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Structure-based modeling reveals molecular basis for CYP153A6’s novel activity toward toluene derivatives
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  • Published: 06 February 2026

Structure-based modeling reveals molecular basis for CYP153A6’s novel activity toward toluene derivatives

  • Yao Wei1,
  • Silvia Donzella2,
  • Sara Foiadelli2,
  • Francesco Molinari2,
  • Uliano Guerrini1 &
  • …
  • Ivano Eberini1 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biochemistry
  • Chemical biology
  • Chemistry
  • Computational biology and bioinformatics
  • Drug discovery

Abstract

CYP153A6 from Mycobacterium sp. strain HXN-1500 is a monooxygenase that catalyzes the selective hydroxylation of terminal methyl groups in various alkanes. This study explored CYP153A6 activity towards a set of toluene derivatives, along with the underlying molecular recognition. Initial in vivo evaluation of CYP153A6 activity, conducted using both whole cells and cell-free extracts, showed efficient conversion of toluene derivatives with apolar or slightly polar substituents, while no detectable activity was observed for derivatives bearing more polar groups. A homology model of CYP153A6 3D structure was built and validated, revealing key structural features and molecular tunnels. An ensemble docking strategy was used to identify the most effective docking setup. Molecular dynamics simulations and binding free energy calculations further confirmed the hydrophobic nature of the active site. QM/MM calculations supported the different reactivity observed between p-chlorotoluene and p-nitrotoluene. Toluene derivatives bearing a hydroxyl or nitro group on the aromatic ring exhibit reduced binding affinity, adopting unfavorable orientations and non-productive distances between the methyl group and the enzyme’s heme iron center. These computational findings agree with experimental data. Overall, this study provides valuable insights into CYP153A6 molecular recognition mechanism and lay a strong foundation for future protein engineering to extend CYP153A6 enzyme substrate scope and/or enhance the product yield.

Data availability

Materials are archived in the University of Milan Dataverse (institutional FAIR repository) if applicable at the following link:  https://doi.org/10.13130/RD_UNIMI/9GCFAM

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Funding

This project has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101073546 (MSCA Doctoral Network Metal-containing Radical Enzymes - MetRaZymes), and grants from MUR - “Progetto Eccellenza 2023–2027”.

Author information

Authors and Affiliations

  1. Dipartimento di Scienze Farmacologiche e Biomolecolari “Rodolfo Paoletti”, Università degli Studi di Milano, Via Giuseppe Balzaretti 9, Milano, 20133, Italy

    Yao Wei, Uliano Guerrini & Ivano Eberini

  2. Dipartimento di Scienze per gli Alimenti, la Nutrizione e l’Ambiente (DeFENS), Università degli Studi di Milano, Via Luigi Mangiagalli 25, Milano, 20133, Italy

    Silvia Donzella, Sara Foiadelli & Francesco Molinari

Authors
  1. Yao Wei
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  2. Silvia Donzella
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Contributions

Y.W. designed and performed all molecular modeling research and wrote the bioinformatics section of the manuscript. S.D. and S.F. designed and conducted all enzyme expression and biotransformation experiments and wrote the experimental section. U.G. was responsible for managing the molecular modeling software. F.M. and I.E. supervised the study and were responsible for funding acquisition. All authors participated in the review and revision of the manuscript.

Corresponding author

Correspondence to Ivano Eberini.

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The authors declare no competing interests.

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Wei, Y., Donzella, S., Foiadelli, S. et al. Structure-based modeling reveals molecular basis for CYP153A6’s novel activity toward toluene derivatives. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38986-7

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  • Received: 31 December 2025

  • Accepted: 02 February 2026

  • Published: 06 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38986-7

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Keywords

  • CYP153A6
  • Toluene derivatives
  • Molecular modeling
  • Molecular recognition
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