def main():
d_cath = parse_CATH()
## dictionary of apo and holo structures (from what script???)
d_apo2holo = {
'1ak1': {'holo': '1c1h', 'rmsd': 0.64, 'ligand': 'MMP', 'overlap': 0.36},
'1lp8': {'holo': '1lpc', 'rmsd': 0.14003320157149318, 'ligand': 'CMP', 'overlap': 0.1663339954531419}, '2exo': {'holo': '1j01', 'rmsd': 0.31317202378931264, 'ligand': 'XIL', 'overlap': 0.5464584014950491}, '1syc': {'holo': '1syd', 'rmsd': 0.42370903255794784, 'ligand': 'THP', 'overlap': 0.312528957121447}, '1cua': {'holo': '3esd', 'rmsd': 0.4040397349113579, 'ligand': 'SXC', 'overlap': 0.08139930257927935}, '1znw': {'holo': '1znx', 'rmsd': 0.24704558797447082, 'ligand': '5GP', 'overlap': 0.12436531581580901}, '1gbs': {'holo': '1lsp', 'rmsd': 0.264857015278693, 'ligand': 'BUL', 'overlap': 0.2934470556757598}, '1sqg': {'holo': '1sqf', 'rmsd': 0.6990763011194481, 'ligand': 'SAM', 'overlap': 0.4723483760294988}, '3npo': {'holo': '3nq3', 'rmsd': 0.7183351557421368, 'ligand': 'DKA', 'overlap': 0.04712778545695382}, '2e3m': {'holo': '2e3q', 'rmsd': 0.8849429260246913, 'ligand': '18C', 'overlap': 0.09031491180306017}, '3k0n': {'holo': '1w8m', 'rmsd': 0.39833839324838677, 'ligand': 'E1P', 'overlap': 0.06688885295094558}, '3aap': {'holo': '3aar', 'rmsd': 0.3572808619937969, 'ligand': 'ANP', 'overlap': 0.35015656527393507}, '1bk7': {'holo': '1ucd', 'rmsd': 0.5608983876422892, 'ligand': 'U5P', 'overlap': 0.6239173853318093}, '1tgn': {'holo': '1tni', 'rmsd': 1.937557415391448, 'ligand': 'PBN', 'overlap': 0.17747463719381318}, '1ahc': {'holo': '1ahb', 'rmsd': 0.19271320420696525, 'ligand': 'FMP', 'overlap': 0.2906115852531481}, '3mft': {'holo': '3mfu', 'rmsd': 0.5294319317376655, 'ligand': 'ANP', 'overlap': 0.5901312084425671}, '1erk': {'holo': '4erk', 'rmsd': 1.8403643776383745, 'ligand': 'OLO', 'overlap': 0.2606792215029042}, '1sll': {'holo': '4sli', 'rmsd': 0.27110444955664886, 'ligand': 'CNP', 'overlap': 0.09295343747516871}, '1rtc': {'holo': '1br6', 'rmsd': 0.7736294829905356, 'ligand': 'PT1', 'overlap': 0.02244838892564617}, '1gy0': {'holo': '1og1', 'rmsd': 0.26938443289620695, 'ligand': 'TAD', 'overlap': 0.11337131846497911}, '2hbj': {'holo': '2hbl', 'rmsd': 0.2791711771177489, 'ligand': 'AMP', 'overlap': 0.2654241484172416}, '1rd6': {'holo': '1x6n', 'rmsd': 0.29783872255245375, 'ligand': 'AO3', 'overlap': 0.020924868377188755}, '1mzl': {'holo': '1mzm', 'rmsd': 0.4977604676331388, 'ligand': 'PLM', 'overlap': 0.15358351922009683}, '1hka': {'holo': '1eqm', 'rmsd': 3.101848541109514, 'ligand': '', 'overlap': 0.29938268367048587}, '2ppn': {'holo': '1fkh', 'rmsd': 0.5498751329287473, 'ligand': 'SBX', 'overlap': 0.008728602838910722}, '2vfy': {'holo': '2vfk', 'rmsd': 0.5234309202023915, 'ligand': 'AMP', 'overlap': 0.4186721907995304}, '1yhv': {'holo': '2hy8', 'rmsd': 0.7580522933908197, 'ligand': '1ST', 'overlap': 0.6167885584722257}, '1eur': {'holo': '1eus', 'rmsd': 0.3471466880748409, 'ligand': 'DAN', 'overlap': 0.656212298345592}, '3a0x': {'holo': '3a0t', 'rmsd': 1.4778758006848136, 'ligand': '', 'overlap': 0.08855830101729956}, '1mri': {'holo': '1mrh', 'rmsd': 0.20580455271425652, 'ligand': 'FMC', 'overlap': 0.2616567944535416}, '2zj8': {'holo': '2zja', 'rmsd': 0.39958904846327736, 'ligand': 'ACP', 'overlap': 0.15477640189079234}, '2ggo': {'holo': '2ggq', 'rmsd': 0.41217362536688407, 'ligand': 'TTP', 'overlap': 0.21415433688009522}, '1bbc': {'holo': '1db4', 'rmsd': 1.3942309487855171, 'ligand': '8IN', 'overlap': 0.12052760594053587}, '3c0e': {'holo': '3c11', 'rmsd': 0.40358994049970154, 'ligand': 'GMY', 'overlap': 0.18401963629557413}, '1tje': {'holo': '1tkg', 'rmsd': 0.5953813587886109, 'ligand': 'SSA', 'overlap': 0.3496015526554969}, '1wvw': {'holo': '1wvy', 'rmsd': 0.9674023140460931, 'ligand': 'STU', 'overlap': 0.13588790082354602}, '1ifb': {'holo': '2ifb', 'rmsd': 0.36597921461938127, 'ligand': 'PLM', 'overlap': 0.2728603476085213}, '1qtr': {'holo': '1x2e', 'rmsd': 0.4771243544672125, 'ligand': 'ATX', 'overlap': 0.003613865518161083}, '1pdb': {'holo': '3nxv', 'rmsd': 0.7597621325331363, 'ligand': 'D2F', 'overlap': 0.07405896998672913}, '2qev': {'holo': '2qeh', 'rmsd': 0.26344417969606054, 'ligand': 'SRO', 'overlap': 0.14227481558897756}, '3g6l': {'holo': '3g6m', 'rmsd': 0.1606666839962277, 'ligand': 'CFF', 'overlap': 0.2849120042129244}, '1arl': {'holo': '2rfh', 'rmsd': 0.349832513662932, 'ligand': '23N', 'overlap': 0.314294597059561}, '2vfb': {'holo': '3ltw', 'rmsd': 0.2811833881753945, 'ligand': 'HLZ', 'overlap': 0.03642491522930895}, '1akz': {'holo': '3fck', 'rmsd': 0.5257761484670386, 'ligand': 'FCK', 'overlap': 0.43841384942941936}, '2paw': {'holo': '1a26', 'rmsd': 0.3302247982261714, 'ligand': 'CNA', 'overlap': 0.07651713423342446}, '1kqx': {'holo': '1kqw', 'rmsd': 