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research article

MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry

Olsen, Jogvan Magnus Haugaard
•
Bolnykh, Viacheslav
•
Meloni, Simone  
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June 1, 2019
Journal of Chemical Theory and Computation

We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through the use of MPI intercommunicators. This allows exploiting the existing parallelization strategies used by the coupled programs while maintaining a high degree of flexibility. MiMiC has been used in a new electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) implementation coupling the highly efficient CPMD and GROMACS programs, but it can also be extended to use other programs. The framework can also be utilized to extend the partitioning of the system into several domains that can be treated using different models, such as models based on wave function or density functional theory as well as coarse-graining and continuum models. The new QM/MM implementation treats long-range electrostatic QM-MM interactions through the multipoles of the QM subsystem which substantially reduces the computational cost without loss of accuracy compared to an exact treatment. This enables QM/MM molecular dynamics (MD) simulations of very large systems.

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Type
research article
DOI
10.1021/acs.jctc.9b00093
Web of Science ID

WOS:000471728500031

Author(s)
Olsen, Jogvan Magnus Haugaard
Bolnykh, Viacheslav
Meloni, Simone  
Ippoliti, Emiliano
Bircher, Martin P.  
Carloni, Paolo
Rothlisberger, Ursula  
Date Issued

2019-06-01

Publisher

AMER CHEMICAL SOC

Published in
Journal of Chemical Theory and Computation
Volume

15

Issue

6

Start page

3810

End page

3823

Subjects

Chemistry, Physical

•

Physics, Atomic, Molecular & Chemical

•

Chemistry

•

Physics

•

molecular-dynamics simulations

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density-functional calculations

•

ab-initio

•

plane-waves

•

protein

•

approximation

•

optimization

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mechanism

•

efficient

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gromacs

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LCBC  
Available on Infoscience
June 28, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/158637
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