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  • The adaptive buffered force...
    Mones, Letif; Jones, Andrew; Götz, Andreas W.; Laino, Teodoro; Walker, Ross C.; Leimkuhler, Ben; Csányi, Gábor; Bernstein, Noam

    Journal of computational chemistry, April 5, 2015, Letnik: 36, Številka: 9
    Journal Article

    The implementation and validation of the adaptive buffered force (AdBF) quantum‐mechanics/molecular‐mechanics (QM/MM) method in two popular packages, CP2K and AMBER are presented. The implementations build on the existing QM/MM functionality in each code, extending it to allow for redefinition of the QM and MM regions during the simulation and reducing QM‐MM interface errors by discarding forces near the boundary according to the buffered force‐mixing approach. New adaptive thermostats, needed by force‐mixing methods, are also implemented. Different variants of the method are benchmarked by simulating the structure of bulk water, water autoprotolysis in the presence of zinc and dimethyl‐phosphate hydrolysis using various semiempirical Hamiltonians and density functional theory as the QM model. It is shown that with suitable parameters, based on force convergence tests, the AdBF QM/MM scheme can provide an accurate approximation of the structure in the dynamical QM region matching the corresponding fully QM simulations, as well as reproducing the correct energetics in all cases. Adaptive unbuffered force‐mixing and adaptive conventional QM/MM methods also provide reasonable results for some systems, but are more likely to suffer from instabilities and inaccuracies. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. Implementations of an adaptive method for QM/MM simulations in the CP2K and AMBER packages are presented, making it straightforward to quantum mechanically describe not only the reacting species, but also a surrounding region of solvent, because the set of quantum atoms can be changed adaptively in the simulation. Geometries and free energy profiles are compared to those of full quantum mechanical simulations to show that the method is more robust than alternatives.