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Quantum computing for faster enzyme discovery and engineering

Nature Catalysis volume 8, pages 872–880 (2025)Cite this article

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Abstract

Quantum computing, by leveraging the unique principles of quantum mechanics, offers transformative potential for biocatalysis and related disciplines. Compared to classical algorithms, quantum algorithms deliver immense acceleration to quantum computers, making them suited for tackling computationally challenging problems such as simulating many-body biomolecular systems or enzyme-catalysed chemical reactions. However, current quantum hardware is constrained by noise, limited qubit coherence and high error rates, restricting its capacity to model complex biochemical phenomena. Here we explore the rapidly advancing landscape of quantum computing and its future applications in the discovery and rational engineering of biocatalysts. We identify key areas where quantum algorithms could surpass classical limitations, including the quantum chemistry-based design of biocatalysts with enhanced catalytic activity or selectivity, parallelized mining of novel enzymes, accurate ancestral sequence reconstruction, and combinatorial in silico protein evolution. Overcoming current hardware limitations could unlock transformative advances in both fundamental enzymology and industrial bioprocessing.

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Fig. 1: Timeline and envisaged applications of quantum computing in biocatalysis.

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Acknowledgements

We express our sincere thanks to the Senior Editor of Nature Catalysis, J.-S. Völler and P. Zapletal from the University of Erlangen-Nuremberg for their constructive comments on the manuscript. We are also grateful for the computational resources provided by the e-INFRA CZ and ELIXIR-CZ projects (90254 and LM2023055), supported by the Ministry of Education, Youth and Sports of the Czech Republic, and by the National Institute for Neurology Research (LX22NPO5107), funded by the European Union—Next Generation EU. We also thank the RECETOX Research Infrastructure (No LM2023069) financed by the MEYS for a supportive background.

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Authors and Affiliations

  1. Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic

    Jiri Damborsky, Petr Kouba, Michal Vasina, David Bednar & Stanislav Mazurenko

  2. International Clinical Research Center, St Anne’s University Hospital, Brno, Czech Republic

    Jiri Damborsky, Michal Vasina, David Bednar & Stanislav Mazurenko

  3. Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Praha, Czech Republic

    Petr Kouba & Josef Sivic

  4. Faculty of Electrical Engineering, Czech Technical University in Prague, Praha, Czech Republic

    Petr Kouba

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Correspondence to Stanislav Mazurenko.

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J.D. is the co-founder of the biotechnology spin-off company Enantis. The remaining authors declare no competing interests.

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Damborsky, J., Kouba, P., Sivic, J. et al. Quantum computing for faster enzyme discovery and engineering. Nat Catal 8, 872–880 (2025). https://doi.org/10.1038/s41929-025-01410-w

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