# Difference between revisions of "DsDNA persistence length"

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http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/eqn.png | http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/eqn.png | ||

− | In the <tt> EXAMPLES/PERSISTENCE_LENGTH </tt> directory, you will find a setup for calculating the persistence length of a 202 base pairs long dsDNA. | + | In the <tt> EXAMPLES/PERSISTENCE_LENGTH</tt> directory, you will find a setup for calculating the persistence length of a 202 base pairs long dsDNA. |

Note that for calculating a persistence length of a dsDNA, one needs a large number of decorrelated states. To obtain the states (which will be saved into a trajectory file), run the simulation program using the prepared input_persistence file: | Note that for calculating a persistence length of a dsDNA, one needs a large number of decorrelated states. To obtain the states (which will be saved into a trajectory file), run the simulation program using the prepared input_persistence file: | ||

− | <pre>oxDNA input_persistence</pre> | + | <pre>../../bin/oxDNA input_persistence</pre> |

− | The program will run a molecular dynamics simulation at 23 °C and record the individual configurations. | + | The program will run a molecular dynamics simulation at 23 °C and record the individual configurations. By default, they are saved in the <tt>trajectory.dat</tt> file. To analyze the data, use the python script <tt>dspl.py</tt>: |

− | <pre>dspl.py trajectory.dat init.top 10 50</pre> | + | <pre>./dspl.py trajectory.dat init.top 10 50</pre> |

This program will produce a table of correlations between helical vectors, http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/eqn2.png. | This program will produce a table of correlations between helical vectors, http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/eqn2.png. | ||

− | The program dspl.py requires base.py in the UTILS directory to be present and to have UTILS directory set in your PYTHONPATH environment variable. The program calculates the local helical axis vector (n_k) as a unit vector pointing from the midpoint of hydrogen bonding sites of k-th base to the midpoint between (k+1)-th | + | The program <tt>dspl.py</tt> requires <tt>base.py</tt> in the UTILS directory to be present and to have UTILS directory set in your PYTHONPATH environment variable. The program calculates the local helical axis vector (n_k) as a unit vector pointing from the midpoint of hydrogen bonding sites of k-th base pair to the midpoint between (k+1)-th base pair. |

− | The init.top file contains topology of the 202 base pairs long strand (included in the <tt> EXAMPLES/PERSISTENCE_LENGTH </tt>). In the example above, the program starts at the 10-th base pair and calculates correlations of n_10 with n_11, n_12, etc. up to n_60. It then prints out the correlations (one per line). Using an exponential fit to these data, one can find the persistence length, as illustrated in the following picture: | + | The init.top file contains topology of the 202 base pairs long strand (included in the <tt> EXAMPLES/PERSISTENCE_LENGTH</tt>). In the example above, the program starts at the 10-th base pair and calculates correlations of n_10 with n_11, n_12, etc. up to n_60. It then prints out the correlations (one per line). Using an exponential fit to these data, one can find the persistence length, as illustrated in the following picture: |

http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/ds.png | http://www-thphys.physics.ox.ac.uk/people/PetrSulc/images/ds.png | ||

− | The exponential fit shows, in this particular example, persistence length 124.8 base pairs. | + | The exponential fit shows, in this particular example, a persistence length of 124.8 base pairs. |

## Latest revision as of 11:34, 8 October 2014

## Persistence length of a double-stranded DNA

The example shows how to calculate a persistence length of a double stranded DNA molecule. dsDNA persistence length. The persistence length in this example is calculated using the following formula (see [1] for details):

In the ` EXAMPLES/PERSISTENCE_LENGTH` directory, you will find a setup for calculating the persistence length of a 202 base pairs long dsDNA.
Note that for calculating a persistence length of a dsDNA, one needs a large number of decorrelated states. To obtain the states (which will be saved into a trajectory file), run the simulation program using the prepared input_persistence file:

../../bin/oxDNA input_persistence

The program will run a molecular dynamics simulation at 23 °C and record the individual configurations. By default, they are saved in the `trajectory.dat` file. To analyze the data, use the python script `dspl.py`:

./dspl.py trajectory.dat init.top 10 50

This program will produce a table of correlations between helical vectors, .

The program `dspl.py` requires `base.py` in the UTILS directory to be present and to have UTILS directory set in your PYTHONPATH environment variable. The program calculates the local helical axis vector (n_k) as a unit vector pointing from the midpoint of hydrogen bonding sites of k-th base pair to the midpoint between (k+1)-th base pair.
The init.top file contains topology of the 202 base pairs long strand (included in the ` EXAMPLES/PERSISTENCE_LENGTH`). In the example above, the program starts at the 10-th base pair and calculates correlations of n_10 with n_11, n_12, etc. up to n_60. It then prints out the correlations (one per line). Using an exponential fit to these data, one can find the persistence length, as illustrated in the following picture:

The exponential fit shows, in this particular example, a persistence length of 124.8 base pairs.