0.6648748206255346, 'ligand': 'RTL', 'overlap': 0.2243499171280635}, '3pte': {'holo': '1yqs', 'rmsd': 0.19520439729404254, 'ligand': 'BSA', 'overlap': 0.23347037537804616}, '1iad': {'holo': '1qji', 'rmsd': 0.33860211897807524, 'ligand': 'PKF', 'overlap': 0.19714803737138323}, '3blm': {'holo': '1blh', 'rmsd': 0.21196668540983332, 'ligand': 'FOS', 'overlap': 0.35086757294487353}, '2d59': {'holo': '2d5a', 'rmsd': 1.191748760948045, 'ligand': '', 'overlap': 0.19626132868398616}, '1lmn': {'holo': '1bb7', 'rmsd': 0.12717943435514337, 'ligand': 'GUM', 'overlap': 0.1248915962046876}, '1kf5': {'holo': '1eow', 'rmsd': 0.18795641863024692, 'ligand': 'U2G', 'overlap': 0.24946252748542863}, '2sil': {'holo': '2sim', 'rmsd': 0.1425616125054784, 'ligand': 'DAN', 'overlap': 0.021600224935827056}, '2zco': {'holo': '2zcs', 'rmsd': 0.2685379543685112, 'ligand': 'B70', 'overlap': 0.6230371569077154}, '2ac4': {'holo': '2q2o', 'rmsd': 0.4309651624839198, 'ligand': 'H01', 'overlap': 0.02673223321151024}, '1ojq': {'holo': '1ojz', 'rmsd': 0.8206121849480196, 'ligand': '', 'overlap': 0.496036330611861}, '1ey0': {'holo': '1stg', 'rmsd': 0.701380747069386, 'ligand': 'THP', 'overlap': 0.16741304780628186}, '1yes': {'holo': '1byq', 'rmsd': 0.8384813140092745, 'ligand': '', 'overlap': 0.23598536851862675}, '1sye': {'holo': '1syf', 'rmsd': 0.699830584716955, 'ligand': 'THP', 'overlap': 0.03728842503269433}, '1tqo': {'holo': '1tr5', 'rmsd': 0.6441666663712677, 'ligand': 'THP', 'overlap': 0.09943304760719905}, '2gg4': {'holo': '2gg6', 'rmsd': 4.053610489733732, 'ligand': 'S3P', 'overlap': 0.32226681990743533}, '1xqz': {'holo': '1xr1', 'rmsd': 0.8735291349884569, 'ligand': 'ANP', 'overlap': 0.03322565994229599}, '1ri5': {'holo': '1ri1', 'rmsd': 0.4756848438429417, 'ligand': 'GTG', 'overlap': 0.40634410780764774}, '1p38': {'holo': '1bmk', 'rmsd': 0.49475592255264006, 'ligand': 'SB5', 'overlap': 0.16284355281518356}, '1z1i': {'holo': '2gx4', 'rmsd': 0.943572422028664, 'ligand': 'NOL', 'overlap': 0.4448793087833217}, '4ape': {'holo': '2v00', 'rmsd': 0.37870807087859537, 'ligand': 'V15', 'overlap': 0.18888234876200738}, '1wos': {'holo': '1wop', 'rmsd': 0.2366436759942632, 'ligand': 'FFO', 'overlap': 0.051811499365777516}, '1jam': {'holo': '1lp4', 'rmsd': 0.5294940012944506, 'ligand': 'ANP', 'overlap': 0.14077385733755635}, '1mtz': {'holo': '1mu0', 'rmsd': 0.5811436641707657, 'ligand': 'PHK', 'overlap': 0.07460944026829339}, '1jcf': {'holo': '1jcg', 'rmsd': 0.3839860003692609, 'ligand': 'ANP', 'overlap': 0.15740954956225073}, '1xqo': {'holo': '1xqp', 'rmsd': 0.7306725684611958, 'ligand': '8HG', 'overlap': 0.006124059539787701}, '3ewq': {'holo': '3ewr', 'rmsd': 0.4118729656576964, 'ligand': 'APR', 'overlap': 0.2245799191683995}, '2sga': {'holo': '1sgc', 'rmsd': 0.10841517059892908, 'ligand': 'CST', 'overlap': 0.25558985372325815}, '1f10': {'holo': '1n4f', 'rmsd': 0.5191688204021571, 'ligand': 'ASR', 'overlap': 0.6209751871169322}
}
for pdb_apo in d_apo2holo.keys():
bool_continue = skip_pdb(pdb_apo,d_apo2holo,d_cath,)
if bool_continue == True:
continue
pdb_holo = d_apo2holo[pdb_apo]['holo']
## continue ## tmp!!!
print pdb_apo, pdb_holo
##
## parse coordinates
##
d_mmCIF_apo, l_coords_alpha_apo = parse_coords(pdb_apo)
d_mmCIF_holo, l_coords_alpha_holo = parse_coords(pdb_holo)
tv1, rm, tv2, l_coords_alpha_apo, l_coords_alpha_holo = get_transformation_matrix(
d_mmCIF_apo, l_coords_alpha_apo,
d_mmCIF_holo, l_coords_alpha_holo,
)
vector_apo2holo = get_apo_holo_vector(
d_mmCIF_apo, l_coords_alpha_apo,
d_mmCIF_holo, l_coords_alpha_holo,
tv1, rm, tv2,
)
chain_apo = ''.join(d_mmCIF_apo['_entity_poly.pdbx_strand_id'])
chain_holo = ''.join(d_mmCIF_holo['_entity_poly.pdbx_strand_id'])
ligand_pos_apo, ligand_pos_holo = get_ligand_pos(
d_mmCIF_holo,
tv1, rm, tv2,
d_apo2holo[pdb_apo]['ligand'],
)
dist_max = 6
dist_min = 3
for pdb, chain, l_coords_alpha, ligand_pos in [
[pdb_holo,chain_holo,l_coords_alpha_holo,ligand_pos_holo,],
[pdb_apo,chain_apo,l_coords_alpha_apo,ligand_pos_apo,],
]:
mode_max_apoholo, overlap_max_apoholo, l_overlaps, max_mode = goodvibes_ligand.main(
pdb,chain,
dist_max,dist_min,
v_apoholo=vector_apo2holo,
l_coords_probe = [ligand_pos],
l_coords_protein_alpha = l_coords_alpha,
)
print pdb, mode_max_apoholo, overlap_max_apoholo, l_overlaps[0]
s = '%s %s %s %s %s %s\n' %(
pdb,pdb_apo,pdb_holo,mode_max_apoholo,
round(overlap_max_apoholo,3), round(l_overlaps[0],3),
)
switch_max = 3
if mode_max_apoholo < 12: suffix_mode = 'low'
else: suffix_mode = 'high'
if mode_max_apoholo == max_mode: suffix_switch = 'same'
else: suffix_switch = 'switched'
if pdb == pdb_apo: suffix_pdb = 'apo'
else: suffix_pdb = 'holo'
## fd = open('induced_or_sampling_%s_%s_%s.txt' %(
## switch_max,suffix_pdb,suffix_mode,
fd = open('induced_or_sampling_%s_%s_%s_%s.txt' %(
