def __init__(self,
targetid,
ensembler_stage=None,
project_dir='.',
log_level=None):
ensembler.core.check_project_toplevel_dir()
ensembler.utils.set_loglevel(log_level)
self.targetid = targetid
self.models_target_dir = os.path.join(
ensembler.core.default_project_dirnames.models, self.targetid)
self.project_dir = project_dir
if ensembler_stage is not None:
self.ensembler_stage = ensembler_stage
else:
for stagename in ['refine_explicit_md', 'refine_implicit_md']:
if check_ensembler_modeling_stage_complete(
stagename, targetid):
self.ensembler_stage = stagename
break
if self.ensembler_stage is None:
raise Exception(
'Models have not yet been built for this Ensembler project.'
)
if self.ensembler_stage == 'refine_implicit_md':
self.energies_filename = 'implicit-energies.txt'
elif self.ensembler_stage == 'refine_explicit_md':
self.energies_filename = 'explicit-energies.txt'
self._get_templateids_and_template_filepaths()
self._get_unique_models()
self._get_successful()
self._get_final_energies()
self._get_seqids()
def __init__(self, targetid, ensembler_stage=None, project_dir='.', log_level=None):
ensembler.core.check_project_toplevel_dir()
ensembler.utils.loglevel_setter(logger, log_level)
self.targetid = targetid
self.models_target_dir = os.path.join(ensembler.core.default_project_dirnames.models, self.targetid)
self.project_dir = project_dir
if ensembler_stage is not None:
self.ensembler_stage = ensembler_stage
else:
for stagename in ['refine_explicit_md', 'refine_implicit_md']:
if check_ensembler_modeling_stage_complete(stagename, targetid):
self.ensembler_stage = stagename
break
if self.ensembler_stage is None:
raise Exception('Models have not yet been built for this Ensembler project.')
if self.ensembler_stage == 'refine_implicit_md':
self.energies_filename = 'implicit-energies.txt'
elif self.ensembler_stage == 'refine_explicit_md':
self.energies_filename = 'explicit-energies.txt'
self._get_templateids_and_template_filepaths()
self._get_unique_models()
self._get_successful()
self._get_final_energies()
self._get_seqids()
def __init__(self,
targetid,
ensembler_stage=None,
project_dir='.',
log_level=None):
ensembler.core.check_project_toplevel_dir()
ensembler.utils.set_loglevel(log_level)
self.targetid = targetid
self.models_target_dir = os.path.join(
ensembler.core.default_project_dirnames.models, self.targetid)
self.project_dir = project_dir
if ensembler_stage is not None:
self.ensembler_stage = ensembler_stage
else:
for stagename in [
'refine_explicit_md', 'refine_implicit_md', 'build_models'
]:
if check_ensembler_modeling_stage_complete(
stagename, targetid):
self.ensembler_stage = stagename
break
if self.ensembler_stage is None:
raise Exception(
'Models have not yet been built for this Ensembler project.'
)
self.model_filename = ensembler.core.model_filenames_by_ensembler_stage[
self.ensembler_stage]
self._get_templateids_and_model_filepaths()
self._get_unique_models()
self._get_seqids()
self._store_highest_seqid_model()
self._mk_traj()
def __init__(self, targetid, ensembler_stage=None, project_dir='.', log_level=None):
ensembler.core.check_project_toplevel_dir()
ensembler.utils.set_loglevel(log_level)
self.targetid = targetid
self.models_target_dir = os.path.join(ensembler.core.default_project_dirnames.models, self.targetid)
self.project_dir = project_dir
if ensembler_stage is not None:
self.ensembler_stage = ensembler_stage
else:
for stagename in ['refine_explicit_md', 'refine_implicit_md', 'build_models']:
if check_ensembler_modeling_stage_complete(stagename, targetid):
self.ensembler_stage = stagename
break
if self.ensembler_stage is None:
raise Exception('Models have not yet been built for this Ensembler project.')
self.model_filename = ensembler.core.model_filenames_by_ensembler_stage[self.ensembler_stage]
self._get_templateids_and_model_filepaths()
self._get_unique_models()
self._get_seqids()
self._store_highest_seqid_model()
self._mk_traj()
def mktraj(targetid, ensembler_stage=None, traj_filepath=None, topol_filepath=None, models_data_filepath=None, process_only_these_templates=None):
"""Makes a trajectory for a given target, using mdtraj. The trajectory can be used with other
software, e.g. for visualization with PyMOL or VMD.
