A unified coarse-grained model of biological macromolecules based on mean-field multipole–multipole interactions

Adam Liwo, Maciej Baranowski, Cezary Czaplewski, Ewa Gołaś, Yi He, Dawid Jagieła, Paweł Krupa, Maciej Maciejczyk, Mariusz Makowski, Magdalena A. Mozolewska,

Journal of Molecular Modeling · 2014 · 156 citations · 89 references

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Abstract

A unified coarse-grained model of three major classes of biological molecules--proteins, nucleic acids, and polysaccharides--has been developed. It is based on the observations that the repeated units of biopolymers (peptide groups, nucleic acid bases, sugar rings) are highly polar and their charge distributions can be represented crudely as point multipoles. The model is an extension of the united residue (UNRES) coarse-grained model of proteins developed previously in our laboratory. The respective force fields are defined as the potentials of mean force of biomacromolecules immersed in water, where all degrees of freedom not considered in the model have been averaged out. Reducing the representation to one center per polar interaction site leads to the representation of average site-site interactions as mean-field dipole-dipole interactions. Further expansion of the potentials of mean force of biopolymer chains into Kubo's cluster-cumulant series leads to the appearance of mean-field dipole-dipole interactions, averaged in the context of local interactions within a biopolymer unit. These mean-field interactions account for the formation of regular structures encountered in biomacromolecules, e.g., α-helices and β-sheets in proteins, double helices in nucleic acids, and helicoidally packed structures in polysaccharides, which enables us to use a greatly reduced number of interacting sites without sacrificing the ability to reproduce the correct architecture. This reduction results in an extension of the simulation timescale by more than four orders of magnitude compared to the all-atom representation. Examples of the performance of the model are presented.

References

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