forked from RosettaCommons/RFdiffusion
-
Notifications
You must be signed in to change notification settings - Fork 7
/
Copy pathcontigs.py
397 lines (380 loc) · 16 KB
/
contigs.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
import sys
import numpy as np
import random
from icecream import ic
class ContigMap:
"""
Class for doing mapping.
Inherited from Inpainting. To update at some point.
Supports multichain or multiple crops from a single receptor chain.
Also supports indexing jump (+200) or not, based on contig input.
Default chain outputs are inpainted chains as A (and B, C etc if multiple chains), and all fragments of receptor chain on the next one (generally B)
Output chains can be specified. Sequence must be the same number of elements as in contig string
"""
def __init__(
self,
parsed_pdb,
contigs=None,
inpaint_seq=None,
inpaint_str=None,
length=None,
ref_idx=None,
hal_idx=None,
idx_rf=None,
inpaint_seq_tensor=None,
inpaint_str_tensor=None,
topo=False,
provide_seq=None,
):
# sanity checks
if contigs is None and ref_idx is None:
sys.exit("Must either specify a contig string or precise mapping")
if idx_rf is not None or hal_idx is not None or ref_idx is not None:
if idx_rf is None or hal_idx is None or ref_idx is None:
sys.exit(
"If you're specifying specific contig mappings, the reference and output positions must be specified, AND the indexing for RoseTTAFold (idx_rf)"
)
self.chain_order = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
if length is not None:
if "-" not in length:
self.length = [int(length), int(length) + 1]
else:
self.length = [int(length.split("-")[0]), int(length.split("-")[1]) + 1]
else:
self.length = None
self.ref_idx = ref_idx
self.hal_idx = hal_idx
self.idx_rf = idx_rf
self.inpaint_seq = (
"/".join(inpaint_seq).split("/") if inpaint_seq is not None else None
)
self.inpaint_str = (
"/".join(inpaint_str).split("/") if inpaint_str is not None else None
)
self.inpaint_seq_tensor = inpaint_seq_tensor
self.inpaint_str_tensor = inpaint_str_tensor
self.parsed_pdb = parsed_pdb
self.topo = topo
if ref_idx is None:
# using default contig generation, which outputs in rosetta-like format
self.contigs = contigs
(
self.sampled_mask,
self.contig_length,
self.n_inpaint_chains,
) = self.get_sampled_mask()
self.receptor_chain = self.chain_order[self.n_inpaint_chains]
(
self.receptor,
self.receptor_hal,
self.receptor_rf,
self.inpaint,
self.inpaint_hal,
self.inpaint_rf,
) = self.expand_sampled_mask()
self.ref = self.inpaint + self.receptor
self.hal = self.inpaint_hal + self.receptor_hal
self.rf = self.inpaint_rf + self.receptor_rf
else:
# specifying precise mappings
self.ref = ref_idx
self.hal = hal_idx
self.rf = rf_idx
self.mask_1d = [False if i == ("_", "_") else True for i in self.ref]
# take care of sequence and structure masking
if self.inpaint_seq_tensor is None:
if self.inpaint_seq is not None:
self.inpaint_seq = self.get_inpaint_seq_str(self.inpaint_seq)
else:
self.inpaint_seq = np.array(
[True if i != ("_", "_") else False for i in self.ref]
)
else:
self.inpaint_seq = self.inpaint_seq_tensor
if self.inpaint_str_tensor is None:
if self.inpaint_str is not None:
self.inpaint_str = self.get_inpaint_seq_str(self.inpaint_str)
else:
self.inpaint_str = np.array(
[True if i != ("_", "_") else False for i in self.ref]
)
else:
self.inpaint_str = self.inpaint_str_tensor
# get 0-indexed input/output (for trb file)
(
self.ref_idx0,
self.hal_idx0,
self.ref_idx0_inpaint,
self.hal_idx0_inpaint,
self.ref_idx0_receptor,
self.hal_idx0_receptor,
) = self.get_idx0()
self.con_ref_pdb_idx = [i for i in self.ref if i != ("_", "_")]
# Handle provide seq. This is zero-indexed, and used only for partial diffusion
if provide_seq is not None:
for i in provide_seq[0].split(","):
if "-" in i:
self.inpaint_seq[
int(i.split("-")[0]) : int(i.split("-")[1]) + 1
] = True
else:
self.inpaint_seq[int(i)] = True
def get_sampled_mask(self):
"""
Function to get a sampled mask from a contig.
