Spin label EPR-based characterization of biosystem complexity

J. Strancar, T. Koklic, Z. Arsov, B. Filipic, D. Stopar, M.A. Hemminga

Research output: Contribution to journalArticleAcademicpeer-review

65 Citations (Scopus)


Following the widely spread EPR spin-label applications for biosystem characterization, a novel approach is proposed for EPR-based characterization of biosystem complexity. Hereto a computational method based on a hybrid evolutionary optimization (HEO) is introduced. The enormous volume of information obtained from multiple HEO runs is reduced with a novel so-called GHOST condensation method for automatic detection of the degree of system complexity through the construction of two-dimensional solution distributions. The GHOST method shows the ability of automatic quantitative characterization of groups of solutions, e.g. the determination of average spectral parameters and group contributions. The application of the GHOST condensation algorithm is demonstrated on four synthetic examples of different complexity and applied to two physiologically relevant examples - the determination of domains in biomembranes (lateral heterogeneity) and the study of the low-resolution structure of membrane proteins
Original languageEnglish
Pages (from-to)394-406
Number of pages13
JournalJournal of Chemical Information and Modeling
Issue number2
Publication statusPublished - 2005


  • major coat protein
  • paramagnetic-resonance-spectra
  • lipid interactions
  • membranes
  • dynamics
  • simulations
  • parameters
  • motion
  • domain
  • model

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