QM/MM free energy simulations: recent progress and challenges

Abstract

Due to the higher computational cost relative to pure molecular mechanical (MM) simulations, hybrid quantum mechanical/molecular mechanical (QM/MM) free energy simulations particularly require a careful consideration of balancing computational cost and accuracy. Here, we review several recent developments in free energy methods most relevant to QM/MM simulations and discuss several topics motivated by these developments using simple but informative examples that involve processes in water. For chemical reactions, we highlight the value of invoking enhanced sampling technique (e.g. replica-exchange) in umbrella sampling calculations and the value of including collective environmental variables (e.g. hydration level) in metadynamics simulations; we also illustrate the sensitivity of string calculations, especially free energy along the path, to various parameters in the computation. Alchemical free energy simulations with a specific thermodynamic cycle are used to probe the effect of including the first solvation shell into the QM region when computing solvation free energies. For cases where high-level QM/MM potential functions are needed, we analyse two different approaches: the QM/MM–MFEP method of Yang and co-workers and perturbative correction to low-level QM/MM free energy results. For the examples analysed here, both approaches seem productive although care needs to be exercised when analysing the perturbative corrections.

Keywords:

• QM/MM
• free energy
• sampling

Acknowledgements

We also thank Dr Jia and his co-workers for sending the manuscript for Ref. [127] prior to publication; discussions with Dr Woodcock and König about NBB are also acknowledged.

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work has been supported by grants from the National Science Foundation [grant number CHE-1300209]; the National Institutes of Health [R01GM106443]. Computational resources from the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF [grant number OCI-1053575], are greatly appreciated; computations are also supported in part by NSF through a major instrumentation [grant number CHE-0840494] to the Chemistry department.