switch_max,suffix_pdb,suffix_mode,suffix_switch,
),'a')
fd.write(s)
fd.close()
print 'f(x) = x'
print 'g(x) = x-0.05'
print 'h(x) = x+0.05'
print 'set xlabel "max overlap between apo/holo motion"'
print 'set ylabel "max overlap between apo/holo motion - perturbed"'
s = 'plot [0.1:1][0.1:1]'
s += '"induced_or_sampling_3_apo_low_same.txt" u 5:6 t "apo, mode of max contribution = [6:12], mode not switched", '
s += '"induced_or_sampling_3_holo_low_same.txt" u 5:6 t "holo, mode of max contribution = [6:12], mode not switched", '
s += '"induced_or_sampling_3_apo_low_switched.txt" u 5:6 t "apo, mode of max contribution = [6:12], mode switched", '
s += '"induced_or_sampling_3_holo_low_switched.txt" u 5:6 t "holo, mode of max contribution = [6:12], mode switched", '
s += '"induced_or_sampling_3_apo_high_same.txt" u 5:6 t "apo, mode of max contribution > 12, mode not switched", '
s += '"induced_or_sampling_3_holo_high_same.txt" u 5:6 t "holo, mode of max contribution > 12, mode not switched", '
s += '"induced_or_sampling_3_apo_high_switched.txt" u 5:6 t "apo, mode of max contribution > 12, mode switched", '
s += '"induced_or_sampling_3_holo_high_switched.txt" u 5:6 t "holo, mode of max contribution > 12, mode switched", '
s += 'f(x) t "", g(x) t "" lc 0, h(x) t "" lc 0'
print s
print 'set key out vert top right'
print 'plot [0.1:1][0.1:1]"induced_or_sampling_3_apo_low.txt" u 5:6 t "apo, mode of max contribution = [6:12]", "induced_or_sampling_3_holo_low.txt" u 5:6 t "holo, mode of max contribution = [6:12]", "induced_or_sampling_3_apo_high.txt" u 5:6 t "apo, mode of max contribution > 12", "induced_or_sampling_3_holo_high.txt" u 5:6 t "holo, mode of max overlap > 12", f(x) t "", g(x) t "" lc 0, h(x) t "" lc 0'
print 'end of main'
return
def main():
## dictionary of apo and holo structures (from what script???)
d_apo2holo = {
## conformational selection
## RNase A, 1kf3 high resolution
## '1kf3': {'holo': '1rpg','ligand':'CPA',},
'1kf5': {
'holo': '1eow',
'ligand': 'U2G',
'site': [
11,
43,
44,
## 119,120,121,122, ## terminal flexible residues...
],
'title': 'Ribonuclease (RNase) A',
},
## CypA, highest resolution room
## '3k0n': {'holo': '1cwa','ligand':['DAL','MLE','MVA','BMT','ABA','SAR',],'site':[18-1,54-1,59-1,62-1,71-1,100-1,101-1,102-1,110-1,112-1,120-1,121-1,125-1,163-1,],'title':'Peptidyl-prolyl isomerase A (CypA)',},
'1w8v': {
'holo': '1w8m',
'ligand': [
'E1P',
],
'site': [
54,
62,
100,
101,
112,
125,
],
'title': 'Peptidyl-prolyl isomerase A (CypA)',
},
## DHFR
'1ra9': {
'holo': '1ra2',
'ligand': 'FOL',
'site': [
4,
5,
6,
26,
27,
30,
31,
56,
93,
112,
],
'title': 'Dihydrofolate reductase (DHFR)',
},
## AdK
'2rh5': {
'holo':
'2rgx',
'ligand':
'AP5',
'coords_apo': [0, 202],
'coords_holo': [0, 202],
'site': [
8,
9,
10,
11,
12,
13,
14,
30,
31,
34,
57,
58,
63,
81,
84,
88,
119,
120,
123,
134,
137,
149,
160,
188,
189,
190,
],
'title':
'Adenylate kinase (AdK)',
},
## PKA
'3iia': {
'holo':
'3pna',
'ligand':
'CMP',
'coords_apo': [4, 133],
'coords_holo': [0, 129],
'site': [
182 - 112,
198 - 112,
199 - 112,
200 - 112,
201 - 112,
202 - 112,
209 - 112,
211 - 112,
],
'title':
'Protein Kinase A (PKA)',
},
## induced fit
## PEPCK
'2qew': {
'holo': '3dt4',
'ligand': 'OXL',
'coords_apo': [1, 620],
'coords_holo': [0, 619],
'site': [240, 260, 307, 401],
'title': 'PEPCK',
},
## beta-lactoglobulin
'3npo': {
'holo': '3nq3',
'ligand': 'DKA',
'site': [
53,
104,
106,
],
'title': 'beta-lactoglobulin',
},
}
for pdb_apo in d_apo2holo.keys():
pdb_holo = d_apo2holo[pdb_apo]['holo']
## continue ## tmp!!!
print pdb_apo, pdb_holo
##
## parse coordinates
##
d_mmCIF_apo, l_coords_alpha_apo = parse_coords(pdb_apo)
d_mmCIF_holo, l_coords_alpha_holo = parse_coords(pdb_holo)
if 'coords_apo' in d_apo2holo[pdb_apo].keys():
l_coords_alpha_apo = l_coords_alpha_apo[d_apo2holo[pdb_apo][
'coords_apo'][0]:d_apo2holo[pdb_apo]['coords_apo'][1]]
l_coords_alpha_holo = l_coords_alpha_holo[d_apo2holo[pdb_apo][
'coords_holo'][0]:d_apo2holo[pdb_apo]['coords_holo'][1]]
else:
## sequential alignment of coordinates
index1_seq_apo = next((i for i, v in enumerate(
d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id']) if v != '?'))
index1_seq_holo = next((i for i, v in enumerate(
d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id']) if v != '?'))
## last non-?
index2_seq_apo = len(
d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id']) - next(
(i for i, v in enumerate(
reversed(
d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id']))
if v != '?'))
index2_seq_holo = len(
d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id']) - next(
(i for i, v in enumerate(
reversed(
d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id']))
if v != '?'))
