AvTraj

AvTraj is tool to calculate FRET observables from MD-trajectories. Read , write and analyze accessible volumes (AVs) using MD trajectories as an input with only a few lines of Python code. By the use of LabelLib AvTraj provides programmatic access to latestdevelopments in implicit dye models for FRET experiments .

AvTraj is a python library that allows users to perform simulations of accessible volumes for molecular dynamics (MD) trajectories. AvTraj serves as a high-level interface for the development of new methodologies for structure-based fluorescence spectroscopy.

Features include:

    A wide support of diverse MD formats by the use of MDTraj. Extremely
     fast calculation of AVs by the use of LabelLib (e.g. xxxx the speed
      of yyyy). Extensive analysis functions including those that compute
    inter-dye distances, FRET-efficiencies, fluorescence decays, distance
     distributions, and an Pythonic API.

AVTraj includes a command-line application, avana, for screening and analyzing structural models.

Relation of other software and libraries

LabelLib serves as core low-level library for the software Olga and the higher-level Python library AvTraj. The deprecated software FPS is independent of LabelLib.

Olga is a software dedicated towards experimentalists. Olga provides a graphical user interface for the calculation of accessible volumes (AVs), screen a set of structural models against experimental observables, rigid-body docking, and the optimal design of new FRET experiments.

AvTraj AvTraj is a Python library for the calculation of accessible volumes (AVs ), screening. AvTraj facilitates the development of new analytical approaches for FRET-based structural models. Avtraj facilitates processing of MD-simulations and the development of Python scripts handling FRET-based structural models.

FPS is a software with a graphical user interface for the FRET-based structural modeling. FPS can calculate accessible volumes (AVs), screen a set of structural models against experimental observables, and can generate new structural models by rigid-body docking using experimental FRET data.

Installation

Anaconda

The software depends on other libraries provided by conda-forge. Thus, as a first step, the conda-forge channel needs to be added.

conda --add channels conda-forge

In a second step, the avtraj package can be installed.

conda --add channels tpeulen
conda install avtraj

Code Example

    import mdtraj as md
    import avtraj as avt
    import json
    
    # First load an MD trajectory by mdtraj
    xtc_filename = './test/data/xtc/1am7_corrected.xtc'
    topology_filename = './test/data/xtc/1am7_protein.pdb'
    traj = md.load(
        xtc_filename,
        top=topology_filename
    )
    # Define your accessible volume (AV) parameters
    av_parameters_donor = {
        'simulation_type': 'AV1',
        'linker_length': 20.0,
        'linker_width': 1.0,
        'radius1': 3.5,
        'simulation_grid_resolution': 1.0,
        'residue_seq_number': 57,
        'atom_name': 'CA'
    }
    
    # Pass a trajectory to fps.AVTrajectory. This creates an object, which can be
    # accessed as a list. The objects within the "list" are accessible volumes
    av_traj_donor = avt.AVTrajectory(
        traj,
        av_parameters=av_parameters_donor,
        name='57'
    )
    # These accessible volumes can be saved as xyz-file
    av_traj_donor[0].save_av()
    
    av_parameters_acceptor = {
        'simulation_type': 'AV1',
        'linker_length': 20.0,
        'linker_width': 1.0,
        'radius1': 3.5,
        'simulation_grid_resolution': 1.0,
        'residue_seq_number': 136,
        'atom_name': 'CA'
    }
    
    # The dye parameters can either be passed explicitly on creation of the object
    av_traj_acceptor = avt.AVTrajectory(
        traj,
        av_parameters=av_parameters_acceptor,
        name='136'
    )
    av_traj_acceptor[0].save_av()
    
    
    # To calculate a trajectory of distances and distance distributions first a
    # labeling file and a "distance file" needs to be specified. The distance
    # file contains a set of labeling positions and distances and should be
    # compatible to the labeling files used by the software "Olga".
    # or by the tool `label_structure` provided by the software ChiSurf.
    labeling_file = './test/data/labeling.fps.json'
    av_dist = avt.AvDistanceTrajectory(
        traj,
        json.load(
            open(
                labeling_file
            )
        )
    )
    print(av_dist[:10])

Citations

• MDTraj -
• FPS -

License

GNU LGPL version 2.1, or at your option a later version of the license. Various sub-portions of this library may be independently distributed under different licenses. See those files for their specific terms.