Molecular Dynamics Simulations Empowered De Novo Design of Binding Peptide for Enhanced Direct Bioelectrocatalytic Oxygen Reduction

Abstract A key challenge in enzymatic electrocatalysis is the precise control of enzyme orientation on electrode surfaces to enable efficient direct electron transfer. Binding peptides have been reported to be helpful in assisting the favorable orientation of multicopper oxidases, while seeking and engineering natural binding peptides for various oxidoreductases is a huge workload. De novo peptide design may provide a versatile and promising approach to tailor binding peptides. Here, we combine de novo design with molecular dynamics (MD) simulations to generate binding peptides that guide laccase into an optimal orientation on the electrode surface. Specifically, we present a rational design pipeline driven by ESM-2 clustering, RFdiffusion, and MD. For experimental validation, the direct bioelectrocatalytic index of laccase from Bacillus pumilus (BpL) was used as a probe to reflect the interaction between binding peptides and carbon nanotubes (CNTs). Consequently, almost half (7/14) of the designed peptides exhibited improved bioelectrocatalytic performance. Notably, BpL-DP-6-11 (de novo designed peptide) assisted the highest electrocatalytic activity of BpL, with a 35.5% increase in current density compared to the wild type, approaching the upper limit of the interfacial electron transfer rate of BpL. Moreover, BpL-DP-6-5 and BpL-DP-1-9, compared to BpL only, improved enzyme loading by 5.7-fold and 3.9-fold, respectively, reaching geometric loadings of 62.9 ± 8.6 and 42.3 ± 11.9 pmol·cm–2, which are 12.3 ± 1.7-fold and 8.2 ± 2.3-fold higher than the theoretical monolayer density of BpL (5.13 pmol·cm–2), respectively. This is attributed to the synergistic effects of oriented immobilization and surface roughness of CNT-modified electrodes. Molecular-level analyses indicate that synergistic π–π stacking and van der Waals interactions enable a reoriented binding configuration that effectively displaces the interfacial hydration layer, thereby enhancing direct electron transfer efficiency. This work establishes a generalizable framework for binding peptide design to reprogram enzyme–material interactions, overcoming the limitations of random physical adsorption and enabling next-generation high-performance bioelectrocatalytic systems.