## first common non-?
index1_coord_apo = max(0, index1_seq_holo - index1_seq_apo)
index1_coord_holo = max(0, index1_seq_apo - index1_seq_holo)
## last common non-?
index2_coord_apo = len(l_coords_alpha_apo) + min(
0, index2_seq_holo - index2_seq_apo)
index2_coord_holo = len(l_coords_alpha_holo) + min(
0, index2_seq_apo - index2_seq_holo)
l_coords_alpha_apo = l_coords_alpha_apo[
index1_coord_apo:index2_coord_apo]
l_coords_alpha_holo = l_coords_alpha_holo[
index1_coord_holo:index2_coord_holo]
if pdb_apo == '2qew' and pdb_holo == '3dt4':
## l_coords_alpha_holo = l_coords_alpha_holo[:459]+l_coords_alpha_holo[466:]
l_coords_alpha_holo = l_coords_alpha_holo[:
461] + l_coords_alpha_holo[
461 + 7:]
if len(l_coords_alpha_apo) != len(l_coords_alpha_holo):
print pdb_apo, pdb_holo
print len(l_coords_alpha_apo), len(l_coords_alpha_holo)
stop
## if pdb_holo == '1eow':
## print l_coords_alpha_holo[d_apo2holo[pdb_apo]['site'][0]]
## print pdb_holo
## stop
tv1, rm, tv2, l_coords_alpha_apo, l_coords_alpha_holo = get_transformation_matrix(
l_coords_alpha_apo,
l_coords_alpha_holo,
)
vector_apo2holo = get_apo_holo_vector(
d_mmCIF_apo,
l_coords_alpha_apo,
d_mmCIF_holo,
l_coords_alpha_holo,
tv1,
rm,
tv2,
)
chain_apo = ''.join(d_mmCIF_apo['_entity_poly.pdbx_strand_id'])
chain_holo = ''.join(d_mmCIF_holo['_entity_poly.pdbx_strand_id'])
if pdb_holo == '1cwa':
ligand_pos_holo = numpy.array([3.307729, 36.55456, 17.45886])
ligand_pos_apo = numpy.dot(ligand_pos_holo - tv1, rm) + tv2
else:
ligand_pos_apo, ligand_pos_holo, lines_ligand_apo = get_ligand_pos(
d_mmCIF_holo,
tv1,
rm,
tv2,
d_apo2holo[pdb_apo]['ligand'],
pdb_holo,
)
dist_max = 6
dist_min = 3
## print len(vector_apo2holo), len(l_coords_alpha_apo)
## stop
for pdb, chain, l_coords_alpha, ligand_pos in [
## [pdb_holo,chain_holo,l_coords_alpha_holo,],
[pdb_apo, chain_apo, l_coords_alpha_apo, ligand_pos_apo],
]:
## l_coords_protein_alpha = []
## for i in range(len(l_coords_alpha)):
## l_coords_protein_alpha += [l_coords_alpha[i][0]]
## l_coords_protein_alpha += [l_coords_alpha[i][1]]
## l_coords_protein_alpha += [l_coords_alpha[i][2]]
fn = '/home/tc/UCD/GV_ligand_binding_site_identification/%s_%s_probe.pdb' % (
pdb,
chain,
)
if os.path.isfile(fn):
continue
d = goodvibes_ligand.main(
pdb,
chain,
dist_max,
dist_min,
v_apoholo=vector_apo2holo,
l_coords_protein_alpha=l_coords_alpha,
## l_coords_probe = [ligand_pos],
)
## d = goodvibes_ligand.main(
## pdb,chain,
## dist_max,dist_min,
## v_apoholo=vector_apo2holo,
## l_coords_protein_alpha = l_coords_alpha,
## l_coords_probe = [ligand_pos],
## )
l_factors = d['l_factors']
## l_factors_perturbed = d['l_factors_probe']
if os.path.isfile(fn):
fd = open(fn, 'r')
lines = fd.readlines()
fd.close()
lines += lines_ligand_apo
fd = open(fn + '2', 'w')
fd.writelines(lines)
fd.close()
continue
eigenvectors = d['eigenvectors']
l_factors_abs = [abs(factor) for factor in l_factors]
mode_max_contribution = l_factors_abs.index(max(l_factors_abs))
print mode_max_contribution
print d['l_overlaps']
v1 = vector_apo2holo
eigenvector = v2 = eigenvectors[mode_max_contribution]
overlap_max = abs(numpy.dot(v1, v2)) / math.sqrt(
numpy.dot(v1, v1) * numpy.dot(v2, v2))
print 'mode_max_contribution', mode_max_contribution
print 'overlap_max', overlap_max
## write amplitudes
lines = []
l1 = []
l2 = []
for i in range(0, len(eigenvector), 3):
amplitude = math.sqrt(eigenvector[i + 0]**2 +
eigenvector[i + 1]**2 +
eigenvector[i + 2]**2)
amplitude7 = math.sqrt(eigenvectors[6][i + 0]**2 +
eigenvectors[6][i + 1]**2 +
eigenvectors[6][i + 2]**2)
l1 += [amplitude]
l2 += [amplitude7]
if i / 3 in d_apo2holo[pdb_apo]['site']:
bool_site = amplitude
else:
bool_site = -1
lines += ['%s %s %s\n' % (
amplitude,
amplitude7,
bool_site,
)]
fd = open('amplitudes_%s%s.txt' % (
pdb_apo,
pdb_holo,
), 'w')
fd.writelines(lines)
fd.close()
r = statistics.correlation(l1, l2)
xmin = 0
if pdb_holo == '1w8m':
xmin = 2
if pdb_holo == '3dt4':
xmin = 5
if pdb_holo == '1eow':
xmin = 1
lines = [
'set terminal png\n',
'set output "%s%s_amplitudes.png"\n' % (
pdb_apo,
pdb_holo,
),
'set size 1,1\n',
'set xlabel "residue index"\n',
'set ylabel "amplitude (a.u.)\n',
'set title "%s (r = %.2f)"\n' % (
d_apo2holo[pdb_apo]['title'],
r,
),
'set key out\n',
'f(x) = %s\n' % (sum(l1) / len(l1)),
'plot [%s:][0:]"amplitudes_%s%s.txt" u 1 t "mode %i" w l, "amplitudes_%s%s.txt" u 2 t "mode 7" w l, "amplitudes_%s%s.txt" u 3 t "binding site" ps 1 pt 7, f(x) t "average amplitude"\n'
% (
## 'plot [%s:][0:]"amplitudes_%s%s.txt" u 1 t "mode %i" w l, "amplitudes_%s%s.txt" u 2 t "mode 7" w l, "amplitudes_%s%s.txt" u 3 t "binding site" ps 1 pt 7\n' %(
xmin,
pdb_apo,
pdb_holo,
mode_max_contribution + 1,
pdb_apo,
pdb_holo,
pdb_apo,
pdb_holo,
),
]
fd = open('gnuplot.settings', 'w')
fd.writelines(lines)
fd.close()
os.system('/usr/bin/gnuplot gnuplot.settings')
s = ''
for i in range(len(l_factors)):
s += '%s %s %s\n' % (
i + 1,
l_factors[i],
abs(l_factors[i]),
)
fd = open('facs_eigvals_%s%s.txt' % (
pdb_apo,
pdb_holo,
), 'w')
fd.write(s)
fd.close()
## s = ''
## for i in range(len(l_factors_perturbed)):
## s += '%s %s %s\n' %(i+1, l_factors_perturbed[i],abs(l_factors_perturbed[i]),)
## fd = open('facs_eigvals_%s%s_perturbed.txt' %(pdb_apo,pdb_holo,),'w')
## fd.write(s)
## fd.close()
return
def main():
d_cath = parse_CATH()
