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import numpy as np
import scipy
import scipy.spatial
import string
import os,re
import random
import util
to1letter = {
"ALA":'A', "ARG":'R', "ASN":'N', "ASP":'D', "CYS":'C',
"GLN":'Q', "GLU":'E', "GLY":'G', "HIS":'H', "ILE":'I',
"LEU":'L', "LYS":'K', "MET":'M', "PHE":'F', "PRO":'P',
"SER":'S', "THR":'T', "TRP":'W', "TYR":'Y', "VAL":'V' }
def parse_a3m(filename):
'''read A3M and convert letters into integers in the 0..20 range,
also keep track of insertions
'''
# read A3M file line by line
lab,seq = [],[] # labels and sequences
for line in open(filename, "r"):
if line[0] == '>':
lab.append(line.split()[0][1:])
seq.append("")
else:
seq[-1] += line.rstrip()
# parse sequences
msa,ins = [],[]
table = str.maketrans(dict.fromkeys(string.ascii_lowercase))
nrow,ncol = len(seq),len(seq[0])
for seqi in seq:
# remove lowercase letters and append to MSA
msa.append(seqi.translate(table))
# 0 - match or gap; 1 - insertion
a = np.array([0 if c.isupper() or c=='-' else 1 for c in seqi])
i = np.zeros((ncol))
if np.sum(a) > 0:
# positions of insertions
pos = np.where(a==1)[0]
# shift by occurrence
a = pos - np.arange(pos.shape[0])
# position of insertions in the cleaned sequence
# and their length
pos,num = np.unique(a, return_counts=True)
i[pos[pos<ncol]] = num[pos<ncol]
# append to the matrix of insetions
ins.append(i)
# convert letters into numbers
alphabet = np.array(list("ARNDCQEGHILKMFPSTWYV-"), dtype='|S1').view(np.uint8)
msa = np.array([list(s) for s in msa], dtype='|S1').view(np.uint8)
for i in range(alphabet.shape[0]):
msa[msa == alphabet[i]] = i
# treat all unknown characters as gaps
msa[msa > 20] = 20
ins = np.array(ins, dtype=np.uint8)
return {"msa":msa, "labels":lab, "insertions":ins}
def parse_pdb(filename, **kwargs):
'''extract xyz coords for all heavy atoms'''
lines = open(filename,'r').readlines()
return parse_pdb_lines(lines, **kwargs)
def parse_pdb_lines(lines, parse_hetatom=False, ignore_het_h=True):
# indices of residues observed in the structure
res = [(l[22:26],l[17:20]) for l in lines if l[:4]=="ATOM" and l[12:16].strip()=="CA"]
seq = [util.aa2num[r[1]] if r[1] in util.aa2num.keys() else 20 for r in res]
pdb_idx = [( l[21:22].strip(), int(l[22:26].strip()) ) for l in lines if l[:4]=="ATOM" and l[12:16].strip()=="CA"] # chain letter, res num
# 4 BB + up to 10 SC atoms
xyz = np.full((len(res), 27, 3), np.nan, dtype=np.float32)
for l in lines:
if l[:4] != "ATOM":
continue
chain, resNo, atom, aa = l[21:22], int(l[22:26]), ' '+l[12:16].strip().ljust(3), l[17:20]
idx = pdb_idx.index((chain,resNo))
for i_atm, tgtatm in enumerate(util.aa2long[util.aa2num[aa]]):
if tgtatm is not None and tgtatm.strip() == atom.strip(): # ignore whitespace
xyz[idx,i_atm,:] = [float(l[30:38]), float(l[38:46]), float(l[46:54])]
break
# save atom mask
mask = np.logical_not(np.isnan(xyz[...,0]))
xyz[np.isnan(xyz[...,0])] = 0.0
# remove duplicated (chain, resi)
new_idx = []
i_unique = []
for i,idx in enumerate(pdb_idx):
if idx not in new_idx:
new_idx.append(idx)
i_unique.append(i)
pdb_idx = new_idx
xyz = xyz[i_unique]
mask = mask[i_unique]
seq = np.array(seq)[i_unique]
out = {'xyz':xyz, # cartesian coordinates, [Lx14]
'mask':mask, # mask showing which atoms are present in the PDB file, [Lx14]
'idx':np.array([i[1] for i in pdb_idx]), # residue numbers in the PDB file, [L]
'seq':np.array(seq), # amino acid sequence, [L]
'pdb_idx': pdb_idx, # list of (chain letter, residue number) in the pdb file, [L]
}
# heteroatoms (ligands, etc)
if parse_hetatom:
xyz_het, info_het = [], []
for l in lines:
if l[:6]=='HETATM' and not (ignore_het_h and l[77]=='H'):
info_het.append(dict(
idx=int(l[7:11]),
atom_id=l[12:16],
atom_type=l[77],
name=l[16:20]
))
xyz_het.append([float(l[30:38]), float(l[38:46]), float(l[46:54])])
out['xyz_het'] = np.array(xyz_het)
out['info_het'] = info_het
return out
def parse_fasta(filename):
'''
Return dict of name: seq
'''
out = {}
with open(filename, 'r') as f_in:
while True:
name = f_in.readline().strip()[1:]
seq = f_in.readline().strip()
if not name: break
out[name] = seq
return out
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