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Functions | Variables
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, pyrosetta.distributed.io.pose_from_sequence, and basic::options::OptionKeys::relax::range.range.

Variable Documentation

int demo.D060_Folding.counter = 0
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 add_rosetta_options_1(), numeric::VoxelArray< _Float, _Value >.at(), 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.cubic_polynomial_from_spline(), 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(), 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::TracerImpl.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)
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()
tuple demo.D060_Folding.scorefxn_low = create_score_function('score3')

AddPyMOLObserver(test_pose, True)

list demo.D060_Folding.scores = [0]
tuple demo.D060_Folding.sequence = f.readlines()
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)