Constant pH Simulations in GROMACS with FMM Electrostatics

The protonation state of most biomolecules is not static, but changes stochastically with time according to the pH of the surrounding solution. For some biomolecules, pH-induced protonation changes are an essential part of their function. However, a typical MD simulation does not include protonation dynamics, but simply uses fixed protonation states that are likely at the given pH. To overcome this limitation and make biomolecular simulations more realistic, we are developing a constant pH simulation protocol based on lambda dynamics and FMM electrostatics.

GROMACS constant pH documentation, download and install instructions

Please follow this link for comprehensive documentation on how to set up constant pH simulations with FMM electrostatics in GROMACS.

Example output of a constant pH lambda dynamics simulation. The left panel is a simulation at a fixed pH values and shows the time evolution of the lambda particle, which indicates the protonation state of a titratable residue. The right panel shows, for a series of simulations at different pH values, the average fraction of this residue in the deprotonated state. — **Example output of a constant pH lambda dynamics simulation.** The left panel is a simulation at a fixed pH values and shows the time evolution of the lambda particle, which indicates the protonation state of a titratable residue. The right panel shows, for a series of simulations at different pH values, the average fraction of this residue in the deprotonated state.

**Example output of a constant pH lambda dynamics simulation.** The left panel is a simulation at a fixed pH values and shows the time evolution of the lambda particle, which indicates the protonation state of a titratable residue. The right panel shows, for a series of simulations at different pH values, the average fraction of this residue in the deprotonated state.

Project related publications

Kohnke, B.; Kutzner, C.; Grubmüller, H.: A GPU-accelerated fast multipole method for GROMACS: Performance and accuracy. Journal of Chemical Theory and Computation 16 (11), pp. 6938 - 6949 (2020)

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Kohnke, B.; Kutzner, C.; Beckmann, A.; Lube, G.; Kabadshow, I.; Dachsel, H.; Grubmüller, H.: A CUDA fast multipole method with highly efficient M2L farfield evaluationfield evaluation. The International Journal of High Performance Computing Applications 35 (1), pp. 97 - 117 (2021)

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Kohnke, B.; Ullmann, R. T.; Beckman, A.; Kabadshow, I.; Haensel, D.; Morgenstern, L.; Dobrev, P.; Groenhof, G.; Kutzner, C.; Hess, B. et al.; Dachsel, H.; Grubmüller, H.: GROMEX: A scalable and versatile fast multipole method for biomolecular simulation. In: Software for Exascale Computing - SPPEXA 2016-2019, pp. 517 - 543 (Eds. Bungartz, H.-J.; Reiz, S.; Uekermann, B.; Neumann, P.; Nagel, W. E.). Springer, Cham (2020)

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Donnini, S.; Ullmann, T.; Groenhof, G.; Grubmüller, H.: Charge-neutral constant pH molecular dynamics simulations using a parsimonious proton buffer. Journal of Chemical Theory and Computation 12 (3), pp. 1040 - 1051 (2016)

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Donnini, S.; Tegeler, F.; Groenhof, G.; Grubmüller, H.: Constant pH molecular dynamics in explicit solvent with lambda-dynamics. Journal of Chemical Theory and Computation 7 (6), pp. 1962 - 1978 (2011)

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