The Sequence-Dependent Statistical Mechanics and Persistence Lengths of DNA

Event details
Date | 14.04.2016 |
Hour | 16:30 › 17:30 |
Speaker |
Prof. John H. Maddocks EPFL SB MATHGEOM LCVMM MA C1 582 (Bâtiment MA) Station 8 CH-1015 Lausanne |
Location | |
Category | Conferences - Seminars |
The recently developed cgDNA sequence-dependent rigid-base coarse grain model of DNA is parameterised from Molecular Dynamics simulations at the scale of 20bp and less. The sequence-dependent ground states predicted by the cgDNA model compare reasonably well with both NMR and X-ray crystal experimental data. The cgDNA free energy also allows numerically efficient simulations at much longer length (and time) scales, for example computation of looping and cyclisation J-factors. The cgDNA model also allows efficient Monte Carlo sampling of the configuration space equilibrium ensemble for DNA fragments with arbitrarily prescribed sequence at length scales of a few hundred to a few thousand bp and more. These Monte Carlo simulations reveal strong sequence dependence of the classic correlation functions of polymer physics through the effect of both intrinsic shape and differing stiffnesses, and moreover that these two effects can be factored in a simple way. On the other hand when the ensem
ble includes averaging over sequence, the cgDNA Monte Carlo simulations predict the single effective persistence length of 163 bp, which is in remarkably good agreement with the consensus experimental value of 150 bp or so.
Joint work with A. Grandchamp, J. Glowacki, R. Manning, and J. Mitchell
ble includes averaging over sequence, the cgDNA Monte Carlo simulations predict the single effective persistence length of 163 bp, which is in remarkably good agreement with the consensus experimental value of 150 bp or so.
Joint work with A. Grandchamp, J. Glowacki, R. Manning, and J. Mitchell
Practical information
- General public
- Free
Organizer
- Prof. Ulrich Lorenz
Contact
- Prof. Ulrich Lorenz