#!/usr/bin/env python
"""Module containing the MemProtMDSimSearch class and the command line interface."""
from typing import Optional
from biobb_common.generic.biobb_object import BiobbObject
from biobb_common.tools.file_utils import launchlogger
from biobb_io.api.common import check_output_path, get_memprotmd_sim_search, write_json
[docs]
class MemProtMDSimSearch(BiobbObject):
"""
| biobb_io MemProtMDSimSearch
| This class is a wrapper of the MemProtMD to perform advanced searches in the MemProtMD DB using its REST API.
| Wrapper for the `MemProtMD DB REST API <http://memprotmd.bioch.ox.ac.uk/>`_ to perform advanced searches.
Args:
output_simulations (str): Path to the output JSON file. File type: output. `Sample file <https://github.com/bioexcel/biobb_io/raw/master/biobb_io/test/reference/api/output_sim_search_schema_validator.json>`_. Accepted formats: json (edam:format_3464).
properties (dic - Python dictionary object containing the tool parameters, not input/output files):
* **collection_name** (*str*) - ("refs") Name of the collection to query.
* **keyword** (*str*) - (None) String to search for in the database metadata. Examples are families like gpcr or porin. Values: porin, outer membrane protein, membrane protein, gpcr (7-transmembrane domain receptors transducing extracellular signals into cells), ion channels, rhodopsin (The most famous GPCRs), abc, mip (Major Intrinsic Protein (MIP)/FNT superfamily: specific for the transport of water and small neutral solutes), ligand-gated (Ligand-dependent signal conversion from chemical signals to electric signals), ammonia (Regulating transepithelial ammonia secretion), mapeg (Eicosanoid and Glutathione metabolism proteins), transmembrane (Heme biosynthesis), protein, kinase (Tyrosine-protein kinases: regulate central nervous system; gene transcription and cell differentiation), glycoprotein (Expression of TCR complex), immunoglobulin (Recognition; binding and adhesion process of cells), integrin (Bridges for cell-cell and cell-extracellular matrix interaction), bnip3 (BNip3 protein family: protect cell from apoptosis), bcl-2 (Regulating cell-death; either induce apoptotic or inhibit apoptosis), atpase (ATPase regulators; P-P-bond hydrolysis-driven transporter), cytochrome (Terminal oxidase enzyme in electron transfer chain), nadp (Transmembrane proteins with NAD(P)-binding Rossmann-fold domains: monoamine oxidase; deaminates norepinephrine; epinephrine; serotonin and dopamine), a4 (Amyloid beta A4 protein; involved in alzheimer's diseases), lysosome (Lysosome-associated membrane glycoprotein: specific to lysosomes; CD107), necrosis (Tumor necrosis factor recepto: binding with TNF and NGF; interacting with a variety of signal molecules; highly associated with apoptosis), oxidoreductase (DHODH; biosynthesis of orotate), ceramidase (Neutral/alkaline ceramidase: converting sphingolipid to sphingosine), dehydrogenase (Aldehyde dehydrogenase:ALDH; Oxidation of aldehydes), mitochondrial, plastid.
* **remove_tmp** (*bool*) - (True) [WF property] Remove temporal files.
* **restart** (*bool*) - (False) [WF property] Do not execute if output files exist.
* **sandbox_path** (*str*) - ("./") [WF property] Parent path to the sandbox directory.
Examples:
This is a use example of how to use the building block from Python::
from biobb_io.api.memprotmd_sim_search import memprotmd_sim_search
prop = {
'collection_name': 'refs',
'keyword': 'porin'
}
memprotmd_sim_search(output_simulations='/path/to/newSimulationSearch.json',
properties=prop).launch()
Info:
* wrapped_software:
* name: MemProtMD DB
* license: Creative Commons
* ontology:
* name: EDAM
* schema: http://edamontology.org/EDAM.owl
"""
def __init__(self, output_simulations, properties=None, **kwargs) -> None:
properties = properties or {}
# Call parent class constructor
super().__init__(properties)
self.locals_var_dict = locals().copy()
# Input/Output files
self.io_dict = {"out": {"output_simulations": output_simulations}}
# Properties specific for BB
self.collection_name = properties.get("collection_name", "refs")
self.keyword = properties.get("keyword", None)
self.properties = properties
# Check the properties
self.check_properties(properties)
self.check_arguments()
[docs]
def check_data_params(self, out_log, err_log):
"""Checks all the input/output paths and parameters"""
self.output_simulations = check_output_path(
self.io_dict["out"]["output_simulations"],
"output_simulations",
False,
out_log,
self.__class__.__name__,
)
[docs]
@launchlogger
def launch(self) -> int:
"""Execute the :class:`MemProtMDSimSearch <api.memprotmd_sim_search.MemProtMDSimSearch>` api.memprotmd_sim_search.MemProtMDSimSearch object."""
# check input/output paths and parameters
self.check_data_params(self.out_log, self.err_log)
# Setup Biobb
if self.check_restart():
return 0
self.keyword = self.keyword.strip().lower()
# get JSON object
json_string = get_memprotmd_sim_search(
self.collection_name, self.keyword, self.out_log, self.global_log
)
# write JSON file
write_json(json_string, self.output_simulations, self.out_log, self.global_log)
self.check_arguments(output_files_created=True, raise_exception=False)
return 0
[docs]
def memprotmd_sim_search(
output_simulations: str, properties: Optional[dict] = None, **kwargs
) -> int:
"""Execute the :class:`MemProtMDSimSearch <api.memprotmd_sim_search.MemProtMDSimSearch>` class and
execute the :meth:`launch() <api.memprotmd_sim_search.MemProtMDSimSearch.launch>` method."""
return MemProtMDSimSearch(**dict(locals())).launch()
memprotmd_sim_search.__doc__ = MemProtMDSimSearch.__doc__
main = MemProtMDSimSearch.get_main(memprotmd_sim_search, "Wrapper for the MemProtMD DB REST API (http://memprotmd.bioch.ox.ac.uk/) to perform advanced searches.")
if __name__ == "__main__":
main()