def superimpose_proteins(structure_dict):
names = tuple(key for key in structure_dict.keys())
ref_name = names[0]
# Move reference structure to the origin
centered_centroid = centroid.centroid(
structure_dict[ref_name].get_carbons())
centered_ref_coords = [
atomic_coords - centered_centroid
for atomic_coords in structure_dict[ref_name].get_carbons()
]
structure_dict[ref_name].set_carbons(centered_ref_coords)
for i in range(1, len(names)):
moving_carbons = structure_dict[names[i]].get_carbons()
# Superimpose the structure onto the reference structure and keep only the updated coordinates
# (do not need rotation matrix or RMSD)
centered_structure = superimpose.superimpose(
np.asarray(centered_ref_coords), np.asarray(moving_carbons))[0]
structure_dict[names[i]].set_carbons(centered_structure.tolist())
# TODO update coordinates of all atoms after superimposing (not just carbon alpha and carbon beta atoms)
'''
def image(self, state):
"""Transform a state to a receptor image.
A receptor image is one in which the binding site and ligand
are first normalized to be within the same periodic box image
and at the center of the box, and then only the binding site
and ligand are retained.
Parameters
----------
state : object implementing WalkerState
State with 'positions' (Nx3 dims) and 'box_vectors' (3x3 array)
attributes.
Returns
-------
receptor_image : array of float
The positions of binding site and ligand after
preprocessing.
"""
# get the unaligned image
state_image = self._unaligned_image(state)
# then superimpose it to the reference structure
sup_image, _, _ = superimpose(self.ref_image,
state_image,
idxs=self._image_bs_idxs)
return sup_image
def image(self, state):
# get the unaligned image
state_image = self._unaligned_image(state)
# then superimpose it to the reference structure
sup_image = superimpose(self.ref_image,
state_image,
idxs=self._image_bs_idxs)
return sup_image
def _progress(self, walker):
"""Calculate if the walker has bound and provide progress record.
Parameters
----------
walker : object implementing the Walker interface
Returns
-------
is_bound : bool
Whether the walker is unbound (warped) or not
progress_data : dict of str : value
Dictionary of the progress record group fields
for this walker alone.
"""
# first recenter the ligand and the receptor in the walker
box_lengths, box_angles = box_vectors_to_lengths_angles(
walker.state['box_vectors'])
grouped_walker_pos = group_pair(walker.state['positions'], box_lengths,
self.binding_site_idxs,
self.ligand_idxs)
# center the positions around the center of the binding site
centered_walker_pos = center_around(grouped_walker_pos,
self.binding_site_idxs)
# superimpose the walker state positions over the native state
# matching the binding site indices only
sup_walker_pos, _, _ = superimpose(self.native_state['positions'],
centered_walker_pos,
idxs=self.binding_site_idxs)
# calculate the rmsd of the walker ligand (superimposed
# according to the binding sites) to the native state ligand
native_rmsd = calc_rmsd(self.native_state['positions'],
sup_walker_pos,
idxs=self.ligand_idxs)
# test to see if the ligand is re-bound
rebound = False
if native_rmsd <= self.cutoff_rmsd:
rebound = True
progress_data = {'native_rmsd': native_rmsd}
return rebound, progress_data
def image(self, state):
"""
Parameters
----------
state :
Returns
-------
"""
# get the unaligned image
state_image = self._unaligned_image(state)
# then superimpose it to the reference structure
sup_image, _, _ = superimpose(self.ref_image,
state_image,
idxs=self._image_bs_idxs)
return sup_image