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Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method

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Published on: July 19, 2019

The adaptive buffered force QM/MM method in the CP2K and AMBER software packages.

Letif Mones¹, Andrew Jones, Andreas W Götz

¹Engineering Department, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom.

Journal of Computational Chemistry

|February 5, 2015

Summary

The adaptive buffered force (AdBF) QM/MM method, implemented in CP2K and AMBER, accurately simulates molecular structures and energetics. This advanced QM/MM approach minimizes interface errors for reliable computational chemistry studies.

Keywords:

adaptive quantum-mechanics/molecular-mechanics force-mixing multiscale quantum-mechanics/molecular-mechanics

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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Published on: September 17, 2021

Area of Science:

Computational chemistry
Molecular modeling
Quantum mechanics/molecular mechanics (QM/MM)

Background:

Accurate simulation of complex chemical systems requires robust QM/MM methods.
Existing QM/MM approaches often face challenges with interface errors and computational stability.
The adaptive buffered force (AdBF) method offers a potential solution to these limitations.

Purpose of the Study:

To implement and validate the adaptive buffered force (AdBF) QM/MM method in CP2K and AMBER.
To assess the performance of AdBF in simulating various chemical systems, including bulk water and hydrolysis reactions.
To compare AdBF with other QM/MM variants and fully QM simulations.

Main Methods:

Implementation of AdBF QM/MM with redefinable QM/MM regions and buffered force-mixing.
Development of new adaptive thermostats to support force-mixing methods.
Benchmarking using simulations of bulk water, water autoprotolysis, and dimethyl-phosphate hydrolysis.
Utilizing semiempirical Hamiltonians and density functional theory for QM calculations.

Main Results:

AdBF QM/MM accurately reproduces the structure and energetics of the QM region, matching fully QM simulations.
Suitable parameterization based on force convergence tests is crucial for AdBF accuracy.
Adaptive unbuffered force-mixing and conventional QM/MM methods showed potential but were prone to instabilities.

Conclusions:

The AdBF QM/MM scheme provides a reliable and accurate method for computational chemistry simulations.
AdBF effectively minimizes QM/MM interface errors, enhancing simulation stability and accuracy.
This implementation offers a valuable tool for studying complex chemical processes at the molecular level.