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GLYCAM06: A generalizable biomolecular force field. Carbohydrates
Open accessAbstract
A new derivation of the GLYCAM06 force field, which removes its previous specificity for carbohydrates, and its dependency on the AMBER force field and parameters, is presented. All pertinent force field terms have been explicitly specified and so no default or generic parameters are employed. The new GLYCAM is no longer limited to any particular class of biomolecules, but is extendible to all molecular classes in the spirit of a small‐molecule force field. The torsion terms in the present work were all derived from quantum mechanical data from a collection of minimal molecular fragments and related small molecules. For carbohydrates, there is now a single parameter set applicable to both α‐ and β‐anomers and to all monosaccharide ring sizes and conformations. We demonstrate that deriving dihedral parameters by fitting to QM data for internal rotational energy curves for representative small molecules generally leads to correct rotamer populations in molecular dynamics simulations, and that this approach removes the need for phase corrections in the dihedral terms. However, we note that there are cases where this approach is inadequate. Reported here are the basic components of the new force field as well as an illustration of its extension to carbohydrates. In addition to reproducing the gas‐phase properties of an array of small test molecules, condensed‐phase simulations employing GLYCAM06 are shown to reproduce rotamer populations for key small molecules and representative biopolymer building blocks in explicit water, as well as crystalline lattice properties, such as unit cell dimensions, and vibrational frequencies. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008
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Cites
Role of Glycosylation in Development
Haltiwanger, R. S., & Lowe, J. B. (2004) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.73.011303.074043 · Cited by 757
Weinhold, B., Seidenfaden, R., Röckle, I., Mühlenhoff, M., Schertzinger, F., Conzelmann, S., Marth, J. D., Gerardy-Schahn, R., & Hildebrandt, H. (2005) · Journal of Biological Chemistry · doi:10.1074/jbc.m511097200 · Cited by 298
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Smith, J. S., Nebgen, B., Lubbers, N., Isayev, O., & Roitberg, A. E. (2018) · The Journal of Chemical Physics · doi:10.1063/1.5023802 · Cited by 811
Guvench, O., Mallajosyula, S. S., Raman, E. P., Hatcher, E., Vanommeslaeghe, K., Foster, T. J., Jamison, F. W., & MacKerell, A. D. (2011) · Journal of Chemical Theory and Computation · doi:10.1021/ct200328p · Cited by 699
Thomson, E. C., Rosen, L. E., Shepherd, J. G., Spreafico, R., da Silva Filipe, A., Wojcechowskyj, J. A., Davis, C., Piccoli, L., Pascall, D. J., Dillen, J., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.037 · Cited by 606
Christensen, A. S., Kubař, T., Cui, Q., & Elstner, M. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00584 · Cited by 446
Proença, C., Freitas, M., Ribeiro, D., Oliveira, E. F. T., Sousa, J. L. C., Tomé, S. M., Ramos, M. J., Silva, A. M. S., Fernandes, P. A., & Fernandes, E. (2017) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756366.2017.1368503 · Cited by 432
Metadata
- Authors
- Kirschner, K. N., Yongye, A. B., Tschampel, S. M., González‐Outeiriño, J., Daniels, C. R., Foley, B. L., & Woods, R. J.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2007-09-11
- Volume
- 29
- Issue
- 4
- Pages
- 622-655
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2098943363
- Cited by
- 2,243
- References
- 2
- FWCI
- 21.59
- Type
- journal article
- Language
- en
- Open access
- green
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