import sys
sys.path.append('/Users/npolizzi/Projects/combs/src/')
import combs
import prody as pr
import pickle
import numpy as np
import functools
from sklearn.neighbors import NearestNeighbors
import os
import copy
pdb_path = '/Users/npolizzi/Projects/combs/src/runs/apixaban/'
sample = combs.Sample()
poi_path = '/Users/npolizzi/Downloads/scPDB_2013/sc_gt80_le300_MWgt400_sitele35res_pdbs/reduce/'
sample.poi = pr.parsePDB(poi_path + '1c3eH.pdb')
roi_path = '/Users/npolizzi/Downloads/scPDB_2013/sc_gt80_le300_MWgt400_sitele35res_sites_pdbs/'
rois = pr.parsePDB(roi_path + '1c3e.pdb')
rois_resnums = rois.select('name CA').getResnums()
rois_chids = rois.select('name CA').getChids()
sample.bs_residues = list(zip(rois_resnums, rois_chids))
print(sample.bs_residues)
sample.set_rois()
sample.set_rois_phipsi()
sample.set_poi_clash_coords()
sample.set_roi_bb_coords()
sample.ligand_conformers = [pr.parsePDB(pdb_path + 'apix.pdb')]
relvdm_backbone = combs.Rel_Vandermer.RelVandermer('backbone')
relvdm_backbone.rel_vdm_path = '/Users/npolizzi/Projects/combs/results/backbone/rel_vdms_hbond_carbonyl/20171022/'
def main():
pdb_path = sys.argv[1]
sample = combs.Sample()
sample.poi = pr.parsePDB(pdb_path)
sample.bs_residues = list(zip([7, 10, 11, 14, 7, 10, 11, 14, 17, 7, 10, 11, 14, 7, 10, 11, 14, 17],
['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B',
'C', 'C', 'C', 'C', 'D', 'D', 'D', 'D', 'D']))
sample.set_rois()
sample.set_rois_phipsi()
sample.set_poi_clash_coords()
sample.set_roi_bb_coords()
relvdm_carboxamide = combs.Rel_Vandermer('carboxamide')
relvdm_carboxamide.rel_vdm_path = \
'/netapp/home/nick.polizzi/combs/results/carboxamide/rel_vdms/20170830/'
relvdm_carboxamide.load_rel_vdms_pickle(sample, subset={'ALA', 'GLY', 'SER', 'THR', 'TYR', 'TRP', 'ARG',
'ASN', 'GLN', 'HIS', 'PHE', 'LEU', 'VAL', 'ILE'})
relvdm_carboxamide.set_rel_vdm_bb_coords()
relvdm_carboxamide.set_rois_rot_trans(sample)
relvdm_carboxamide.set_rel_vdm_tags(sample)
print('moving carboxamide vdMs')
relvdm_carboxamide.move_rel_vdms(sample)
print('removing clashing carboxamide vdMs')
relvdm_carboxamide.remove_clash(sample)
relvdm_carboxamide.reshape_ifgs()
print('finding carboxamide hotspots')
relvdm_carboxamide.find_hotspots(rmsd_cutoff=0.7)
relvdm_carboxamide.rel_vdms_pickle = None
relvdm_carboxamide.rel_vdm_ifg_coords = None
relvdm_carboxamide.rel_vdm_bb_coords = None
relvdm_carboxamide.rel_vdm_sc_coords = None
relvdm_carboxamide.rel_vdm_tags = None
relvdm_carboxamide.rel_vdm_resnames = None
relvdm_carboxamide._ifgs = None
relvdm_carboxamide._resn = None
relvdm_carboxamide._type = None
relvdm_carboxamide._vdm_tags = None
relvdm_carboxamide._indices = None
relvdm_carboxamide.ifg_dict = {'GLN': 'CG CD OE1 NE2'}
relvdm_preproline_carbonyl1 = combs.Rel_Vandermer('preproline_carbonyl1')
relvdm_preproline_carbonyl1.rel_vdm_path = \
'/netapp/home/nick.polizzi/combs/results/preproline_carbonyl/rel_vdms/20170927/'
relvdm_preproline_carbonyl1.load_rel_vdms_pickle(sample, subset={'ALA', 'GLY', 'SER', 'THR', 'TYR', 'TRP', 'ARG',
'ASN', 'GLN', 'HIS', 'PHE', 'LEU', 'VAL', 'ILE'})