## dictionary of apo and holo structures (from what script???)
d_apo2holo = {
'1ak1': {
'holo': '1c1h',
'rmsd': 0.64,
'ligand': 'MMP',
'overlap': 0.36
},
'1lp8': {
'holo': '1lpc',
'rmsd': 0.14003320157149318,
'ligand': 'CMP',
'overlap': 0.1663339954531419
},
'2exo': {
'holo': '1j01',
'rmsd': 0.31317202378931264,
'ligand': 'XIL',
'overlap': 0.5464584014950491
},
'1syc': {
'holo': '1syd',
'rmsd': 0.42370903255794784,
'ligand': 'THP',
'overlap': 0.312528957121447
},
'1cua': {
'holo': '3esd',
'rmsd': 0.4040397349113579,
'ligand': 'SXC',
'overlap': 0.08139930257927935
},
'1znw': {
'holo': '1znx',
'rmsd': 0.24704558797447082,
'ligand': '5GP',
'overlap': 0.12436531581580901
},
'1gbs': {
'holo': '1lsp',
'rmsd': 0.264857015278693,
'ligand': 'BUL',
'overlap': 0.2934470556757598
},
'1sqg': {
'holo': '1sqf',
'rmsd': 0.6990763011194481,
'ligand': 'SAM',
'overlap': 0.4723483760294988
},
'3npo': {
'holo': '3nq3',
'rmsd': 0.7183351557421368,
'ligand': 'DKA',
'overlap': 0.04712778545695382
},
'2e3m': {
'holo': '2e3q',
'rmsd': 0.8849429260246913,
'ligand': '18C',
'overlap': 0.09031491180306017
},
'3k0n': {
'holo': '1w8m',
'rmsd': 0.39833839324838677,
'ligand': 'E1P',
'overlap': 0.06688885295094558
},
'3aap': {
'holo': '3aar',
'rmsd': 0.3572808619937969,
'ligand': 'ANP',
'overlap': 0.35015656527393507
},
'1bk7': {
'holo': '1ucd',
'rmsd': 0.5608983876422892,
'ligand': 'U5P',
'overlap': 0.6239173853318093
},
'1tgn': {
'holo': '1tni',
'rmsd': 1.937557415391448,
'ligand': 'PBN',
'overlap': 0.17747463719381318
},
'1ahc': {
'holo': '1ahb',
'rmsd': 0.19271320420696525,
'ligand': 'FMP',
'overlap': 0.2906115852531481
},
'3mft': {
'holo': '3mfu',
'rmsd': 0.5294319317376655,
'ligand': 'ANP',
'overlap': 0.5901312084425671
},
'1erk': {
'holo': '4erk',
'rmsd': 1.8403643776383745,
'ligand': 'OLO',
'overlap': 0.2606792215029042
},
'1sll': {
'holo': '4sli',
'rmsd': 0.27110444955664886,
'ligand': 'CNP',
'overlap': 0.09295343747516871
},
'1rtc': {
'holo': '1br6',
'rmsd': 0.7736294829905356,
'ligand': 'PT1',
'overlap': 0.02244838892564617
},
'1gy0': {
'holo': '1og1',
'rmsd': 0.26938443289620695,
'ligand': 'TAD',
'overlap': 0.11337131846497911
},
'2hbj': {
'holo': '2hbl',
'rmsd': 0.2791711771177489,
'ligand': 'AMP',
'overlap': 0.2654241484172416
},
'1rd6': {
'holo': '1x6n',
'rmsd': 0.29783872255245375,
'ligand': 'AO3',
'overlap': 0.020924868377188755
},
'1mzl': {
'holo': '1mzm',
'rmsd': 0.4977604676331388,
'ligand': 'PLM',
'overlap': 0.15358351922009683
},
'1hka': {
'holo': '1eqm',
'rmsd': 3.101848541109514,
'ligand': '',
'overlap': 0.29938268367048587
},
'2ppn': {
'holo': '1fkh',
'rmsd': 0.5498751329287473,
'ligand': 'SBX',
'overlap': 0.008728602838910722
},
'2vfy': {
'holo': '2vfk',
'rmsd': 0.5234309202023915,
'ligand': 'AMP',
'overlap': 0.4186721907995304
},
'1yhv': {
'holo': '2hy8',
'rmsd': 0.7580522933908197,
'ligand': '1ST',
'overlap': 0.6167885584722257
},
'1eur': {
'holo': '1eus',
'rmsd': 0.3471466880748409,
'ligand': 'DAN',
'overlap': 0.656212298345592
},
'3a0x': {
'holo': '3a0t',
'rmsd': 1.4778758006848136,
'ligand': '',
'overlap': 0.08855830101729956
},
'1mri': {
'holo': '1mrh',
'rmsd': 0.20580455271425652,
'ligand': 'FMC',
'overlap': 0.2616567944535416
},
'2zj8': {
'holo': '2zja',
'rmsd': 0.39958904846327736,
'ligand': 'ACP',
'overlap': 0.15477640189079234
},
'2ggo': {
'holo': '2ggq',
'rmsd': 0.41217362536688407,
'ligand': 'TTP',
'overlap': 0.21415433688009522
},
'1bbc': {
'holo': '1db4',
'rmsd': 1.3942309487855171,
'ligand': '8IN',
'overlap': 0.12052760594053587
},
'3c0e': {
'holo': '3c11',
'rmsd': 0.40358994049970154,
'ligand': 'GMY',
'overlap': 0.18401963629557413
},
'1tje': {
'holo': '1tkg',
'rmsd': 0.5953813587886109,
'ligand': 'SSA',
'overlap': 0.3496015526554969
},
'1wvw': {
'holo': '1wvy',
'rmsd': 0.9674023140460931,
'ligand': 'STU',
'overlap': 0.13588790082354602
},
'1ifb': {
'holo': '2ifb',
'rmsd': 0.36597921461938127,
'ligand': 'PLM',
'overlap': 0.2728603476085213
},
'1qtr': {
'holo': '1x2e',
'rmsd': 0.4771243544672125,
