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Analyzing Forced Unfolding of Protein Tandems by Ordered Variates, 2: Dependent Unfolding Times

E. Bura ^*, D. K. Klimov  and V. Barsegov 

^* Department of Statistics, George Washington University, Washington, District of Columbia 20052; Department of Bioinformatics and Computational Biology, George Mason University, Manassas, Virginia 20110; and Department of Chemistry, University of Massachusetts, Lowell, Massachusetts 01854

Correspondence: Address reprint requests to V. Barsegov, Tel.: 978-934-3661; Fax: 978-934-3013; E-mail: Valeri_Barsegov{at}uml.edu.

Statistical analyses of forced unfolding data for protein tandems, i.e., unfolding forces (force-ramp) and unfolding times (force-clamp), used in single-molecule dynamic force spectroscopy rely on the assumption that the unfolding transitions of individual protein domains are independent (uncorrelated) and characterized, respectively, by identically distributed unfolding forces and unfolding times. In our previous work, we showed that in the experimentally accessible piconewton force range, this assumption, which holds at a lower constant force, may break at an elevated force level, i.e., the unfolding transitions may become correlated when force is increased. In this work, we develop much needed statistical tests for assessing the independence of the unobserved forced unfolding times for individual protein domains in the tandem and equality of their parent distributions, which are based solely on the observed ordered unfolding times. The use and performance of these tests are illustrated through the analysis of unfolding times for computer models of protein tandems. The proposed tests can be used in force-clamp atomic force microscopy experiments to obtain accurate information on protein forced unfolding and to probe data on the presence of interdomain interactions. The order statistics-based formalism is extended to cover the analysis of correlated unfolding transitions. The use of order statistics leads naturally to the development of new kinetic models, which describe the probabilities of ordered unfolding transitions rather than the populations of chemical species.