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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Efficient QM/MM Modeling of Enzymatic Reactions Combining PathCV with OPES.

José Pablo Rivas-Fernández1, Martin Calvelo1, Mert Sagiroglugil1

  • 1Departament de Química Inorgànica i Orgànica & IQTCUB, Universitat de Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain.

Journal of Chemical Theory and Computation
|May 27, 2026
PubMed
Summary

This study introduces a new protocol combining Path Collective Variable (PathCV) and on-the-fly probability-enhanced sampling (OPES_E) to efficiently study enzymatic reactions using quantum mechanics/molecular mechanics (QM/MM) simulations.

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Area of Science:

  • Computational chemistry
  • Biochemistry
  • Molecular dynamics

Background:

  • Hybrid quantum mechanics/molecular mechanics (QM/MM) simulations are vital for studying enzyme mechanisms.
  • Current limitations include short accessible timescales and challenges in defining collective variables for enhanced sampling.

Purpose of the Study:

  • To develop a practical protocol for accelerating reactive transitions and reconstructing free energy profiles in enzymatic QM/MM simulations.
  • To improve the efficiency of enhanced sampling techniques for studying enzyme reaction mechanisms.

Main Methods:

  • Integration of a Path Collective Variable (PathCV) with exploratory on-the-fly probability-enhanced sampling (OPES_E).
  • Construction of PathCV from preliminary trajectories to guide biased simulations.
  • Implementation of a block-selection strategy for robust free energy reconstruction.
  • Systematic analysis and optimization of OPES_E parameters.

Main Results:

  • The PathCV-guided OPES_E protocol successfully accelerated multiple reactive transitions in QM/MM simulations for three distinct enzymes.
  • Demonstrated superior sampling efficiency compared to alternative methods like OPES, metadynamics, and well-tempered metadynamics.
  • Enabled robust free energy profile reconstruction from time-dependent biased trajectories.

Conclusions:

  • The developed protocol offers a practical and efficient approach for enhanced sampling QM/MM studies of enzymatic reactions.
  • This method overcomes limitations of short simulation times and difficulties in defining reaction coordinates.
  • Provides a valuable guide for computational investigations of complex enzymatic processes.