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arxiv: 1408.5603 · v2 · pith:R7BPJESWnew · submitted 2014-08-24 · ⚛️ physics.bio-ph · cond-mat.soft

Self-avoiding worm-like chain model for dsDNA loop formation

classification ⚛️ physics.bio-ph cond-mat.soft
keywords chainworm-likeloopcomputedsdnaexcludedformincrease
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We compute for the first time the effects of excluded volume on the probability for double-stranded DNA to form a loop. We utilize a Monte-Carlo algorithm for generation of large ensembles of self- avoiding worm-like chains, which are used to compute the J-factor for varying lengthscales. In the entropic regime, we confirm the scaling-theory prediction of a power-law drop off of -1.92, which is significantly stronger than the -1.5 power-law predicted by the non-self-avoiding worm-like chain model. In the elastic regime, we find that the angle-independent end-to-end chain distribution is highly anisotropic. This anisotropy, combined with the excluded volume constraints, lead to an increase in the J-factor of the self-avoiding worm-like chain by about half an order of magnitude relative to its non-self-avoiding counterpart. This increase could partially explain the anomalous results of recent cyclization experiments, in which short dsDNA molecules were found to have an increased propensity to form a loop.

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