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Scalable Constant pH Molecular Dynamics in GROMACS

Authors: Buslaev, Pavel; Jansen, Anton; Bauer, Paul; Groenhof, Gerrit; Hess; Berk; Aho, Noora;
Abstract

Molecular dynamics (MD) computer simulations are used routinely to compute atomistic trajectories of complex systems. Systems are simulated in various ensembles, depending on the experimental conditions one aims to mimic. While constant energy, temperature, volume, and pressure are rather straightforward to model, pH, which is an equally important parameter in experiments, is more difficult to account for in simulations. Although a constant pH algorithm based on the $\lambda$-dynamics approach by Brooks and co-workers was implemented in a fork of the GROMACS molecular dynamics program, uptake has been rather limited, presumably due to the poor scaling of that code with respect to the number of titratable sites. To overcome this limitation, we implemented an alternative scheme for interpolating the Hamiltonians of the protonation states that makes the constant pH molecular dynamics simulations almost as fast as a normal MD simulation with GROMACS. In addition, we implemented a simpler scheme, called multisite representation, for modeling side chains with multiple titratable sites, such as imidazole rings. This scheme, which is based on constraining the sum of the $\lambda$-coordinates, not only reduces the complexity associated with parameterizing the intra-molecular interactions between the sites, but is also easily extendable to other molecules with multiple titratable sites. With the combination of a more efficient interpolation scheme and multisite representation of titratable groups, we anticipate a rapid uptake of constant pH molecular dynamics simulations within the GROMACS user community.

Country
Finland
Keywords

ta1182, Imidazoles, molekyylit, potentiaalienergia, Hydrogen-Ion Concentration, Molecular Dynamics Simulation, monomers, peptides and proteins, reaktiomekanismit, molecular mechanics, potential energy, reaction mechanisms, peptidit, Humans, molekyylidynamiikka, proteiinit, ta116, Algorithms

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
110
Top 1%
Top 10%
Top 0.1%
Green
hybrid