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Phys Rev E. 2016 Mar;93(3):032415. doi: 10.1103/PhysRevE.93.032415. Epub 2016 Mar 28.

Random close packing in protein cores.

Gaines JC1,2, Smith WW3, Regan L1,2,4,5, O'Hern CS1,2,3,6,7.

Author information

1
Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA.
2
Integrated Graduate Program in Physical and Engineering Biology (IGPPEB), Yale University, New Haven, Connecticut 06520, USA.
3
Department of Physics, Yale University, New Haven, Connecticut 06520, USA.
4
Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, Connecticut 06520, USA.
5
Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA.
6
Department of Mechanical Engineering & Materials Science, Yale University, New Haven, Connecticut 06520, USA.
7
Department of Applied Physics, Yale University, New Haven, Connecticut 06520, USA.

Abstract

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈ 0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈ 0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

PMID:
27078398
DOI:
10.1103/PhysRevE.93.032415
[Indexed for MEDLINE]

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