'ligand': 'ATX',
'overlap': 0.003613865518161083
},
'1pdb': {
'holo': '3nxv',
'rmsd': 0.7597621325331363,
'ligand': 'D2F',
'overlap': 0.07405896998672913
},
'2qev': {
'holo': '2qeh',
'rmsd': 0.26344417969606054,
'ligand': 'SRO',
'overlap': 0.14227481558897756
},
'3g6l': {
'holo': '3g6m',
'rmsd': 0.1606666839962277,
'ligand': 'CFF',
'overlap': 0.2849120042129244
},
'1arl': {
'holo': '2rfh',
'rmsd': 0.349832513662932,
'ligand': '23N',
'overlap': 0.314294597059561
},
'2vfb': {
'holo': '3ltw',
'rmsd': 0.2811833881753945,
'ligand': 'HLZ',
'overlap': 0.03642491522930895
},
'1akz': {
'holo': '3fck',
'rmsd': 0.5257761484670386,
'ligand': 'FCK',
'overlap': 0.43841384942941936
},
'2paw': {
'holo': '1a26',
'rmsd': 0.3302247982261714,
'ligand': 'CNA',
'overlap': 0.07651713423342446
},
'1kqx': {
'holo': '1kqw',
'rmsd': 0.6648748206255346,
'ligand': 'RTL',
'overlap': 0.2243499171280635
},
'3pte': {
'holo': '1yqs',
'rmsd': 0.19520439729404254,
'ligand': 'BSA',
'overlap': 0.23347037537804616
},
'1iad': {
'holo': '1qji',
'rmsd': 0.33860211897807524,
'ligand': 'PKF',
'overlap': 0.19714803737138323
},
'3blm': {
'holo': '1blh',
'rmsd': 0.21196668540983332,
'ligand': 'FOS',
'overlap': 0.35086757294487353
},
'2d59': {
'holo': '2d5a',
'rmsd': 1.191748760948045,
'ligand': '',
'overlap': 0.19626132868398616
},
'1lmn': {
'holo': '1bb7',
'rmsd': 0.12717943435514337,
'ligand': 'GUM',
'overlap': 0.1248915962046876
},
'1kf5': {
'holo': '1eow',
'rmsd': 0.18795641863024692,
'ligand': 'U2G',
'overlap': 0.24946252748542863
},
'2sil': {
'holo': '2sim',
'rmsd': 0.1425616125054784,
'ligand': 'DAN',
'overlap': 0.021600224935827056
},
'2zco': {
'holo': '2zcs',
'rmsd': 0.2685379543685112,
'ligand': 'B70',
'overlap': 0.6230371569077154
},
'2ac4': {
'holo': '2q2o',
'rmsd': 0.4309651624839198,
'ligand': 'H01',
'overlap': 0.02673223321151024
},
'1ojq': {
'holo': '1ojz',
'rmsd': 0.8206121849480196,
'ligand': '',
'overlap': 0.496036330611861
},
'1ey0': {
'holo': '1stg',
'rmsd': 0.701380747069386,
'ligand': 'THP',
'overlap': 0.16741304780628186
},
'1yes': {
'holo': '1byq',
'rmsd': 0.8384813140092745,
'ligand': '',
'overlap': 0.23598536851862675
},
'1sye': {
'holo': '1syf',
'rmsd': 0.699830584716955,
'ligand': 'THP',
'overlap': 0.03728842503269433
},
'1tqo': {
'holo': '1tr5',
'rmsd': 0.6441666663712677,
'ligand': 'THP',
'overlap': 0.09943304760719905
},
'2gg4': {
'holo': '2gg6',
'rmsd': 4.053610489733732,
'ligand': 'S3P',
'overlap': 0.32226681990743533
},
'1xqz': {
'holo': '1xr1',
'rmsd': 0.8735291349884569,
'ligand': 'ANP',
'overlap': 0.03322565994229599
},
'1ri5': {
'holo': '1ri1',
'rmsd': 0.4756848438429417,
'ligand': 'GTG',
'overlap': 0.40634410780764774
},
'1p38': {
'holo': '1bmk',
'rmsd': 0.49475592255264006,
'ligand': 'SB5',
'overlap': 0.16284355281518356
},
'1z1i': {
'holo': '2gx4',
'rmsd': 0.943572422028664,
'ligand': 'NOL',
'overlap': 0.4448793087833217
},
'4ape': {
'holo': '2v00',
'rmsd': 0.37870807087859537,
'ligand': 'V15',
'overlap': 0.18888234876200738
},
'1wos': {
'holo': '1wop',
'rmsd': 0.2366436759942632,
'ligand': 'FFO',
'overlap': 0.051811499365777516
},
'1jam': {
'holo': '1lp4',
'rmsd': 0.5294940012944506,
'ligand': 'ANP',
'overlap': 0.14077385733755635
},
'1mtz': {
'holo': '1mu0',
'rmsd': 0.5811436641707657,
'ligand': 'PHK',
'overlap': 0.07460944026829339
},
'1jcf': {
'holo': '1jcg',
'rmsd': 0.3839860003692609,
'ligand': 'ANP',
'overlap': 0.15740954956225073
},
'1xqo': {
'holo': '1xqp',
'rmsd': 0.7306725684611958,
'ligand': '8HG',
'overlap': 0.006124059539787701
},
'3ewq': {
'holo': '3ewr',
'rmsd': 0.4118729656576964,
'ligand': 'APR',
'overlap': 0.2245799191683995
},
'2sga': {
'holo': '1sgc',
'rmsd': 0.10841517059892908,
'ligand': 'CST',
'overlap': 0.25558985372325815
},
'1f10': {
'holo': '1n4f',
'rmsd': 0.5191688204021571,
'ligand': 'ASR',
'overlap': 0.6209751871169322
}
}
for pdb_apo in d_apo2holo.keys():
bool_continue = skip_pdb(
pdb_apo,
d_apo2holo,
d_cath,
)
if bool_continue == True:
continue
pdb_holo = d_apo2holo[pdb_apo]['holo']
