MiMiCPy-FM: A User-Friendly Force Matching Tool for Extending the Time Scale of QM/MM MD MiMiC Simulations

Journal of Chemical Information and Modeling, vol. 66, pp. 2458–2465

Abstract

Force matching (FM) algorithms develop force fields to dramatically extend the time scales of quantum mechanical/molecular mechanics (QM/MM) molecular dynamics (MD) simulations. Here, we present MiMiCPy-FM, an implementation of the generalized QM/MM FM approach for the automated parametrization of biomolecular force fields. MiMiCPy-FM streamlines the optimization of force field parameters by using reference data generated by the recently developed, highly scalable QM/MM MD MiMiC interface. MiMiCPy-FM is fully integrated within the MiMiCPy framework, providing both a command-line interface for quick execution and a Python library for advanced, customizable workflows. The tool is able to treat systems with and without covalent QM/MM boundaries and produces updated topology files that can be directly used to perform classical MD simulations with GROMACS. An application to a complex Mg-based enzyme of pharmacological relevance illustrates how MiMiCPy-FM enables a seamless transition from MiMiC QM/MM MD simulations to long-time scale, force-matched classical MD simulations.

Authors 9

1. Sachin Shivakumar Aachen

   Forschungszentrum Jülich · Science for Life Laboratory · KTH Royal Institute of Technology · RWTH Aachen University

   Affiliation as printed

   Computational Biomedicine (INM-9)

   Department of Applied Physics, Science for Life Laboratory

   Department of Physics

   Forschungszentrum Jülich

   KTH Royal Institute of Technology

   RWTH Aachen University

2. Giorgia Frumenzio

   Cineca · University of Bologna

   Affiliation as printed

   CINECA

   Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology

   University of Bologna

3. Francesco Musiani

   University of Bologna

   Affiliation as printed

   Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology

   University of Bologna

4. Fabio Affinito

   Cineca

   Affiliation as printed

   CINECA

5. Emiliano Ippoliti

   Forschungszentrum Jülich

   Affiliation as printed

   Computational Biomedicine (INM-9)

   Forschungszentrum Jülich

6. Bharath Raghavan

   Oak Ridge National Laboratory

   Affiliation as printed

   National Center for Computational Sciences

   Oak Ridge National Laboratory

7. Giulia Rossetti Aachen

   Forschungszentrum Jülich · Universitätsklinikum Aachen · Jülich Supercomputing Centre · RWTH Aachen University

   Affiliation as printed

   Computational Biomedicine (INM-9)

   Department of Neurology

   Forschungszentrum Jülich

   Jülich Supercomputing Centre (JSC)

   University Hospital Aachen (UKA), RWTH Aachen University

8. Davide Mandelli corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Computational Biomedicine (INM-9)

   Forschungszentrum Jülich

9. Paolo Carloni corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Computational Biomedicine (INM-9)

   Forschungszentrum Jülich

   Neuroscience and Neuroimaging (INM-11)