"""
length_compatible = False
count = 0
while length_compatible is False:
inpaint_chains = 0
contig_list = self.contigs[0].strip().split()
sampled_mask = []
sampled_mask_length = 0
# allow receptor chain to be last in contig string
if all([i[0].isalpha() for i in contig_list[-1].split("/")]):
contig_list[-1] = f"{contig_list[-1]}/0"
for con in contig_list:
if (
all([i[0].isalpha() for i in con.split("/")[:-1]])
and con.split("/")[-1] == "0"
) or self.topo is True:
# receptor chain
sampled_mask.append(con)
else:
inpaint_chains += 1
# chain to be inpainted. These are the only chains that count towards the length of the contig
subcons = con.split("/")
subcon_out = []
for subcon in subcons:
if subcon[0].isalpha():
subcon_out.append(subcon)
if "-" in subcon:
sampled_mask_length += (
int(subcon.split("-")[1])
- int(subcon.split("-")[0][1:])
+ 1
)
else:
sampled_mask_length += 1
else:
if "-" in subcon:
length_inpaint = random.randint(
int(subcon.split("-")[0]), int(subcon.split("-")[1])
)
subcon_out.append(f"{length_inpaint}-{length_inpaint}")
sampled_mask_length += length_inpaint
elif subcon == "0":
subcon_out.append("0")
else:
length_inpaint = int(subcon)
subcon_out.append(f"{length_inpaint}-{length_inpaint}")
sampled_mask_length += int(subcon)
sampled_mask.append("/".join(subcon_out))
# check length is compatible
if self.length is not None:
if (
sampled_mask_length >= self.length[0]
and sampled_mask_length < self.length[1]
):
length_compatible = True
else:
length_compatible = True
count += 1
if count == 100000: # contig string incompatible with this length
sys.exit("Contig string incompatible with --length range")
return sampled_mask, sampled_mask_length, inpaint_chains
def expand_sampled_mask(self):
chain_order = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
receptor = []
inpaint = []
receptor_hal = []
inpaint_hal = []
receptor_idx = 1
inpaint_idx = 1
inpaint_chain_idx = -1
receptor_chain_break = []
inpaint_chain_break = []
for con in self.sampled_mask:
if (
all([i[0].isalpha() for i in con.split("/")[:-1]])
and con.split("/")[-1] == "0"
) or self.topo is True:
# receptor chain
subcons = con.split("/")[:-1]
assert all(
[i[0] == subcons[0][0] for i in subcons]
), "If specifying fragmented receptor in a single block of the contig string, they MUST derive from the same chain"
assert all(
int(subcons[i].split("-")[0][1:])
< int(subcons[i + 1].split("-")[0][1:])
for i in range(len(subcons) - 1)
), "If specifying multiple fragments from the same chain, pdb indices must be in ascending order!"
for idx, subcon in enumerate(subcons):
ref_to_add = [
(subcon[0], i)
for i in np.arange(
int(subcon.split("-")[0][1:]), int(subcon.split("-")[1]) + 1
)
]
receptor.extend(ref_to_add)
receptor_hal.extend(
[
(self.receptor_chain, i)
for i in np.arange(
receptor_idx, receptor_idx + len(ref_to_add)
)
]
)
receptor_idx += len(ref_to_add)
if idx != len(subcons) - 1:
idx_jump = (
int(subcons[idx + 1].split("-")[0][1:])
- int(subcon.split("-")[1])
- 1
)
receptor_chain_break.append(
(receptor_idx - 1, idx_jump)
) # actual chain break in pdb chain
else:
receptor_chain_break.append(
(receptor_idx - 1, 200)
) # 200 aa chain break
else:
inpaint_chain_idx += 1
for subcon in con.split("/"):
if subcon[0].isalpha():
ref_to_add = [
(subcon[0], i)
for i in np.arange(
int(subcon.split("-")[0][1:]),
int(subcon.split("-")[1]) + 1,
)
]
inpaint.extend(ref_to_add)
inpaint_hal.extend(
[
(chain_order[inpaint_chain_idx], i)
for i in np.arange(
inpaint_idx, inpaint_idx + len(ref_to_add)
