Multimerization-cyclization of DNA fragments as a method of conformationalanalysis

Citation
Aa. Podtelezhnikov et al., Multimerization-cyclization of DNA fragments as a method of conformationalanalysis, BIOPHYS J, 79(5), 2000, pp. 2692-2704
Citations number
38
Categorie Soggetti
Biochemistry & Biophysics
Journal title
BIOPHYSICAL JOURNAL
ISSN journal
00063495 → ACNP
Volume
79
Issue
5
Year of publication
2000
Pages
2692 - 2704
Database
ISI
SICI code
0006-3495(200011)79:5<2692:MODFAA>2.0.ZU;2-M
Abstract
Ligation of short DNA fragments results in the formation of linear and circ ular multimers of various lengths. The distribution of products in such a r eaction is often used to evaluate fragment bending caused by specific chemi cal modification, by bound ligands or by the presence of irregular structur al elements. We have developed a more rigorous quantitative approach to the analysis of such experimental data based on determination of j-factors for different multimers from the distribution of the reaction products. j-fact ors define the effective concentration of one end of a linear chain in the vicinity of the other end. To extract j-factors we assumed that kinetics of the reaction is described by a system of differential equations where j-fa ctors appear as coefficients. The assumption was confirmed by comparison wi th experimental data obtained here for DNA fragments containing A-tracts. A t the second step of the analysis j-factors are used to determine conformat ional parameters of DNA fragments: the equilibrium bend angle, the bending rigidity of the fragment axis, and the total twist of the fragments. This p rocedure is based on empirical equations that connect the conformational pa rameters with the set of j-factors. To obtain the equations, we computed j- factors for a large array of conformational parameters that describe model fragments. The approach was tested on both simulated and actual experimenta l data for DNA fragments containing A-tracts. A-tract DNA bend angle determ ined here is in good agreement with previously published data. We have esta blished a set of experimental conditions necessary for the data analysis to be successful.