Sequence-Dependent Persistence Lengths of DNA

J Chem Theory Comput. 2017 Apr 11;13(4):1539-1555. doi: 10.1021/acs.jctc.6b00904. Epub 2017 Mar 24.

Abstract

A Monte Carlo code applied to the cgDNA coarse-grain rigid-base model of B-form double-stranded DNA is used to predict a sequence-averaged persistence length of lF = 53.5 nm in the sense of Flory, and of lp = 160 bp or 53.5 nm in the sense of apparent tangent-tangent correlation decay. These estimates are slightly higher than the consensus experimental values of 150 bp or 50 nm, but we believe the agreement to be good given that the cgDNA model is itself parametrized from molecular dynamics simulations of short fragments of length 10-20 bp, with no explicit fit to persistence length. Our Monte Carlo simulations further predict that there can be substantial dependence of persistence lengths on the specific sequence [Formula: see text] of a fragment. We propose, and confirm the numerical accuracy of, a simple factorization that separates the part of the apparent tangent-tangent correlation decay [Formula: see text] attributable to intrinsic shape, from a part [Formula: see text] attributable purely to stiffness, i.e., a sequence-dependent version of what has been called sequence-averaged dynamic persistence length l̅d (=58.8 nm within the cgDNA model). For ensembles of both random and λ-phage fragments, the apparent persistence length [Formula: see text] has a standard deviation of 4 nm over sequence, whereas our dynamic persistence length [Formula: see text] has a standard deviation of only 1 nm. However, there are notable dynamic persistence length outliers, including poly(A) (exceptionally straight and stiff), poly(TA) (tightly coiled and exceptionally soft), and phased A-tract sequence motifs (exceptionally bent and stiff). The results of our numerical simulations agree reasonably well with both molecular dynamics simulation and diverse experimental data including minicircle cyclization rates and stereo cryo-electron microscopy images.

MeSH terms

  • DNA / chemistry*
  • Molecular Dynamics Simulation*
  • Monte Carlo Method

Substances

  • DNA