Exploiting QM/MM Capabilities in Geometry Optimization:  A Microiterative Approach Using Electrostatic Embedding.

J Chem Theory Comput

Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, D-45470 Mülheim an der Ruhr, Germany, and Computational Science and Engineering Department, CCLRC Daresbury Laboratory, Daresbury, Warrington WA4 4AD, United Kingdom.

Published: May 2007

AI Article Synopsis

  • A microiterative adiabatic scheme for QM/MM energy minimization is introduced, optimizing the MM component in each QM macroiteration, applicable to various embedding types.
  • The scheme calculates electrostatic interactions on-the-fly using QM density-fitted charges and ensures consistent energy surfaces across iterations, leading to accurate and well-converged results.
  • Tests on water clusters and enzymes show the method's efficiency, particularly for large MM systems, reducing the number of QM calculations by 2-10 times compared to standard methods.

Article Abstract

We present a microiterative adiabatic scheme for quantum mechanical/molecular mechanical (QM/MM) energy minimization that fully optimizes the MM part in each QM macroiteration. This scheme is applicable not only to mechanical embedding but also to electrostatic and polarized embedding. The electrostatic QM/MM interactions in the microiterations are calculated from electrostatic potential charges fitted on the fly to the QM density. Corrections to the energy and gradient expressions ensure that macro- and microiterations are performed on the same energy surface. This results in excellent convergence properties and no loss of accuracy compared to standard optimization. We test our implementation on water clusters and on two enzymes using electrostatic embedding, as well as on a surface example using polarized embedding with a shell model. Our scheme is especially well-suited for systems containing large MM regions, since the computational effort for the optimization is almost independent of the MM system size. The microiterations reduce the number of required QM calculations typically by a factor of 2-10, depending on the system.

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http://dx.doi.org/10.1021/ct600346pDOI Listing

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