Charge group partitioning in biomolecular simulation

Canzar, Stefan, El-Kebir, Mohammed, Pool, René, Elbassioni, Khaled, Malde, Alpeshkumar K., Mark, Alan E., Geerke, Daan P., Stougie, Leen and Klau, Gunnar W. (2013) Charge group partitioning in biomolecular simulation. Journal of Computational Biology, 20 3: 188-198. doi:10.1089/cmb.2012.0239

Author Canzar, Stefan
El-Kebir, Mohammed
Pool, René
Elbassioni, Khaled
Malde, Alpeshkumar K.
Mark, Alan E.
Geerke, Daan P.
Stougie, Leen
Klau, Gunnar W.
Title Charge group partitioning in biomolecular simulation
Journal name Journal of Computational Biology   Check publisher's open access policy
ISSN 1066-5277
Publication date 2013-03-05
Year available 2013
Sub-type Article (original research)
DOI 10.1089/cmb.2012.0239
Open Access Status DOI
Volume 20
Issue 3
Start page 188
End page 198
Total pages 11
Place of publication United States
Publisher Mary Ann Liebert Publishers
Language eng
Formatted abstract
Molecular simulation techniques are increasingly being used to study biomolecular systems at an atomic level. Such simulations rely on empirical force fields to represent the intermolecular interactions. There are many different force fields available—each based on a different set of assumptions and thus requiring different parametrization procedures. Recently, efforts have been made to fully automate the assignment of force-field parameters, including atomic partial charges, for novel molecules. In this work, we focus on a problem arising in the automated parametrization of molecules for use in combination with the ɢʀᴏᴍᴏs family of force fields: namely, the assignment of atoms to charge groups such that for every charge group the sum of the partial charges is ideally equal to its formal charge. In addition, charge groups are required to have size at most k. We show -hardness and give an exact algorithm that solves practical problem instances to provable optimality in a fraction of a second.
Keyword Atomic force fields
Biomolecular simulation
Charge groups
Dynamic programming
Tree decomposition
Q-Index Code CX
Q-Index Status Confirmed Code
Grant ID 115002 (eTOX)
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
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School of Chemistry and Molecular Biosciences
Institute for Molecular Bioscience - Publications
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Created: Fri, 05 Apr 2013, 21:05:31 EST by Mrs Louise Nimwegen on behalf of School of Chemistry & Molecular Biosciences