def get_rmsd_native(self, walkers):
num_walkers = len(walkers)
small_lig_idxs = np.array(range(len(self.ligand_idxs)))
small_bs_idxs = np.array(
range(len(self.ligand_idxs),
len(self.ligand_idxs) + len(self.binding_site_idxs)))
keep_atoms = np.concatenate((self.ligand_idxs, self.binding_site_idxs),
axis=0)
small_pos = self._xyz_from_walkers(walkers, keep_atoms)
box_lengths = self._box_from_walkers(walkers)
newpos_small = np.zeros_like(small_pos)
for frame_idx, positions in enumerate(small_pos):
newpos_small[frame_idx, :, :] = recenter_pair(
positions, box_lengths[frame_idx], small_lig_idxs,
small_bs_idxs)
small_top = self.topology.subset(keep_atoms)
traj_rec = mdj.Trajectory(newpos_small, small_top)
traj_rec.superpose(self.comp_traj, atom_indices=small_bs_idxs)
rmsd_native = np.zeros((num_walkers))
for i in range(num_walkers):
rmsd_native[i] = calc_rmsd(traj_rec.xyz[i], self.comp_traj.xyz[0],
small_lig_idxs)
if self.alt_maps is not None:
# figure out the "small" alternative maps
small_alt_maps = deepcopy(self.alt_maps)
for i, a in enumerate(self.alt_maps):
for j, e in enumerate(a):
try:
small_alt_maps[i][j] = list(self.binding_site_idxs).index(e) +\
len(self.ligand_idxs)
except:
raise Exception(
'Alternative maps are assumed to be permutations of'
' existing binding site indices')
for alt_map in small_alt_maps:
alt_traj_rec = mdj.Trajectory(newpos_small, small_top)
alt_traj_rec.superpose(self.comp_traj,
atom_indices=small_bs_idxs,
ref_atom_indices=alt_map)
for i in range(num_walkers):
dist = calc_rmsd(alt_traj_rec.xyz[i],
self.comp_traj.xyz[0], small_lig_idxs)
if dist < rmsd_native[i]:
rmsd_native[i] = dist
return rmsd_native
def _unaligned_image(self, state):
# 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
rece_positions = recenter_pair(state['positions'], box_lengths,
self._bs_idxs, self._lig_idxs)
# slice these positions to get the image
state_image = rece_positions[self._image_idxs]
return state_image
def distance(self, walkers):
n_walkers = len(walkers)
keep_atoms = np.concatenate((self.ligand_idxs, self.protein_idxs),
axis=0)
small_lig_idxs = np.array(range(len(self.ligand_idxs)))
small_prot_idxs = np.array(
range(len(self.ligand_idxs),
len(self.ligand_idxs) + len(self.protein_idxs)))
# recenter protein and ligand
small_pos = self._xyz_from_walkers(walkers, keep_atoms)
box_lengths = self._box_from_walkers(walkers)
newpos_small = np.zeros_like(small_pos)
for frame_idx, positions in enumerate(small_pos):
newpos_small[frame_idx, :, :] = recenter_pair(
positions, box_lengths[frame_idx], small_lig_idxs,
small_bs_idxs)
# profile ligand-protein interactions for each walker (in parallel)
profiles = [[] for i in range(n_walkers)]
for i in range(n_walkers):
# pass coordinates in angstroms
coords = [
10 * newpos_small[i][small_lig_idxs],
10 * newpos_small[i][small_prot_idxs]
]
system = self.sys_type.to_system(coords)
profiles[i] = self.profiler.profile(system)
# vectorize profiles (in serial)
inte_vec, names = self.vectorize_profiles(profiles, n_walkers)
# calculate distance matrix in interaction space
dist_mat = np.zeros((n_walkers, n_walkers))
for i in range(n_walkers):
for j in range(i + 1, n_walkers):
dist = np.linalg.norm(inte_vec[i] - inte_vec[j], ord=2)
dist_mat[i][j] = dist
dist_mat[j][i] = dist
return dist
"clipped_{}_{}_{}_tryp_ben.pdb".format(*unit_corner))
# first group the protein and ligand together, this may be outside of
# the PBCs
grouped_coords = group_pair(uncentered_system.xyz[0], box_lengths, prot_idxs,
lig_idxs)
# write this out to check it
grouped_system = mdj.Trajectory(
grouped_coords,
top,
unitcell_lengths=uncentered_system.unitcell_lengths,
unitcell_angles=uncentered_system.unitcell_angles)
# grouped_system.save_pdb("grouped_tryp_ben.pdb")
# finally we can combine these functions into something that recenters
# our box around a pair of groups (molecules for instance)
recentered_coords = recenter_pair(uncentered_system.xyz[0], box_lengths,
prot_idxs, lig_idxs)
# write them out so we can visualize
recentered_system = mdj.Trajectory(
recentered_coords,
top,
unitcell_lengths=uncentered_system.unitcell_lengths,
unitcell_angles=uncentered_system.unitcell_angles)
recentered_system.save_pdb("recentered_tryp_ben.pdb")