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

[NiFe]-hydrogenases exhibit outstanding catalytic performance for H2 production and oxidation but suffer from extreme O2 sensitivity, limiting their biotechnological potential. The identity and functional roles of gas channels that connect to the buried [NiFe] active site have remained unclear, impeding the rational engineering of O2-tolerant enzyme variants. In this study, we present an artificial intelligence-guided de novo protein binder design strategy, utilizing compact protein binders as selective molecular probes to map hydrophobic O2 diffusion pathways in Escherichia coli hydrogenase-2 (Hyd-2). By integrating RFdiffusion, ProteinMPNN, and AlphaFold, approximately 100,000 candidate binders were computationally screened, leading to the identification of two high-affinity binders, L1 and L2. Structural, biophysical, and electrochemical analyses reveal that L1 specifically occludes the primary O2 ingress channel, thereby enhancing the enzyme's oxygen tolerance by more than threefold, whereas L2, which targets a putative secondary channel, exerts a negligible effect, demonstrating the nonfunctionality of this pathway. These results provide the first direct experimental evidence for a hierarchical organization of O2 diffusion channels in [NiFe]-hydrogenases and establish binder-mediated channel occlusion as a generalizable, mutation-free approach for probing gas transport mechanisms and selectivity in metalloenzymes.