flexserv package

Submodules

flexserv.bd_run module

Module containing the bd_run class and the command line interface.

class flexserv.bd_run.BDRun(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv BDRun
Wrapper of the Browian Dynamics tool from the FlexServ module.
Generates protein conformational structures using the Brownian Dynamics (BD) method.
Parameters:

  • input_pdb_path (str) – Input PDB file. File type: input. Sample file. Accepted formats: pdb (edam:format_1476).

  • output_log_path (str) –

    Output log file. File type: output. Sample file. Accepted formats: log (edam:format_2330), out (edam:format_2330), txt (edam:format_2330), o (edam:format_2330).

  • output_crd_path (str) –

    Output ensemble. File type: output. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“bd”) BD binary path to be used.

    • time (int) - (1000000) Total simulation time (ps)

    • dt (float) - (1e-15) Integration time (ps)

    • wfreq (int) - (1000) Writing frequency (ps)

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.flexserv.bd_run import bd_run
prop = {
    'binary_path': 'bd'
}
flexserv_run(input_pdb_path='/path/to/bd_input.pdb',
             output_log_path='/path/to/bd_log.log',
             output_crd_path='/path/to/bd_ensemble.crd',
             properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ BDRun module.

flexserv.bd_run.bd_run(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs) → int[source]

Create BDRun method

flexserv.bd_run.main()[source]

flexserv.dmd_run module

Module containing the dmd_run class and the command line interface.

class flexserv.dmd_run.DMDRun(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv DMDRun
Wrapper of the Discrete Molecular Dynamics tool from the FlexServ module.
Generates protein conformational structures using the Discrete Molecular Dynamics (DMD) method.
Parameters:

  • input_pdb_path (str) –

    Input PDB file. File type: input. Sample file. Accepted formats: pdb (edam:format_1476).

  • output_log_path (str) –

    Output log file. File type: output. Sample file. Accepted formats: log (edam:format_2330), out (edam:format_2330), txt (edam:format_2330), o (edam:format_2330).

  • output_crd_path (str) –

    Output ensemble. File type: output. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“dmdgoopt”) DMD binary path to be used.

    • dt (float) - (1e-12) Integration time (s)

    • temperature (int) - (300) Simulation temperature (K)

    • frames (int) - (1000) Number of frames in the final ensemble

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.flexserv.dmd_run import dmd_run
prop = {
    'binary_path': 'dmdgoopt'
}
flexserv_run(input_pdb_path='/path/to/dmd_input.pdb',
             output_log_path='/path/to/dmd_log.log',
             output_crd_path='/path/to/dmd_ensemble.crd',
             properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ BDRun module.

flexserv.dmd_run.dmd_run(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs) → int[source]

Create DMDRun method

flexserv.dmd_run.main()[source]

flexserv.nma_run module

Module containing the nma_run class and the command line interface.

class flexserv.nma_run.NMARun(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs)[source]

Bases: BiobbObject

biobb_flexserv NMARun
Wrapper of the Normal Mode Analysis tool from the FlexServ module.
Generates protein conformational structures using the Normal Mode Analysis (NMA) method.
Parameters:

  • input_pdb_path (str) –

    Input PDB file. File type: input. Sample file. Accepted formats: pdb (edam:format_1476).

  • output_log_path (str) –

    Output log file. File type: output. Sample file. Accepted formats: log (edam:format_2330), out (edam:format_2330), txt (edam:format_2330), o (edam:format_2330).

  • output_crd_path (str) –

    Output ensemble. File type: output. Sample file. Accepted formats: crd (edam:format_3878), mdcrd (edam:format_3878), inpcrd (edam:format_3878).

  • properties (dict - Python dictionary object containing the tool parameters, not input/output files) –

    • binary_path (str) - (“diaghess”) NMA binary path to be used.

    • frames (int) - (1000) Number of frames in the final ensemble

    • nvecs (int) - (50) Number of vectors to take into account for the ensemble generation

    • remove_tmp (bool) - (True) [WF property] Remove temporal files.

    • restart (bool) - (False) [WF property] Do not execute if output files exist.

Examples

This is a use example of how to use the building block from Python:

from biobb_flexserv.flexserv.bd_run import bd_run
prop = {
    'binary_path': 'diaghess'
}
flexserv_run(input_pdb_path='/path/to/nma_input.pdb',
             output_log_path='/path/to/nma_log.log',
             output_crd_path='/path/to/nma_ensemble.crd',
             properties=prop)
Info:
launch()[source]

Launches the execution of the FlexServ NMARun module.

flexserv.nma_run.main()[source]
flexserv.nma_run.nma_run(input_pdb_path: str, output_log_path: str, output_crd_path: str, properties: dict | None = None, **kwargs) → int[source]

Create NMARun method