def _unaligned_image(self, state):
"""
Parameters
----------
state :
Returns
-------
"""
# get the box lengths from the vectors
box_lengths, box_angles = box_vectors_to_lengths_angles(
state['box_vectors'])
# recenter the protein-ligand complex into the center of the
# periodic boundary conditions
# regroup the ligand and protein in together
grouped_positions = group_pair(state['positions'], box_lengths,
self._bs_idxs, self._lig_idxs)
# then center them around the binding site
centered_positions = center_around(grouped_positions, self._bs_idxs)
# slice these positions to get the image
state_image = centered_positions[self._image_idxs]
return state_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 _unaligned_image(self, state):
"""The preprocessing method of states.
First it groups the binding site and ligand into the same
periodic box image and then centers the box around their
mutual center of mass and returns only the positions of the
binding site and ligand.
Parameters
----------
state : object implementing WalkerState
State with 'positions' (Nx3 dims) and 'box_vectors' (3x3
array) attributes.
Returns
-------
"""
# get the box lengths from the vectors
box_lengths, box_angles = box_vectors_to_lengths_angles(
state['box_vectors'])
# recenter the protein-ligand complex into the center of the
# periodic boundary conditions
# regroup the ligand and protein in together
grouped_positions = group_pair(state['positions'], box_lengths,
self._bs_idxs, self._lig_idxs)
# then center them around the binding site
centered_positions = center_around(grouped_positions, self._bs_idxs)
# slice these positions to get the image
state_image = centered_positions[self._image_idxs]
return state_image
def __init__(self, native_state=None,
cutoff_rmsd=0.2,
initial_states=None,
initial_weights=None,
ligand_idxs=None,
binding_site_idxs=None,
**kwargs):
"""Constructor for RebindingBC.
Arguments
---------
native_state : object implementing the State interface
The reference bound state. Will be automatically centered.
cutoff_rmsd : float
The cutoff RMSD for considering a walker bound.
initial_states : list of objects implementing the State interface
The list of possible states that warped walkers will assume.
initial_weights : list of float, optional
List of normalized probabilities of the initial_states
provided. If not given, uniform probabilities will be
used.
ligand_idxs : arraylike of int
The indices of the atom positions in the state considered
the ligand.
binding_site_idxs : arraylike of int
The indices of the atom positions in the state considered
the binding site.
Raises
------
AssertionError
If any of the following kwargs are not given:
native_state, initial_states, ligand_idxs, receptor_idxs.
"""
super().__init__(initial_states=initial_states,
initial_weights=initial_weights,
ligand_idxs=ligand_idxs,
receptor_idxs=binding_site_idxs
**kwargs)
# test inputs
assert native_state is not None, "Must give a native state"
assert type(cutoff_rmsd) is float
native_state_d = native_state.dict()
# save the native state and center it around it's binding site
native_state_d['positions'] = center_around(native_state['positions'], binding_site_idxs)
native_state = WalkerState(**native_state_d)
# save attributes
self._native_state = native_state
self._cutoff_rmsd = cutoff_rmsd