demo.D060_Folding Namespace Reference

Functions
def	sample_folding
	Methods. More...
def	guess_disulfides
	if you create a custom protocol, you may have additional variables to reset, such as kT More...

Variables
tuple	scorefxn_low = create_score_function('score3')
	AddPyMOLObserver(test_pose, True) More...
tuple	scorefxn_high = get_fa_scorefxn()
tuple	folding_mover = protocols.moves.SequenceMover()
	add any other moves you desire More...
tuple	mc = MonteCarlo(test_pose, scorefxn_low, kT)
tuple	trial = TrialMover(folding_mover, mc)
tuple	folding = protocols.moves.RepeatMover(trial, cycles)
	for each trajectory, try cycles number of applications More...
tuple	jd = PyJobDistributor(job_output, jobs, scorefxn_high)
list	scores = [0]
int	counter = 0
tuple	parser = optparse.OptionParser()
	INTERPRETING RESULTS. More...
string	default = '../test/data/test_in.pdb'
string	help = 'the PDB file containing the protein to fold'
tuple	pose = Pose()
	fasta_filename = options.fasta_filename
tuple	f = open(fasta_filename, 'r')
tuple	sequence = f.readlines()
	pdb_filename = options.pdb_filename;
	long_frag_filename = options.long_frag_filename
tuple	long_frag_length = int(options.long_frag_length)
	short_frag_filename = options.short_frag_filename
tuple	short_frag_length = int(options.short_frag_length)
tuple	kT = float(options.kT)
tuple	long_inserts = int(options.long_inserts)
tuple	short_inserts = int(options.short_inserts)
tuple	cycles = int(options.cycles)
tuple	jobs = int(options.jobs)
	job_output = options.job_output

Function Documentation

def demo.D060_Folding.guess_disulfides	(		pose,
			cutoff = 6.0
	)

if you create a custom protocol, you may have additional variables to reset, such as kT

if you create a custom protocol, this section will most likely change, many protocols exist as single Movers or can be chained together in a sequence (see above) so you need only apply the final Mover b. apply the refinement protocol c. export the lowest scoring decoy structure for this trajectory -recover the lowest scoring decoy structure if you want to see the decoy scores, uncomment the line below scorefxn_high( test_pose )

A quick method for probing a protein for cysteine residues close to each
    other (within  <cutoff>  )

References ObjexxFCL.len(), fmt.print(), basic::options::OptionKeys::relax::range.range, sum(), and basic::options::OptionKeys::in::file.xyz.

def demo.D060_Folding.sample_folding	(		sequence,
			long_frag_filename,
			long_frag_length,
			short_frag_filename,
			short_frag_length,
			kT = 3.0,
			long_inserts = 1,
			short_inserts = 3,
			cycles = 40,
			jobs = 1,
			job_output = 'fold_output'
	)

Methods.

Performs
    exporting structures to a PyMOL instance
    Output structures are named  <job_output>_(job#).pdb

References name, and basic::options::OptionKeys::relax::range.range.

Variable Documentation

int demo.D060_Folding.counter = 0

Referenced by supercharge.design_supercharge(), main(), utility::graph::Graph.output_connectivity(), utility::graph::Digraph.output_connectivity(), sequence_tolerance_main(), Solver.Solve(), and numeric::UniformRotationSampler.UniformRotationSampler().

tuple demo.D060_Folding.cycles = int(options.cycles)

string demo.D060_Folding.default = '../test/data/test_in.pdb'

tuple demo.D060_Folding.f = open(fasta_filename, 'r')