relvdm_preproline_carbonyl1.set_rel_vdm_bb_coords()
relvdm_preproline_carbonyl1.set_rois_rot_trans(sample)
relvdm_preproline_carbonyl1.set_rel_vdm_tags(sample)
print('moving vdMs')
relvdm_preproline_carbonyl1.move_rel_vdms(sample)
print('removing clashing vdMs')
relvdm_preproline_carbonyl1.remove_clash(sample)
relvdm_preproline_carbonyl1.reshape_ifgs()
print('finding hotspots')
relvdm_preproline_carbonyl1.find_hotspots(rmsd_cutoff=0.7)
relvdm_preproline_carbonyl1.rel_vdms_pickle = None
relvdm_preproline_carbonyl1.rel_vdm_ifg_coords = None
relvdm_preproline_carbonyl1.rel_vdm_bb_coords = None
relvdm_preproline_carbonyl1.rel_vdm_sc_coords = None
relvdm_preproline_carbonyl1.rel_vdm_tags = None
relvdm_preproline_carbonyl1.rel_vdm_resnames = None
relvdm_preproline_carbonyl1._ifgs = None
relvdm_preproline_carbonyl1._resn = None
relvdm_preproline_carbonyl1._type = None
relvdm_preproline_carbonyl1._vdm_tags = None
relvdm_preproline_carbonyl1._indices = None
relvdm_preproline_carbonyl1.ifg_dict = {'ANY': 'C O CA N'}
# with open(outdir + 'relvdm_preproline_carbonyl_subset.pickle', 'wb') as outfile:
# pickle.dump(relvdm_preproline_carbonyl1, outfile)
relvdm_preproline_carbonyl2 = deepcopy(relvdm_preproline_carbonyl1)
relvdm_preproline_carbonyl2.name = 'preproline_carbonyl2'
relvdm_carboxamide.hotspot_subgraphs = list(
sorted((comp for comp in nx.connected_component_subgraphs(relvdm_carboxamide.hotspot_graph) if len(comp) > 10),
key=len, reverse=True))
relvdm_preproline_carbonyl1.hotspot_subgraphs = list(
sorted((comp for comp in nx.connected_component_subgraphs(relvdm_preproline_carbonyl1.hotspot_graph) if len(comp) > 10),
key=len, reverse=True))
relvdm_preproline_carbonyl2.hotspot_subgraphs = list(
sorted((comp for comp in nx.connected_component_subgraphs(relvdm_preproline_carbonyl2.hotspot_graph) if len(comp) > 10),
key=len, reverse=True))
outdir = '/netapp/home/nick.polizzi/combs/results/apixaban/20170927/subset_TSAGYWNQHFLVIR/output/' \
+ pdb_path.split('/')[-1].split('.')[0] + '/'
try:
os.makedirs(outdir)
except:
pass
confs_indir = '/netapp/home/nick.polizzi/combs/src/runs/apixaban/apix.pdb'
sample.ligand_conformers = [pr.parsePDB(confs_indir)]
sample.set_lig_ifg_dict(relvdm_carboxamide, 'C10 C11 O1 N3')
sample.set_lig_ifg_dict(relvdm_preproline_carbonyl1, 'C8 O3 C13 N5')
sample.set_lig_ifg_dict(relvdm_preproline_carbonyl2, 'C19 O2 C23 N2')
sample.set_ligand_ifg_coords(relvdm_carboxamide)
sample.set_ligand_ifg_coords(relvdm_preproline_carbonyl1)
sample.set_ligand_ifg_coords(relvdm_preproline_carbonyl2)
sample.set_rel_vdms([relvdm_carboxamide, relvdm_preproline_carbonyl1, relvdm_preproline_carbonyl2])
def rev(name_pairs):
return [((tup[0][1], tup[0][0]), tup[1]) for tup in name_pairs]
sample.name_pairs[('carboxamide', 'preproline_carbonyl1')] = \
[(('O1', 'N5'), 0.25), (('O1', 'C13'), 0.3), (('O1', 'O3'), 0.25),
(('N3', 'N5'), 0.25), (('N3', 'C13'), 0.3), (('N3', 'O3'), 0.25),
(('C10', 'N5'), 0.3), (('C10', 'C13'), 0.3), (('C10', 'O3'), 0.3)]
sample.name_pairs[('preproline_carbonyl1', 'carboxamide')] = \
rev(sample.name_pairs[('carboxamide', 'preproline_carbonyl1')])