## continue ## tmp!!!
print pdb_apo, pdb_holo
##
## parse coordinates
##
d_mmCIF_apo, l_coords_alpha_apo = parse_coords(pdb_apo)
d_mmCIF_holo, l_coords_alpha_holo = parse_coords(pdb_holo)
tv1, rm, tv2, l_coords_alpha_apo, l_coords_alpha_holo = get_transformation_matrix(
d_mmCIF_apo,
l_coords_alpha_apo,
d_mmCIF_holo,
l_coords_alpha_holo,
)
vector_apo2holo = get_apo_holo_vector(
d_mmCIF_apo,
l_coords_alpha_apo,
d_mmCIF_holo,
l_coords_alpha_holo,
tv1,
rm,
tv2,
)
chain_apo = ''.join(d_mmCIF_apo['_entity_poly.pdbx_strand_id'])
chain_holo = ''.join(d_mmCIF_holo['_entity_poly.pdbx_strand_id'])
ligand_pos_apo, ligand_pos_holo = get_ligand_pos(
d_mmCIF_holo,
tv1,
rm,
tv2,
d_apo2holo[pdb_apo]['ligand'],
)
dist_max = 6
dist_min = 3
for pdb, chain, l_coords_alpha, ligand_pos in [
[
pdb_holo,
chain_holo,
l_coords_alpha_holo,
ligand_pos_holo,
],
[
pdb_apo,
chain_apo,
l_coords_alpha_apo,
ligand_pos_apo,
],
]:
mode_max_apoholo, overlap_max_apoholo, l_overlaps, max_mode = goodvibes_ligand.main(
pdb,
chain,
dist_max,
dist_min,
v_apoholo=vector_apo2holo,
l_coords_probe=[ligand_pos],
l_coords_protein_alpha=l_coords_alpha,
)
print pdb, mode_max_apoholo, overlap_max_apoholo, l_overlaps[0]
s = '%s %s %s %s %s %s\n' % (
pdb,
pdb_apo,
pdb_holo,
mode_max_apoholo,
round(overlap_max_apoholo, 3),
round(l_overlaps[0], 3),
)
switch_max = 3
if mode_max_apoholo < 12: suffix_mode = 'low'
else: suffix_mode = 'high'
if mode_max_apoholo == max_mode: suffix_switch = 'same'
else: suffix_switch = 'switched'
if pdb == pdb_apo: suffix_pdb = 'apo'
else: suffix_pdb = 'holo'
## fd = open('induced_or_sampling_%s_%s_%s.txt' %(
## switch_max,suffix_pdb,suffix_mode,
fd = open(
'induced_or_sampling_%s_%s_%s_%s.txt' % (
switch_max,
suffix_pdb,
suffix_mode,
suffix_switch,
), 'a')
fd.write(s)
fd.close()
print 'f(x) = x'
print 'g(x) = x-0.05'
print 'h(x) = x+0.05'
print 'set xlabel "max overlap between apo/holo motion"'
print 'set ylabel "max overlap between apo/holo motion - perturbed"'
s = 'plot [0.1:1][0.1:1]'
s += '"induced_or_sampling_3_apo_low_same.txt" u 5:6 t "apo, mode of max contribution = [6:12], mode not switched", '
s += '"induced_or_sampling_3_holo_low_same.txt" u 5:6 t "holo, mode of max contribution = [6:12], mode not switched", '
s += '"induced_or_sampling_3_apo_low_switched.txt" u 5:6 t "apo, mode of max contribution = [6:12], mode switched", '
s += '"induced_or_sampling_3_holo_low_switched.txt" u 5:6 t "holo, mode of max contribution = [6:12], mode switched", '
s += '"induced_or_sampling_3_apo_high_same.txt" u 5:6 t "apo, mode of max contribution > 12, mode not switched", '
s += '"induced_or_sampling_3_holo_high_same.txt" u 5:6 t "holo, mode of max contribution > 12, mode not switched", '
s += '"induced_or_sampling_3_apo_high_switched.txt" u 5:6 t "apo, mode of max contribution > 12, mode switched", '
s += '"induced_or_sampling_3_holo_high_switched.txt" u 5:6 t "holo, mode of max contribution > 12, mode switched", '
s += 'f(x) t "", g(x) t "" lc 0, h(x) t "" lc 0'
print s
print 'set key out vert top right'
print 'plot [0.1:1][0.1:1]"induced_or_sampling_3_apo_low.txt" u 5:6 t "apo, mode of max contribution = [6:12]", "induced_or_sampling_3_holo_low.txt" u 5:6 t "holo, mode of max contribution = [6:12]", "induced_or_sampling_3_apo_high.txt" u 5:6 t "apo, mode of max contribution > 12", "induced_or_sampling_3_holo_high.txt" u 5:6 t "holo, mode of max overlap > 12", f(x) t "", g(x) t "" lc 0, h(x) t "" lc 0'
print 'end of main'
return
def main():
## dictionary of apo and holo structures (from what script???)
d_apo2holo = {
## conformational selection
## RNase A, 1kf3 high resolution
## '1kf3': {'holo': '1rpg','ligand':'CPA',},
'1kf5': {
'holo': '1eow','ligand':'U2G',
'site':[
11,43,44,
## 119,120,121,122, ## terminal flexible residues...
],
'title':'Ribonuclease (RNase) A',
},
## CypA, highest resolution room
## '3k0n': {'holo': '1cwa','ligand':['DAL','MLE','MVA','BMT','ABA','SAR',],'site':[18-1,54-1,59-1,62-1,71-1,100-1,101-1,102-1,110-1,112-1,120-1,121-1,125-1,163-1,],'title':'Peptidyl-prolyl isomerase A (CypA)',},
'1w8v': {'holo': '1w8m','ligand':['E1P',],'site':[54,62,100,101,112,125,],'title':'Peptidyl-prolyl isomerase A (CypA)',},
## DHFR
'1ra9': {'holo': '1ra2','ligand':'FOL','site':[4,5,6,26,27,30,31,56,93,112,],'title':'Dihydrofolate reductase (DHFR)',},
## AdK
'2rh5': {'holo': '2rgx','ligand':'AP5','coords_apo':[0,202],'coords_holo':[0,202],'site':[8,9,10,11,12,13,14,30,31,34,57,58,63,81,84,88,119,120,123,134,137,149,160,188,189,190,],'title':'Adenylate kinase (AdK)',},
## PKA
'3iia': {'holo': '3pna', 'ligand':'CMP', 'coords_apo':[4,133],'coords_holo':[0,129],'site':[
182-112, 198-112, 199-112, 200-112, 201-112, 202-112, 209-112, 211-112,
],
'title':'Protein Kinase A (PKA)',
},
## induced fit
## PEPCK
'2qew': {'holo': '3dt4', 'ligand':'OXL', 'coords_apo':[1,620],'coords_holo':[0,619],'site':[240,260,307,401],'title':'PEPCK',},
## beta-lactoglobulin
'3npo': {'holo': '3nq3', 'ligand':'DKA','site':[53,104,106,],'title':'beta-lactoglobulin',},
}
for pdb_apo in d_apo2holo.keys():
pdb_holo = d_apo2holo[pdb_apo]['holo']
## continue ## tmp!!!
print pdb_apo, pdb_holo
##
## parse coordinates
##
d_mmCIF_apo, l_coords_alpha_apo = parse_coords(pdb_apo)
d_mmCIF_holo, l_coords_alpha_holo = parse_coords(pdb_holo)
if 'coords_apo' in d_apo2holo[pdb_apo].keys():
l_coords_alpha_apo = l_coords_alpha_apo[
d_apo2holo[pdb_apo]['coords_apo'][0]:d_apo2holo[pdb_apo]['coords_apo'][1]
]
l_coords_alpha_holo = l_coords_alpha_holo[
d_apo2holo[pdb_apo]['coords_holo'][0]:d_apo2holo[pdb_apo]['coords_holo'][1]
]
else:
## sequential alignment of coordinates
index1_seq_apo = next((i for i,v in enumerate(d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id']) if v != '?'))
index1_seq_holo = next((i for i,v in enumerate(d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id']) if v != '?'))
## last non-?
index2_seq_apo = len(d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id'])-next((i for i,v in enumerate(reversed(d_mmCIF_apo['_pdbx_poly_seq_scheme.pdb_mon_id'])) if v != '?'))
index2_seq_holo = len(d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id'])-next((i for i,v in enumerate(reversed(d_mmCIF_holo['_pdbx_poly_seq_scheme.pdb_mon_id'])) if v != '?'))
