model.symmetry.define() -- define similar segments

symmetry_weight = <float:1>	1.0	the weight of the symmetry objective function term
add_symmetry = <bool:2>	False True	whether to add segment pair, add atoms to segment pair

Description:

This command allows defining pairs of segments that will be restrained to be the same during optimization of the objective function. This is achieved by adding the sum of squares of the differences between the equivalent distances (similar to distance RMS deviation) to the objective function being optimized, separately for each pair of segments defined by model.symmetry.define(). The value of this term is reported in the log file by the model.energy() command, which also reports the individual contributions to the term when output contains word 'SYMMETRY'. In each call of the model.symmetry.define() command, the list of such segments is either initiated, extended by a new pair of segments, or the last defined pair of segments is extended by adding new atoms.

symmetry_weight specifies the atomic weights to be used in the calculation of the symmetry term (Eq. 6.72).

The two segments correspond to the selected sets 2 and 3 (obtained by the model.restraints.pick() command). They must have the same number of atoms.

A pair of segments can be either added to the list (add_symmetry[0] = True) or the list can be initialized (add_symmetry[0] = False).

If add_symmetry[1] = True, the currently selected atoms are added to the last segment pair in the segment pairs list, otherwise a new segment pair is started.

Example: examples/commands/define_symmetry.py

# Example for: model.symmetry.define()

# This will force two copies of 1fas to have similar mainchain 
# conformation.

log.level(1, 1, 1, 1, 0)
env = environ()
env.libs.topology.read(file='$(LIB)/top_heav.lib')
env.libs.parameters.read(file='$(LIB)/par.lib')

def defsym(mdl, aln, seg1, seg2):
    for (set, seg) in [(2, seg1), (3, seg2)]:
        mdl.pick_atoms(aln, pick_atoms_set=set, selection_segment=seg,
                       atom_types='MNCH', selection_status='INITIALIZE',
                       selection_search='SEGMENT')
    mdl.symmetry.define(symmetry_weight=1.0, add_symmetry=(True, False))

# Generate two copies of a segment:
code = '2abx'
mdl = model(env, file=code, model_segment=('1:A', '74:B'))
aln = alignment(env)
aln.append_model(mdl, align_codes=code, atom_files=code)
aln.append_model(mdl, align_codes=code+'_ini', atom_files=code+'_ini')
mdl.generate_topology(aln, sequence=code+'_ini')
mdl.transfer_xyz(aln)
mdl.build(initialize_xyz=False, build_method='INTERNAL_COORDINATES')
mdl.rename_segments(segment_ids=('A', 'B'), renumber_residues=(1, 1))

myedat = energy_data(dynamic_sphere = False)
mdl.energy(edat=myedat)
mdl.randomize_xyz(deviation=6.0)
# Define the two segments (chains in this case) to be identical:
defsym(mdl, aln, seg1=('1:A', '74:A'), seg2=('1:B', '74:B'))

# Make them identical by optimizing the initial randomized structure
# without any other restraints:
mdl.energy(edat=myedat)
mdl.write(file='define_symmetry-1.atm')
mdl.optimize(max_iterations=300, edat=myedat)
mdl.write(file='define_symmetry-2.atm')
mdl.energy(edat=myedat)

# Now optimize with stereochemical restraints so that the
# result is not so distorted a structure (still distorted
# because optimization is not thorough):
myedat.dynamic_sphere = True
mdl.restraints.make(aln, restraint_type='stereo', spline_on_site=False,
                    edat=myedat)
mdl.randomize_xyz(deviation=3.0)
for method in (1, 3, 1):   # 1 = conjugate gradients, 3 = molecular dynamics
    mdl.optimize(max_iterations=300, md_return='FINAL', edat=myedat,
                 optimization_method=method, output='REPORT')
mdl.write(file='define_symmetry-3.atm')
mdl.energy(edat=myedat)

# Create a blank alignment so that superpose uses its 1:1 default
aln = alignment(env)

mdl = model(env, file='define_symmetry-3.atm', model_segment=('1:A', '74:A'))
mdl2 = model(env, file='define_symmetry-3.atm', model_segment=('1:B', '74:B'))
mdl.pick_atoms(aln, atom_types='MNCH')
mdl.superpose(mdl2, aln)