CMDmpnn: Combining Comparative Molecular Dynamics and ProteinMPNN to Rapidly Expand Enzyme Substrate Spectrum

Journal of Chemical Information and Modeling, vol. 65, pp. 2741–2747

Abstract

Expanding enzyme substrate spectra enhances industrial applications and drives sustainable biocatalysis. Despite advances, challenges in modification efficiency and high-throughput screening persist. Here, we developed a virtual screening method called CMDmpnn that combines comparative molecular dynamics (MD) simulations and ProteinMPNN to broaden enzyme substrate spectra without compromising other industrially important properties of enzymes, such as thermostability. Using glycosyltransferase as a model, we first established a dynamic model library of the wild-type enzyme through MD simulations and performed clustering. Subsequently, we utilized ProteinMPNN to generate a comprehensive set of new sequences for the entire library, enabling rapid identification of all possible enzyme variants. Short MD simulations were then conducted on variant-substrate complex models, with results compared to those of the wild-type enzyme. By analyzing catalytically relevant information such as substrate binding modes and key atomic distances, we identified multiple variants capable of catalyzing a broad spectrum of phenolic compounds, all within a timeframe of less than 2 weeks. The CMDmpnn method offers a powerful and efficient tool for rapidly expanding enzyme substrate spectra.

Authors 5

1. Chuanqi Sun

   East China University of Science and Technology · State Key Laboratory of Bioreactor Engineering

   Affiliation as printed

   East China University of Science and Technology

   State Key Laboratory of Bioreactor Engineering

   State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 200237 Shanghai, China

2. Zhimin Li corresponding

   East China University of Science and Technology · State Key Laboratory of Bioreactor Engineering

   Affiliation as printed

   East China University of Science and Technology

   Shanghai Collaborative Innovation Center for Biomanufacturing Technology

   State Key Laboratory of Bioreactor Engineering

   Shanghai Collaborative Innovation Center for Biomanufacturing Technology, 200237 Shanghai, China

   State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 200237 Shanghai, China

3. Ji Yu corresponding

   Beijing University of Chemical Technology

   Affiliation as printed

   Beijing University of Chemical Technology

   College of Life Science and Technology, Beijing Advanced Innovation Center for Soft Matter Science and Engineering

   College of Life Science and Technology, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China

4. Ulrich Schwaneberg Aachen Institute of Biotechnology

   RWTH Aachen University

   Affiliation as printed

   Institute of Biotechnology, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany

5. Zonglin Li corresponding

   East China University of Science and Technology · State Key Laboratory of Bioreactor Engineering

   Affiliation as printed

   East China University of Science and Technology

   Shanghai Collaborative Innovation Center for Biomanufacturing Technology

   State Key Laboratory of Bioreactor Engineering

   State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 200237 Shanghai, China