Model-free simulation approach to molecular diffusion tensors: Lysozyme

This file contains part 1 (lysozyme) of the supplementary material for the following publication:

Title: Model-free simulation approach to molecular diffusion tensors
Authors: Guillaume Chevrot, Konrad Hinsen, Gerald R. Kneller
Journal: Journal of Chemical Physics 139, 154110 (2013)

It contains the software implementing the computations described in the article, the input datasets for lysozyme, the resulting output datasets, and the figures. A detailed list is given below.

 

 

The file lysozyme_diffusion.ap is a HDF5 file that can be read with any HDF5-compatible software, including the free HDFView package (http://www.hdfgroup.org/hdf-java-html/hdfview/). HDFView can be used to inspect the arrays and tables contained in this file. Reading the protein structure requires software that understands the Mosaic data model (http://bitbucket.org/molsim/mosaic/).

The file has been prepared using the ActivePapers framework (http://bitbucket.org/khinsen/active_papers_py) for reproducible research. It contains all the software used in the study that is described in the article, as well as most of the data, starting from the rigid-body trajectories. The original all-atom Molecular Dynamics trajectories are not included because of their size. All software is written in the Python language. The ActivePapers framework keeps track of which data was generated using which script and also notes the user name, machine name, and versions of all software packages used when running each script.

Readers wishing to modify and re-run the scripts, or to run them on different input data, should download and install the ActivePapers framework.

In order to reduce the file size, some intermediate data (the coordinate and velocity trajectories computed from the original rigid-body trajectories) has been removed from lysozyme_diffusion.ap. It can be restored using the ActivePapers command-line tool using the command

aptool update

 

Datasets contained in the file lysozyme_diffusion.ap

The computations are based on multiple independent simulations of lysozyme in water. The correlation functions are calculated for each simulation and are then averaged. The diffusion tensor is calculated from the averaged correlation functions. The correlation function plots are presented only for the averages.

All single-trajectory data has a numerical suffix. In the following list, only the first one ("_1") is shown.

 

1) Input data.

1.1) The reference structure of lysozyme, with the atomic masses, in Mosaic format.

  reference_structures
    reference_structure_1
      atom_masses
      configuration
      universe

1.2) The rigid-body trajectory, consisting of the time axis, the center-of-mass positions, and the orientation stored as a quaternion trajectory.

  trajectory
    center_of_mass_1
    orientation_1
    time

1.3) The temperature of the simulation.

  temperature

2) Preliminary analyses (calclet thermal_averages).

2.1) The reduced mass of lysozyme in its solvent box,and the tensor of inertia, needed for step 2.2.

  mass_and_inertia:
    reduced_mass_1
    inertia_tensor_1

2.2) The theoretical variances of the x, y, z components of the linear and angular velocities in thermal equilibrium. For comparison with the variances computed later from the trajectory.

  thermal_velocities
    variance_angular_velocity_laboratory_frame
    variance_angular_velocity_molecular_frame
    variance_velocity_laboratory_frame
    variance_velocity_molecular_frame

3) Preprocessing of the trajectory (calclet trajectory_processing). This computes the center-of-mass velocities and the angular velocities in the laboratory and molecular frames.

3.1) Means and variances of the linear and angular velocities. Ideally, the means should be zero and the variances equal to the values under "thermal_velocities".

  trajectory_statistics
    mean_angular_velocity_laboratory_frame_1
    mean_angular_velocity_molecular_frame_1
    mean_velocity_laboratory_frame_1
    mean_velocity_molecular_frame_1
    variance_angular_velocity_laboratory_frame_1
    variance_angular_velocity_molecular_frame_1
    variance_velocity_laboratory_frame_1
    variance_velocity_molecular_frame_1

3.2) Linear and angular velocities.

  velocity_trajectories
    rotation_laboratory_frame
    rotation_molecular_frame
    translation_laboratory_frame
    translation_molecular_frame

3.3) Linear and angular positions.

  coordinate_trajectories
    rotation_laboratory_frame_1
    rotation_molecular_frame_1
    translation_laboratory_frame_1
    translation_molecular_frame_1

4) Correlation functions and mean-square displacements (calclet correlation_functions).

  correlation_functions
    correlation_function_laboratory_frame_1
    correlation_function_molecular_frame_1
    correlation_function_laboratory_frame_averaged
    correlation_function_molecular_frame_averaged
    correlation_function_time
    mean_square_displacement_laboratory_frame_1
    mean_square_displacement_molecular_frame_1
    mean_square_displacement_laboratory_frame_averaged
    mean_square_displacement_molecular_frame_averaged
    mean_square_displacement_time

5) Manually set parameters used in computing the diffusion tensors.

  correlation_function_integration_limit
  correlation_function_plot_range
  msd_fit_range
  msd_plot_range

6) Diffusion tensors from the Kubo relations (integral over the velocity correlation functions) and from the slope of the mean-square displacement.

  diffusion_tensor_kubo_laboratory_frame
  diffusion_tensor_kubo_molecular_frame
  diffusion_tensor_msd_laboratory_frame
  diffusion_tensor_msd_molecular_frame