Charge group partitioning in biomolecular simulation

Stefan Canzar, Mohammed El-Kebir, René Pool, Khaled Elbassioni, Alpesh K. Malde, Alan E. Mark, Daan P. Geerke, Leen Stougie, Gunnar W. Klau

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations


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 gromos 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 κ. We show NP-hardness and give an exact algorithm capable of solving practical problem instances to provable optimality in a fraction of a second.

Original languageBritish English
Title of host publicationResearch in Computational Molecular Biology - 16th Annual International Conference, RECOMB 2012, Proceedings
Number of pages15
StatePublished - 2012
Event16th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2012 - Barcelona, Spain
Duration: 21 Apr 201224 Apr 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7262 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2012


  • atomic force fields
  • biomolecular simulation
  • charge groups
  • dynamic programming
  • gromos
  • tree-decomposition


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