance of gas channels leading to the buried [NiFe] active site remain elusive, hindering rational enzyme engineering. Here, we introduce an artificial intelligence–guided de novo protein binder design strategy to map hydrophobic O 2 diffusion pathways in Escherichia coli hydrogenase‐2 (Hyd‐2). By integrating RFdiffusion, ProteinMPNN, and AlphaFold, ∼100,000 candidate binders were computationally screened, yielding two high‐affinity binders, L1 and L2. Biophysical and electrochemical analyses show that L1 selectively occludes the primary O 2 ingress channel, enhancing the enzyme's oxygen tolerance by more than threefold, whereas L2, which targets another putative channel, has a negligible effect, indicating that this pathway contributes minimally to O 2 ingress under the tested conditions. Furthermore, we determined the L1‐Hyd‐2 complex structure by cryo‐electron microscopy and revealed the key interaction residues and interface conformation. Integrated structural and computational analyses provide mechanistic insights into the system's oxygen tolerance and high‐affinity L1‐Hyd‐2 interaction. All findings provide the first direct experimental evidence for hierarchical O 2 diffusion channels in [NiFe]‐hydrogenases and establish binder‐mediated channel occlusion as a generalizable, mutation‐free strategy for elucidating and modulating gas transport in metalloenzymes.

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Publication Details

Journal
Angewandte Chemie
Published
2026-08-26
DOI
https://doi.org/10.1002/ange.6395554
Primary Topic
Metalloenzymes and iron-sulfur proteins
Type
article
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article

De Novo Design of a Protein Binder to Probe Gas Channel and Enhance the Oxygen Tolerance of [NiFe]‐Hydrogenase

Hang Luo, Yanxin Gao, Leyan Zhang, Wencheng Fu et al.
Angewandte Chemie
Metalloenzymes and iron-sulfur proteins
article

De Novo Design of a Protein Binder to Probe Gas Channel and Enhance the Oxygen Tolerance of [NiFe]‐Hydrogenase

Hang Luo, Yanxin Gao, Leyan Zhang, Wencheng Fu, Liyun Zhang, Wenjin Li, Xuan Sun, Qi xiao, Yucen Huang, Yilin Fan, Nan Zhang, Peiyu Jiang
article en

Abstract

ABSTRACT [NiFe]‐Hydrogenases display remarkable catalytic efficiency for H 2 production and oxidation but are sensitive to O 2 , which severely restricts their biotechnological applications. The identities and functional relevance of gas channels leading to the buried [NiFe] active site remain elusive, hindering rational enzyme engineering. Here, we introduce an artificial intelligence–guided de novo protein binder design strategy to map hydrophobic O 2 diffusion pathways in Escherichia coli hydrogenase‐2 (Hyd‐2). By integrating RFdiffusion, ProteinMPNN, and AlphaFold, ∼100,000 candidate binders were computationally screened, yielding two high‐affinity binders, L1 and L2. Biophysical and electrochemical analyses show that L1 selectively occludes the primary O 2 ingress channel, enhancing the enzyme's oxygen tolerance by more than threefold, whereas L2, which targets another putative channel, has a negligible effect, indicating that this pathway contributes minimally to O 2 ingress under the tested conditions. Furthermore, we determined the L1‐Hyd‐2 complex structure by cryo‐electron microscopy and revealed the key interaction residues and interface conformation. Integrated structural and computational analyses provide mechanistic insights into the system's oxygen tolerance and high‐affinity L1‐Hyd‐2 interaction. All findings provide the first direct experimental evidence for hierarchical O 2 diffusion channels in [NiFe]‐hydrogenases and establish binder‐mediated channel occlusion as a generalizable, mutation‐free strategy for elucidating and modulating gas transport in metalloenzymes.

Angewandte Chemie
Shanghai Jiao Tong University (CN), Nankai University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 27%
Metalloenzymes and iron-sulfur proteins
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