## first common non-?
index1_coord_apo = max(0,index1_seq_holo-index1_seq_apo)
index1_coord_holo = max(0,index1_seq_apo-index1_seq_holo)
## last common non-?
index2_coord_apo = len(l_coords_alpha_apo)+min(0,index2_seq_holo-index2_seq_apo)
index2_coord_holo = len(l_coords_alpha_holo)+min(0,index2_seq_apo-index2_seq_holo)
l_coords_alpha_apo = l_coords_alpha_apo[index1_coord_apo:index2_coord_apo]
l_coords_alpha_holo = l_coords_alpha_holo[index1_coord_holo:index2_coord_holo]
if pdb_apo == '2qew' and pdb_holo == '3dt4':
## l_coords_alpha_holo = l_coords_alpha_holo[:459]+l_coords_alpha_holo[466:]
l_coords_alpha_holo = l_coords_alpha_holo[:461]+l_coords_alpha_holo[461+7:]
if len(l_coords_alpha_apo) != len(l_coords_alpha_holo):
print pdb_apo, pdb_holo
print len(l_coords_alpha_apo), len(l_coords_alpha_holo)
stop
## if pdb_holo == '1eow':
## print l_coords_alpha_holo[d_apo2holo[pdb_apo]['site'][0]]
## print pdb_holo
## stop
tv1, rm, tv2, l_coords_alpha_apo, l_coords_alpha_holo = get_transformation_matrix(
l_coords_alpha_apo,
l_coords_alpha_holo,
)
vector_apo2holo = get_apo_holo_vector(
d_mmCIF_apo, l_coords_alpha_apo,
d_mmCIF_holo, l_coords_alpha_holo,
tv1, rm, tv2,
)
chain_apo = ''.join(d_mmCIF_apo['_entity_poly.pdbx_strand_id'])
chain_holo = ''.join(d_mmCIF_holo['_entity_poly.pdbx_strand_id'])
if pdb_holo == '1cwa':
ligand_pos_holo = numpy.array([3.307729,36.55456,17.45886])
ligand_pos_apo = numpy.dot(ligand_pos_holo-tv1,rm)+tv2
else:
ligand_pos_apo, ligand_pos_holo, lines_ligand_apo = get_ligand_pos(
d_mmCIF_holo,
tv1, rm, tv2,
d_apo2holo[pdb_apo]['ligand'],
pdb_holo,
)
dist_max = 6
dist_min = 3
## print len(vector_apo2holo), len(l_coords_alpha_apo)
## stop
for pdb, chain, l_coords_alpha, ligand_pos in [
## [pdb_holo,chain_holo,l_coords_alpha_holo,],
[pdb_apo,chain_apo,l_coords_alpha_apo,ligand_pos_apo],
]:
## l_coords_protein_alpha = []
## for i in range(len(l_coords_alpha)):
## l_coords_protein_alpha += [l_coords_alpha[i][0]]
## l_coords_protein_alpha += [l_coords_alpha[i][1]]
## l_coords_protein_alpha += [l_coords_alpha[i][2]]
fn = '/home/tc/UCD/GV_ligand_binding_site_identification/%s_%s_probe.pdb' %(pdb,chain,)
if os.path.isfile(fn):
continue
d = goodvibes_ligand.main(
pdb,chain,
dist_max,dist_min,
v_apoholo=vector_apo2holo,
l_coords_protein_alpha = l_coords_alpha,
## l_coords_probe = [ligand_pos],
)
## d = goodvibes_ligand.main(
## pdb,chain,
## dist_max,dist_min,
## v_apoholo=vector_apo2holo,
## l_coords_protein_alpha = l_coords_alpha,
## l_coords_probe = [ligand_pos],
## )
l_factors = d['l_factors']
## l_factors_perturbed = d['l_factors_probe']
if os.path.isfile(fn):
fd = open(fn,'r')
lines = fd.readlines()
fd.close()
lines += lines_ligand_apo
fd = open(fn+'2','w')
fd.writelines(lines)
fd.close()
continue
eigenvectors = d['eigenvectors']
l_factors_abs = [abs(factor) for factor in l_factors]
mode_max_contribution = l_factors_abs.index(max(l_factors_abs))
print mode_max_contribution
print d['l_overlaps']
v1 = vector_apo2holo
eigenvector = v2 = eigenvectors[mode_max_contribution]
overlap_max = abs(numpy.dot(v1,v2))/math.sqrt(numpy.dot(v1,v1)*numpy.dot(v2,v2))
print 'mode_max_contribution', mode_max_contribution
print 'overlap_max', overlap_max
## write amplitudes
lines = []
l1 = []
l2 = []
for i in range(0,len(eigenvector),3):
amplitude = math.sqrt(eigenvector[i+0]**2+eigenvector[i+1]**2+eigenvector[i+2]**2)
amplitude7 = math.sqrt(eigenvectors[6][i+0]**2+eigenvectors[6][i+1]**2+eigenvectors[6][i+2]**2)
l1 += [amplitude]
l2 += [amplitude7]
if i/3 in d_apo2holo[pdb_apo]['site']:
bool_site = amplitude
else:
bool_site = -1
lines += ['%s %s %s\n' %(amplitude,amplitude7,bool_site,)]
fd = open('amplitudes_%s%s.txt' %(pdb_apo,pdb_holo,),'w')
fd.writelines(lines)
fd.close()
r = statistics.correlation(l1,l2)
xmin = 0
if pdb_holo == '1w8m':
xmin = 2
if pdb_holo == '3dt4':
xmin = 5
if pdb_holo == '1eow':
xmin = 1
lines = [
'set terminal png\n',
'set output "%s%s_amplitudes.png"\n' %(pdb_apo,pdb_holo,),
'set size 1,1\n',
'set xlabel "residue index"\n',
'set ylabel "amplitude (a.u.)\n',
'set title "%s (r = %.2f)"\n' %(d_apo2holo[pdb_apo]['title'],r,),
'set key out\n',
'f(x) = %s\n' %(sum(l1)/len(l1)),
'plot [%s:][0:]"amplitudes_%s%s.txt" u 1 t "mode %i" w l, "amplitudes_%s%s.txt" u 2 t "mode 7" w l, "amplitudes_%s%s.txt" u 3 t "binding site" ps 1 pt 7, f(x) t "average amplitude"\n' %(
## 'plot [%s:][0:]"amplitudes_%s%s.txt" u 1 t "mode %i" w l, "amplitudes_%s%s.txt" u 2 t "mode 7" w l, "amplitudes_%s%s.txt" u 3 t "binding site" ps 1 pt 7\n' %(
xmin,pdb_apo,pdb_holo,mode_max_contribution+1, pdb_apo,pdb_holo, pdb_apo,pdb_holo,
),
]
fd = open('gnuplot.settings','w')
fd.writelines(lines)
fd.close()
os.system('/usr/bin/gnuplot gnuplot.settings')
s = ''
for i in range(len(l_factors)):
s += '%s %s %s\n' %(i+1, l_factors[i],abs(l_factors[i]),)
fd = open('facs_eigvals_%s%s.txt' %(pdb_apo,pdb_holo,),'w')
fd.write(s)
fd.close()
## s = ''
## for i in range(len(l_factors_perturbed)):
## s += '%s %s %s\n' %(i+1, l_factors_perturbed[i],abs(l_factors_perturbed[i]),)
## fd = open('facs_eigvals_%s%s_perturbed.txt' %(pdb_apo,pdb_holo,),'w')
## fd.write(s)
## fd.close()
return