Parameters
----------
targetid : str
e.g. 'EGFR_HUMAN_D0'
ensembler_stage : str
The Ensembler stage from which to build models, e.g. 'build_models' results in a trajectory
built from the 'model.pdb.gz' files output by the build_models command.
options: build_models|refine_implicit_md|refine_explicit_md
default: most advanced stage for which model files are available
traj_filepath : str
default: models/[targetid]/traj-[ensembler_stage].xtc
topol_filepath : str
default: models/[targetid]/traj-[ensembler_stage]-topol.pdb
models_data_filepath :
default: models/[targetid]/traj-[ensembler_stage]-data.csv
process_only_these_templates : list of str
Returns
-------
traj : mdtraj.Trajectory
df : pandas.DataFrame
models data (e.g. sequence identities):
"""
ensembler.core.check_project_toplevel_dir()
models_target_dir = os.path.join(ensembler.core.default_project_dirnames.models, targetid)
logger.debug('Working on target %s' % targetid)
if ensembler_stage is None:
for stagename in ['refine_explicit_md', 'refine_implicit_md', 'build_models']:
if check_ensembler_modeling_stage_complete(stagename, targetid):
ensembler_stage = stagename
break
if ensembler_stage is None:
raise Exception('Models have not yet been built for this Ensembler project.')
if traj_filepath is None:
traj_filepath = os.path.join(models_target_dir, 'traj-{0}.xtc'.format(ensembler_stage))
if topol_filepath is None:
topol_filepath = os.path.join(models_target_dir, 'traj-{0}-topol.pdb'.format(ensembler_stage))
if models_data_filepath is None:
models_data_filepath = os.path.join(models_target_dir, 'traj-{0}-data.csv'.format(ensembler_stage))
if process_only_these_templates:
templateids = process_only_these_templates
else:
dirs = os.walk(models_target_dir).next()[1]
templateids = [dir for dir in dirs if '_D' in dir]
model_filename = ensembler.core.model_filenames_by_ensembler_stage[ensembler_stage]
valid_model_templateids = [templateid for templateid in templateids if os.path.exists(os.path.join(models_target_dir, templateid, model_filename))]
valid_model_filepaths = [os.path.join(models_target_dir, templateid, model_filename) for templateid in valid_model_templateids]
seqid_filepaths = [os.path.join(models_target_dir, templateid, 'sequence-identity.txt') for templateid in valid_model_templateids]
seqids = [float(open(seqid_filepath).read().strip()) if os.path.exists(seqid_filepath) else None for seqid_filepath in seqid_filepaths]
df = pd.DataFrame({
'templateid': valid_model_templateids,
'model_filepath': valid_model_filepaths,
'seqid': seqids,
})
df.sort(columns='seqid', inplace=True, ascending=False)
df.reset_index(drop=True, inplace=True)
df.to_csv(models_data_filepath, columns=['templateid', 'seqid'])
# construct traj
traj = mdtraj.load_pdb(df.model_filepath[0])
for model_filepath in df.model_filepath[1:]:
traj += mdtraj.load_pdb(model_filepath)
# superpose structured C-alphas
dssp = mdtraj.compute_dssp(traj[0])[0]
structured_resis_bool = (dssp == 'H') + (dssp == 'E')
alpha_indices = traj.topology.select_atom_indices('alpha')
structured_alpha_indices = np.array([alpha_indices[x] for x in range(traj.n_residues) if structured_resis_bool[x]])
traj.superpose(reference=traj, frame=0, atom_indices=structured_alpha_indices)
# write traj, and write first frame as pdb file
traj[0].save(topol_filepath)
traj.save(traj_filepath)
return traj, df
