def check_ringed_lipids(protein):
print('Checking for ringed lipids')
if not os.path.exists(g_var.merged_directory +
'checked_ringed_lipid_de_novo.pdb'):
if not os.path.exists(g_var.merged_directory +
'merged_cg2at_threaded.pdb'):
box_vec = g_var.box_vec.split()[1:4]
r_b_vec, r_b_inv = read_in.real_box_vectors(g_var.box_vec)
os.chdir(g_var.merged_directory)
merge, merge_coords = read_in_merged_pdbs([], [], protein)
resid_prev = 0
ringed = False
lipid_atoms = []
with open(g_var.merged_directory + 'threaded_lipids.dat',
'w') as ring_ouput:
for at_val, atom in enumerate(merge):
resname = get_np_resname(at_val)
if resname != None:
if atom['residue_id'] != resid_prev:
if 'offset' in locals() and len(
g_var.heavy_bond[resname]) > 0:
if at_val - offset > int(
len(g_var.np_blocks[resname_prev]) /
g_var.system[resname_prev]):
offset = at_val
else:
offset = at_val
resid_prev = atom['residue_id']
resname_prev = resname
if atom['atom_number'] - offset in g_var.heavy_bond[
resname]:
for at_bond in g_var.heavy_bond[resname][
atom['atom_number'] - offset]:
at_bond -= 1
if merge[at_bond +
offset]['atom_number'] > merge[
at_val]['atom_number']:
merge[at_bond + offset]['x'], merge[
at_bond + offset]['y'], merge[
at_bond + offset]['z'] = np.array(
read_in.brute_mic(
merge_coords[at_val],
merge_coords[at_bond +
offset],
r_b_vec))
merge_coords[at_bond + offset] = merge[
at_bond + offset]['x'], merge[
at_bond +
offset]['y'], merge[at_bond +
offset]['z']
dist = gen.calculate_distance(
merge_coords[at_val],
merge_coords[at_bond + offset])
if 2 < dist < 6:
lipid_atoms.append([
at_val, at_bond + offset,
(np.array(merge_coords[at_val]) +
np.array(merge_coords[at_bond +
offset])) /
2
])
ring_ouput.write(
'{0:6}{1:6}{2:2}{3:4}{4:2}{5:7}{6:5}{7:5}{8:5}{9:5}{10:5}{11:5}\n'
.format(
'distance: ',
str(np.round(dist,
2)), 'residue: ',
merge[at_val]['residue_name'],
merge[at_val]['residue_id'],
' atom_1: ',
merge[at_val]['atom_name'],
'atom_2: ',
merge[at_bond +
offset]['atom_name'],
'rough line num: ', at_val,
at_bond + offset))
ringed = True
if ringed or os.path.exists(g_var.merged_directory +
'merged_cg2at_threaded.pdb'):
print('Found ' + str(len(lipid_atoms)) +
' abnormal bonds, now attempting to fix.')
print('See this file for a complete list: ' +
g_var.merged_directory + 'threaded_lipids.dat')
fix_threaded_lipids(lipid_atoms, merge, merge_coords)
else:
gen.file_copy_and_check(
g_var.merged_directory +
'MIN/merged_cg2at_de_novo_minimised.pdb',
g_var.merged_directory + 'checked_ringed_lipid_de_novo.pdb')
#### collects initial structures into INPUT folder
gro.collect_input()
#### saves flags used into INPUT folder
gen.flags_used()
g_var.tc['i_t_e'] = time.time()
#### reads in CG file and separates into residue types
box_vec_initial = read_in.read_initial_cg_pdb()
#### box size update
if g_var.args.box != None:
print('box cutting only works for cubic boxes currently')
g_var.box_vec, box_shift = gen.new_box_vec(box_vec_initial,
g_var.args.box)
else:
g_var.box_vec = box_vec_initial
box_shift = np.array([0, 0, 0])
read_in.real_box_vectors(g_var.box_vec)
#### pbc fix and residue truncation if required
read_in.fix_pbc(box_vec_initial, g_var.box_vec, box_shift)
#### checks if fragment database and input files match
at_mod.sanity_check()
### convert protein to atomistic representation
g_var.tc['r_i_t'] = time.time()
if 'PROTEIN' in g_var.cg_residues:
g_var.coord_atomistic = at_mod_p.build_multi_residue_atomistic_system(
g_var.cg_residues, 'PROTEIN') ## converts protein to atomistic
if not g_var.user_at_input and g_var.args.v >= 1: ## prints protein sequences
print(gen.print_sequnce_info('PROTEIN'))
## reads in user chain, runs a sequence alignment and finds existing disulphide bonds
g_var.tc['p_d_n_t'] = time.time()
if g_var.user_at_input:
for file_num, file_name in enumerate(g_var.args.a):
def fix_chirality(merge, merge_temp, merged_coords, residue_type):
#### fixes chiral groups
r_b_vec, r_b_inv = read_in.real_box_vectors(g_var.box_vec)
chiral_atoms, coord = fetch_chiral_coord(merge_temp, residue_type)
for residue in chiral_atoms:
if residue_type in ['PROTEIN', 'OTHER']:
for atom in chiral_atoms[residue]:
resname = merge_temp[chiral_atoms[residue]
[atom]]['residue_name']
break
else:
resname = residue_type
for chiral_group in g_var.res_top[resname]['CHIRAL']:
if chiral_group != 'atoms':
stat = merge_temp[chiral_atoms[residue][chiral_group]].copy()
atom_move = {
'stat': np.array([stat['x'], stat['y'], stat['z']]),
'm': '',
'c1': '',
'c2': '',
'c3': ''
}
for chir_atom in atom_move:
if chir_atom != 'stat':
test = merge_temp[chiral_atoms[residue]
[g_var.res_top[resname]['CHIRAL']
[chiral_group][chir_atom]]].copy()
atom_move[chir_atom] = np.array(
[test['x'], test['y'], test['z']])
if gen.calculate_distance(atom_move['stat'],
atom_move[chir_atom]) > 10:
atom_move[chir_atom] = np.array(
read_in.brute_mic(atom_move['stat'],
atom_move[chir_atom],
r_b_vec))
S_M = atom_move['m'] - atom_move['stat']
rotation = align_to_vector(S_M, [0, 0, 1])
c1_coord = (atom_move['c1'] - atom_move['stat']).dot(rotation)
c2_coord = (atom_move['c2'] - atom_move['stat']).dot(rotation)
c3_coord = (atom_move['c3'] - atom_move['stat']).dot(rotation)
if gen.angle_clockwise(c1_coord[0:2],
c2_coord[0:2]) > gen.angle_clockwise(
c1_coord[0:2], c3_coord[0:2]):
for ax_val, axis in enumerate(['x', 'y', 'z']):
merge_temp[chiral_atoms[residue][
g_var.res_top[resname]['CHIRAL'][chiral_group]
['m']]][axis] = merge_temp[chiral_atoms[residue][
g_var.res_top[resname]['CHIRAL'][chiral_group]
['m']]][axis] - (3 * S_M[ax_val])
merge_temp[chiral_atoms[residue]
[chiral_group]][axis] = merge_temp[
chiral_atoms[residue]
[chiral_group]][axis] - (S_M[ax_val])
coord[chiral_atoms[residue]
[g_var.res_top[resname]['CHIRAL'][chiral_group]
['m']]] -= (2 * S_M) #move_coord -
coord[chiral_atoms[residue][chiral_group]] -= (
0.25 * S_M) #stat_coord -
merge += merge_temp
merged_coords += coord
return merge, merged_coords