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Entropy of proteins using multiscale cell correlation

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Entropy of proteins using multiscale cell correlation. / Chakravorty, Arghya; Higham, Jonathan; Henchman, Richard H.
In: Journal of Chemical Information and Modeling, Vol. 60, No. 11, 23.11.2020, p. 5540-5551.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Chakravorty, A, Higham, J & Henchman, RH 2020, 'Entropy of proteins using multiscale cell correlation', Journal of Chemical Information and Modeling, vol. 60, no. 11, pp. 5540-5551. https://doi.org/10.1021/acs.jcim.0c00611

APA

Chakravorty, A., Higham, J., & Henchman, R. H. (2020). Entropy of proteins using multiscale cell correlation. Journal of Chemical Information and Modeling, 60(11), 5540-5551. https://doi.org/10.1021/acs.jcim.0c00611

Vancouver

Chakravorty A, Higham J, Henchman RH. Entropy of proteins using multiscale cell correlation. Journal of Chemical Information and Modeling. 2020 Nov 23;60(11):5540-5551. Epub 2020 Sept 21. doi: 10.1021/acs.jcim.0c00611

Author

Chakravorty, Arghya ; Higham, Jonathan ; Henchman, Richard H. / Entropy of proteins using multiscale cell correlation. In: Journal of Chemical Information and Modeling. 2020 ; Vol. 60, No. 11. pp. 5540-5551.

Bibtex

@article{7b4113b3d116447bbb61f3485ec8ae4e,
title = "Entropy of proteins using multiscale cell correlation",
abstract = "A new multiscale method is presented to calculate the entropy of proteins from molecular dynamics simulations. Termed Multiscale Cell Correlation (MCC), the method decomposes the protein into sets of rigid-body units based on their covalent-bond connectivity at three levels of hierarchy: molecule, residue, and united atom. It evaluates the vibrational and topographical entropy from forces, torques, and dihedrals at each level, taking into account correlations between sets of constituent units that together make up a larger unit at the coarser length scale. MCC gives entropies in close agreement with normal-mode analysis and smaller than those using quasiharmonic analysis as well as providing much faster convergence. Moreover, MCC provides an insightful decomposition of entropy at each length scale and for each type of amino acid according to their solvent exposure and whether they are terminal residues. While the residue entropy depends weakly on solvent exposure, there is greater variation in entropy components for larger, more polar amino acids, which have increased conformational entropy but reduced vibrational entropy with greater solvent exposure.",
author = "Arghya Chakravorty and Jonathan Higham and Henchman, {Richard H.}",
year = "2020",
month = nov,
day = "23",
doi = "10.1021/acs.jcim.0c00611",
language = "English",
volume = "60",
pages = "5540--5551",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society (ACS)",
number = "11",

}

RIS

TY - JOUR

T1 - Entropy of proteins using multiscale cell correlation

AU - Chakravorty, Arghya

AU - Higham, Jonathan

AU - Henchman, Richard H.

PY - 2020/11/23

Y1 - 2020/11/23

N2 - A new multiscale method is presented to calculate the entropy of proteins from molecular dynamics simulations. Termed Multiscale Cell Correlation (MCC), the method decomposes the protein into sets of rigid-body units based on their covalent-bond connectivity at three levels of hierarchy: molecule, residue, and united atom. It evaluates the vibrational and topographical entropy from forces, torques, and dihedrals at each level, taking into account correlations between sets of constituent units that together make up a larger unit at the coarser length scale. MCC gives entropies in close agreement with normal-mode analysis and smaller than those using quasiharmonic analysis as well as providing much faster convergence. Moreover, MCC provides an insightful decomposition of entropy at each length scale and for each type of amino acid according to their solvent exposure and whether they are terminal residues. While the residue entropy depends weakly on solvent exposure, there is greater variation in entropy components for larger, more polar amino acids, which have increased conformational entropy but reduced vibrational entropy with greater solvent exposure.

AB - A new multiscale method is presented to calculate the entropy of proteins from molecular dynamics simulations. Termed Multiscale Cell Correlation (MCC), the method decomposes the protein into sets of rigid-body units based on their covalent-bond connectivity at three levels of hierarchy: molecule, residue, and united atom. It evaluates the vibrational and topographical entropy from forces, torques, and dihedrals at each level, taking into account correlations between sets of constituent units that together make up a larger unit at the coarser length scale. MCC gives entropies in close agreement with normal-mode analysis and smaller than those using quasiharmonic analysis as well as providing much faster convergence. Moreover, MCC provides an insightful decomposition of entropy at each length scale and for each type of amino acid according to their solvent exposure and whether they are terminal residues. While the residue entropy depends weakly on solvent exposure, there is greater variation in entropy components for larger, more polar amino acids, which have increased conformational entropy but reduced vibrational entropy with greater solvent exposure.

U2 - 10.1021/acs.jcim.0c00611

DO - 10.1021/acs.jcim.0c00611

M3 - Journal article

C2 - 32955869

AN - SCOPUS:85096814548

VL - 60

SP - 5540

EP - 5551

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 11

ER -