sample.name_pairs[('carboxamide', 'preproline_carbonyl2')] = \
[(('O1', 'N2'), 0.25), (('O1', 'C23'), 0.3), (('O1', 'O2'), 0.25),
(('N3', 'N2'), 0.25), (('N3', 'C23'), 0.3), (('N3', 'O2'), 0.25),
(('C10', 'N2'), 0.3), (('C10', 'C23'), 0.3), (('C10', 'O2'), 0.3)]
sample.name_pairs[('preproline_carbonyl2', 'carboxamide')] = \
rev(sample.name_pairs[('carboxamide', 'preproline_carbonyl2')])
sample.name_pairs[('preproline_carbonyl1', 'preproline_carbonyl2')] = \
[(('N5', 'N2'), 0.25), (('N5', 'C23'), 0.25), (('N5', 'O2'), 0.3),
(('C13', 'N2'), 0.25), (('C13', 'C23'), 0.25), (('C13', 'O2'), 0.3),
(('O3', 'N2'), 0.3), (('O3', 'C23'), 0.3), (('O3', 'O2'), 0.3)]
sample.name_pairs[('preproline_carbonyl2', 'preproline_carbonyl1')] = \
rev(sample.name_pairs[('preproline_carbonyl1', 'preproline_carbonyl2')])
print('finding lig cst hotspots')
sample.find_ligand_cst_hotspots()
sample.set_protein_bb_coords(clash_cutoff=2.5)
sample.make_densities()
sample.set_lig_coords()
print('fitting lig confs to density')
sample.fit_lig_to_density()
if sample.poses:
sample.pose_metrics(rmsd_cutoff=1.7)
pscores = []
ifgs = []
num_sites = []
poses = []
for ind in sample.ranked_poses_by_score:
pscore = sample.pose_scores[ind]
ifg = sample.pose_num_satisfied_iFGs[ind]
num_site = sample.pose_num_residues[ind]
pose = ind
if pscore > 1:
pscores.append(pscore)
ifgs.append(ifg)
num_sites.append(num_site)
poses.append(pose)
keys = set(sample.rel_vdms.keys()) - {'preproline_carbonyl'}
for relvdm_key in keys:
if relvdm_key[:3] == 'pre':
sample.rel_vdms['preproline_carbonyl'] = sample.rel_vdms[relvdm_key]
sample.rel_vdms['preproline_carbonyl'].name = 'preproline_carbonyl'
sample.rel_vdms['preproline_carbonyl'].rel_vdm_path = \
'/netapp/home/nick.polizzi/combs/results/preproline_carbonyl/rel_vdms/20170830/'
outdir_pdb = outdir + 'pose' + str(ind) + '/' + relvdm_key + '/'
try:
os.makedirs(outdir_pdb)
except:
pass
sample.poses[ind].subgraphs['preproline_carbonyl'] = sample.poses[ind].subgraphs[relvdm_key]
sample.poses[ind].print_graph_pdbs(sample, 'preproline_carbonyl', outdir_pdb)
pr.writePDB(outdir + 'pose' + str(ind) + '/' + 'ligand.pdb', sample.poses[ind].ligand)
else:
outdir_pdb = outdir + 'pose' + str(ind) + '/' + relvdm_key + '/'
try:
os.makedirs(outdir_pdb)
except:
pass
sample.poses[ind].print_graph_pdbs(sample, relvdm_key, outdir_pdb)
pr.writePDB(outdir + 'pose' + str(ind) + '/' + 'ligand.pdb', sample.poses[ind].ligand)
if pscores:
with open(outdir + pdb_path.split('/')[-1].split('.')[0] + '_pose_scores.txt', 'w') as outfile:
outfile.write(sys.argv[1].split('/')[-1] + ', ' + ' '.join(str(s) for s in pscores) + '\n')
outfile.write('number satisfied iFGs, ' + ' '.join(str(s) for s in ifgs) + '\n')
outfile.write('number residue sites in pose, ' + ' '.join(str(s) for s in num_sites) + '\n')
outfile.write('pose, ' + ' '.join(str(s) for s in poses) + '\n')
if sample.pose_scores[sample.ranked_poses_by_score[0]] > 1000:
sample.poi = None
sample.rois = None
with gzip.open(outdir + 'sample_TSAGYWNQHFLVI_' + pdb_path.split('/')[-1].split('.')[0] + '.pickle.gz', 'wb') as outfile:
pickle.dump(sample, outfile)
