Abstract
Substrate specificity is a defining feature of enzyme function, but its molecular underpinnings remain difficult to decode and engineer. Here, we leverage enzyme proximity sequencing (EP-Seq) to systematically map how single-point and combinatorial mutations reshape the substrate preferences of D-amino acid oxidase (DAOx) from Rhodotorula gracilis, a model promiscuous enzyme. We generate ~40,000 sequence–phenotype pairs, enabling us to profile the activities of ~6,500 unique DAOx variants against five D-amino acid substrates with distinct physicochemical properties. Our analysis reveals that substrate-specific mutations are distributed throughout the enzyme structure. Mutations near the active site drive strong specificity shifts but also incur catalytic penalties, while distal mutations subtly rewire intramolecular contacts in order to modulate specificity with minimal loss of activity. We identify and validate positional hotspots that act allosterically to influence specificity, and characterize key variants that acquire exclusive substrate specificity or exhibit up to 230-fold changes in substrate preference. Combining mutations with complementary effects further sharpens substrate discrimination, enabling rational design of highly selective biocatalysts. This work establishes a powerful framework for decoding enzyme specificity and provides foundational datasets to advance AI-guided enzyme engineering.
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Data availability
All data required to replicate this study and generated in this study are publicly available. DNA sequencing reads can be accessed through the NCBI Sequence Read Archive under BioProject accession PRJNA1289092. Raw data for all figures, and processed output data are available at https://doi.org/10.5281/zenodo.15846928. The PDB code of the previously published structure used in this study is 1C0P. Source Data are provided as a Source Data file. Source data are provided with this paper.
Code availability
All custom code and scripts used in this study are publicly available in the Zenodo repository at https://doi.org/10.5281/zenodo.15846928
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Acknowledgements
This work was supported by the University of Basel, ETH Zurich, the SNF-NCCR in Molecular Systems Engineering, and an SNSF Grant (200021_191962 and 10004516) to M.A.N.
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R.V. and M.A.N. conceived the study and drafted the manuscript. R.V. carried out the practical work and computational analyses. S.B. optimized and performed the expression and purification of the soluble DAOx variants. C.K. contributed to the conceptualization and optimization of the workflow. M.A.N. secured funding and administered the project.
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Vanella, R., Boult, S., Küng, C. et al. Decoding the substrate specificity landscape of a promiscuous enzyme through multi-substrate mutational scanning. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69913-z
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DOI: https://doi.org/10.1038/s41467-026-69913-z