)
]
)
inpaint_idx += len(ref_to_add)
else:
inpaint.extend([("_", "_")] * int(subcon.split("-")[0]))
inpaint_hal.extend(
[
(chain_order[inpaint_chain_idx], i)
for i in np.arange(
inpaint_idx, inpaint_idx + int(subcon.split("-")[0])
)
]
)
inpaint_idx += int(subcon.split("-")[0])
inpaint_chain_break.append((inpaint_idx - 1, 200))
if self.topo is True or inpaint_hal == []:
receptor_hal = [(i[0], i[1]) for i in receptor_hal]
else:
receptor_hal = [
(i[0], i[1] + inpaint_hal[-1][1]) for i in receptor_hal
] # rosetta-like numbering
# get rf indexes, with chain breaks
inpaint_rf = np.arange(0, len(inpaint))
receptor_rf = np.arange(len(inpaint) + 200, len(inpaint) + len(receptor) + 200)
for ch_break in inpaint_chain_break[:-1]:
receptor_rf[:] += 200
inpaint_rf[ch_break[0] :] += ch_break[1]
for ch_break in receptor_chain_break[:-1]:
receptor_rf[ch_break[0] :] += ch_break[1]
return (
receptor,
receptor_hal,
receptor_rf.tolist(),
inpaint,
inpaint_hal,
inpaint_rf.tolist(),
)
def get_inpaint_seq_str(self, inpaint_s):
"""
function to generate inpaint_str or inpaint_seq masks specific to this contig
"""
s_mask = np.copy(self.mask_1d)
inpaint_s_list = []
for i in inpaint_s:
if "-" in i:
inpaint_s_list.extend(
[
(i[0], p)
for p in range(
int(i.split("-")[0][1:]), int(i.split("-")[1]) + 1
)
]
)
else:
inpaint_s_list.append((i[0], int(i[1:])))
for res in inpaint_s_list:
if res in self.ref:
s_mask[self.ref.index(res)] = False # mask this residue
return np.array(s_mask)
def get_idx0(self):
ref_idx0 = []
hal_idx0 = []
ref_idx0_inpaint = []
hal_idx0_inpaint = []
ref_idx0_receptor = []
hal_idx0_receptor = []
for idx, val in enumerate(self.ref):
if val != ("_", "_"):
assert val in self.parsed_pdb["pdb_idx"], f"{val} is not in pdb file!"
hal_idx0.append(idx)
ref_idx0.append(self.parsed_pdb["pdb_idx"].index(val))
for idx, val in enumerate(self.inpaint):
if val != ("_", "_"):
hal_idx0_inpaint.append(idx)
ref_idx0_inpaint.append(self.parsed_pdb["pdb_idx"].index(val))
for idx, val in enumerate(self.receptor):
if val != ("_", "_"):
hal_idx0_receptor.append(idx)
ref_idx0_receptor.append(self.parsed_pdb["pdb_idx"].index(val))
return (
ref_idx0,
hal_idx0,
ref_idx0_inpaint,
hal_idx0_inpaint,
ref_idx0_receptor,
hal_idx0_receptor,
)
def get_mappings(self):
mappings = {}
mappings["con_ref_pdb_idx"] = [i for i in self.inpaint if i != ("_", "_")]
mappings["con_hal_pdb_idx"] = [
self.inpaint_hal[i]
for i in range(len(self.inpaint_hal))
if self.inpaint[i] != ("_", "_")
]
mappings["con_ref_idx0"] = np.array(self.ref_idx0_inpaint)
mappings["con_hal_idx0"] = np.array(self.hal_idx0_inpaint)
if self.inpaint != self.ref:
mappings["complex_con_ref_pdb_idx"] = [
i for i in self.ref if i != ("_", "_")
]
mappings["complex_con_hal_pdb_idx"] = [
self.hal[i] for i in range(len(self.hal)) if self.ref[i] != ("_", "_")
]
mappings["receptor_con_ref_pdb_idx"] = [
i for i in self.receptor if i != ("_", "_")
]
mappings["receptor_con_hal_pdb_idx"] = [
self.receptor_hal[i]
for i in range(len(self.receptor_hal))
if self.receptor[i] != ("_", "_")
]
mappings["complex_con_ref_idx0"] = np.array(self.ref_idx0)
mappings["complex_con_hal_idx0"] = np.array(self.hal_idx0)
mappings["receptor_con_ref_idx0"] = np.array(self.ref_idx0_receptor)
mappings["receptor_con_hal_idx0"] = np.array(self.hal_idx0_receptor)
mappings["inpaint_str"] = self.inpaint_str
mappings["inpaint_seq"] = self.inpaint_seq
mappings["sampled_mask"] = self.sampled_mask
mappings["mask_1d"] = self.mask_1d
return mappings