Rosetta  2020.37
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Variables
loops_kic Namespace Reference

Variables

int MAX_KIC_BUILD_ATTEMPTS = 10000
 
list args
 
tuple p = Pose()
 
tuple starting_p = Pose()
 
tuple scorefxn_low = create_score_function( 'cen_std' )
 
tuple scorefxn_high = create_score_function( 'standard', 'score12' )
 
tuple pymol = rosetta.PyMOLMover()
 
int loop_begin = 145
 
int loop_end = 155
 
int loop_cut = 150
 
tuple my_loop = Loop( loop_begin, loop_end, loop_cut )
 
tuple my_loops = Loops()
 
tuple movemap = MoveMap()
 
tuple kic_mover = KinematicMover()
 
tuple to_centroid = protocols.simple_moves.SwitchResidueTypeSetMover( 'centroid' )
 
tuple to_fullatom = protocols.simple_moves.SwitchResidueTypeSetMover( 'fa_standard' )
 
tuple recover_sidechains = protocols.simple_moves.ReturnSidechainMover( starting_p )
 
tuple task_pack = TaskFactory.create_packer_task( starting_p )
 
tuple pack = protocols.minimization_packing.PackRotamersMover( scorefxn_high, task_pack )
 
tuple mm = MoveMap()
 
float tol = 0.001
 
string min_type = "linmin"
 
tuple linmin_mover = protocols.minimization_packing.MinMover( mm, scorefxn_low, min_type, tol, True )
 
tuple starting_p_centroid = Pose()
 
 success = False
 
int outer_cycles = 10
 
int inner_cycles = 30
 
float init_temp = 2.0
 
float final_temp = 1.0
 
tuple gamma = math.pow( ( final_temp/init_temp ),( 1.0/( outer_cycles*inner_cycles ) ) )
 
 kT = init_temp
 
tuple mc = MonteCarlo( p, scorefxn_low, kT )
 
tuple kic_start = randrange( loop_begin, loop_end - 1 )
 
tuple kic_end = randrange( kic_start+2, loop_end+1 )
 
tuple middle_offset = ( kic_end - kic_start )
 
 kic_middle = kic_start+middle_offset
 
tuple rms = loop_rmsd( p, starting_p, my_loops )
 
tuple loop_refine = LoopMover_Refine_KIC( my_loops )
 

Variable Documentation

list loops_kic.args
Initial value:
1 = [ "app",
2  "-database minirosetta_database", \
3  "-loops:fast" ]
float loops_kic.final_temp = 1.0
tuple loops_kic.gamma = math.pow( ( final_temp/init_temp ),( 1.0/( outer_cycles*inner_cycles ) ) )
float loops_kic.init_temp = 2.0
int loops_kic.inner_cycles = 30
tuple loops_kic.kic_end = randrange( kic_start+2, loop_end+1 )
loops_kic.kic_middle = kic_start+middle_offset
tuple loops_kic.kic_mover = KinematicMover()
tuple loops_kic.kic_start = randrange( loop_begin, loop_end - 1 )
loops_kic.kT = init_temp
tuple loops_kic.linmin_mover = protocols.minimization_packing.MinMover( mm, scorefxn_low, min_type, tol, True )
int loops_kic.loop_begin = 145
int loops_kic.loop_cut = 150
int loops_kic.loop_end = 155
tuple loops_kic.loop_refine = LoopMover_Refine_KIC( my_loops )
int loops_kic.MAX_KIC_BUILD_ATTEMPTS = 10000
tuple loops_kic.mc = MonteCarlo( p, scorefxn_low, kT )
tuple loops_kic.middle_offset = ( kic_end - kic_start )
string loops_kic.min_type = "linmin"
tuple loops_kic.mm = MoveMap()
tuple loops_kic.movemap = MoveMap()
tuple loops_kic.my_loop = Loop( loop_begin, loop_end, loop_cut )
tuple loops_kic.my_loops = Loops()
int loops_kic.outer_cycles = 10
tuple loops_kic.p = Pose()
tuple loops_kic.pack = protocols.minimization_packing.PackRotamersMover( scorefxn_high, task_pack )
tuple loops_kic.pymol = rosetta.PyMOLMover()
tuple loops_kic.recover_sidechains = protocols.simple_moves.ReturnSidechainMover( starting_p )
tuple loops_kic.rms = loop_rmsd( p, starting_p, my_loops )
tuple loops_kic.scorefxn_high = create_score_function( 'standard', 'score12' )
tuple loops_kic.scorefxn_low = create_score_function( 'cen_std' )
tuple loops_kic.starting_p = Pose()
tuple loops_kic.starting_p_centroid = Pose()
loops_kic.success = False
tuple loops_kic.task_pack = TaskFactory.create_packer_task( starting_p )
tuple loops_kic.to_centroid = protocols.simple_moves.SwitchResidueTypeSetMover( 'centroid' )
tuple loops_kic.to_fullatom = protocols.simple_moves.SwitchResidueTypeSetMover( 'fa_standard' )
float loops_kic.tol = 0.001