Mechanistic Determinants of Oriented Enzyme Immobilization from Martini Simulations

08 December 2025, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Although enzyme immobilization is widely used in biotechnology, it still poses challenges as a result of the trade-offs between stability, activity, and surface interactions. Computer simulations offer a promising aid to explore the effects of different immobilization sites and surface chemistry on both the conformational dynamics and catalytic activity of these biomolecules. Here, we introduce a protocol based on a structure-based version of the Martini coarse-grained simulation model (GōMartini) to explore how surface tethering geometry influences the structure and function of immobilized \textit{Bacillus stearothermophilus} alcohol dehydrogenase (BsADH). We compare traditional His-tag tethering with two engineered histidine cluster variants, analyzing their behavior in both soluble and surface-tethered states. We find that cluster-based immobilization locally restricts flexibility in surface-contacting subunits while preserving the mobility of exposed regions, resulting in enhanced conformational stability under thermal stress. Functional analyses reveal that the ethanol association rates remain largely unaffected by surface attachment, whereas the dissociation of NADH is significantly slowed, explaining the reduced catalytic efficiency. These trends align with experimental findings and highlight the predictive power of GōMartini simulations in capturing key functional trade-offs. Altogether, this work offers mechanistic insight for the rational design of immobilized biocatalysts and outlines a practical framework for in silico exploration of enzyme–surface systems.

Keywords

Enzyme catalysis
Coarse grained models
Molecular dynamics simulations
Immobilization

Supplementary materials

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Supporting Information
Description
Complete descriptions of system preparation, GoMartini parameterization, simulation protocols, analysis scripts, and additional figures (Figures S1–S10)
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