Referenced by binder.base_namespace(), numeric::interpolation::periodic_range::full.bilinearly_interpolated(), numeric::interpolation::periodic_range::half.bilinearly_interpolated(), binder.binding_public_data_members(), numeric::kinematic_closure.bridgeObjects(), fmt::BufferedFile.BufferedFile(), numeric::kinematic_closure.buildsturm(), close_loops(), numeric::deriv.dihedral_p1_cosine_deriv_first(), numeric::deriv.dihedral_p2_cosine_deriv_first(), numeric::kinematic_closure.evalpoly(), ObjexxFCL::format.F(), fmt::File.fdopen(), figure_out_fold_tree(), utility.filename(), utility::signals::SignalHub< ReturnType, Signal >.find_connection(), foo(), B.foo_member(), B.foo_member_const(), B.foo_static(), fmt.fprintf(), binder::Context.generate(), numeric.hsv_to_rgb(), numeric::geometry::hashing::xyzStripeHash.init(), basic.interpolate_bilinear_by_value(), basic.interpolate_trilinear_by_value(), numeric::interpolation::periodic_range::full.interpolated(), numeric::interpolation::periodic_range::half.interpolated(), numeric::fourier.kf_work(), binder.last_namespace(), ObjexxFCL.left_Fstring_of(), ObjexxFCL.left_string_of(), utility::options::OptionCollection.load_options_from_stream(), main(), ObjexxFCL.mod(), nucleobase_probe_score_test(), numeric::kinematic_closure.numchanges(), numeric::kinematic_closure.numroots(), numeric::deriv.p1_theta_deriv(), fmt.print(), binder::Config.read(), ObjexxFCL.right_Fstring_of(), ObjexxFCL.right_string_of(), DockFragmentsMover.run(), run_pep_prep(), RunPepSpec(), DougsDockDesignMinimizeMagicMover.setup_pert_foldtree(), basic.subtract_radian_angles(), basic::Tracer.super_mute(), numeric::linear_algebra.svdcmp(), basic::svd::SVD_Solver.svdcmp(), svm_train(), svm_train_one(), numeric::kinematic_closure.test_triaxialCoefficients(), numeric::kinematic_closure.torsion(), numeric::kinematic_closure::radians.torsion(), binder.update_source_file(), and basic::Emitter.write_raw().

demo.D060_Folding.fasta_filename = options.fasta_filename

tuple demo.D060_Folding.folding = protocols.moves.RepeatMover(trial, cycles)

for each trajectory, try cycles number of applications

tuple demo.D060_Folding.folding_mover = protocols.moves.SequenceMover()

add any other moves you desire

string demo.D060_Folding.help = 'the PDB file containing the protein to fold'

tuple demo.D060_Folding.jd = PyJobDistributor(job_output, jobs, scorefxn_high)

Referenced by main().

demo.D060_Folding.job_output = options.job_output

tuple demo.D060_Folding.jobs = int(options.jobs)

tuple demo.D060_Folding.kT = float(options.kT)

demo.D060_Folding.long_frag_filename = options.long_frag_filename

tuple demo.D060_Folding.long_frag_length = int(options.long_frag_length)

tuple demo.D060_Folding.long_inserts = int(options.long_inserts)

tuple demo.D060_Folding.mc = MonteCarlo(test_pose, scorefxn_low, kT)

tuple demo.D060_Folding.parser = optparse.OptionParser()

INTERPRETING RESULTS.

COMMANDLINE COMPATIBILITY

demo.D060_Folding.pdb_filename = options.pdb_filename;

tuple demo.D060_Folding.pose = Pose()

tuple demo.D060_Folding.scorefxn_high = get_fa_scorefxn()

Referenced by demo.D080_Loop_modeling.sample_single_loop_modeling().

tuple demo.D060_Folding.scorefxn_low = create_score_function('score3')

AddPyMOLObserver(test_pose, True)

list demo.D060_Folding.scores = [0]

Referenced by add_rosetta_options_10(), main(), and save_per_residue_scores().

tuple demo.D060_Folding.sequence = f.readlines()

Referenced by add_rosetta_options_12(), add_rosetta_options_13(), composite_sequences_from_cmd_line(), create_base_pair_step_database_test(), utility::CSI_Sequence.CSI_Sequence(), get_n_mer_maltose(), get_n_mer_polyalanine(), main(), my_main(), nucleobase_probe_score_test(), read_fasta(), rna_build_helix_test(), rna_thread_test(), DockFragmentsMover.run(), run_pep_prep(), and sequences_from_cmd_line().

demo.D060_Folding.short_frag_filename = options.short_frag_filename

tuple demo.D060_Folding.short_frag_length = int(options.short_frag_length)

tuple demo.D060_Folding.short_inserts = int(options.short_inserts)

tuple demo.D060_Folding.trial = TrialMover(folding_mover, mc)