In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.
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28 December 2017
Research Article|
December 22 2017
Optimization and benchmarking of a perturbative Metropolis Monte Carlo quantum mechanics/molecular mechanics program
Jonas Feldt
;
Jonas Feldt
1
Institut für Physikalische Chemie, Universität Göttingen
, Tammannstrasse 6, D-37077 Göttingen, Germany
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Sebastião Miranda;
Sebastião Miranda
2
INESC-ID/IST, Universidade de Lisboa
, Rua Alves Redol, 1000-029 Lisboa, Portugal
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Frederico Pratas;
Frederico Pratas
2
INESC-ID/IST, Universidade de Lisboa
, Rua Alves Redol, 1000-029 Lisboa, Portugal
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Nuno Roma;
Nuno Roma
2
INESC-ID/IST, Universidade de Lisboa
, Rua Alves Redol, 1000-029 Lisboa, Portugal
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Pedro Tomás;
Pedro Tomás
2
INESC-ID/IST, Universidade de Lisboa
, Rua Alves Redol, 1000-029 Lisboa, Portugal
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Ricardo A. Mata
Ricardo A. Mata
1
Institut für Physikalische Chemie, Universität Göttingen
, Tammannstrasse 6, D-37077 Göttingen, Germany
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J. Chem. Phys. 147, 244105 (2017)
Article history
Received:
October 20 2017
Accepted:
December 01 2017
Citation
Jonas Feldt, Sebastião Miranda, Frederico Pratas, Nuno Roma, Pedro Tomás, Ricardo A. Mata; Optimization and benchmarking of a perturbative Metropolis Monte Carlo quantum mechanics/molecular mechanics program. J. Chem. Phys. 28 December 2017; 147 (24): 244105. https://doi.org/10.1063/1.5009820
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