File size: 7,454 Bytes
d766458
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import animation
from colabdesign.shared.plot import plot_pseudo_3D, pymol_cmap, _np_kabsch
from string import ascii_uppercase, ascii_lowercase
alphabet_list = list(ascii_uppercase+ascii_lowercase)
import numpy as np

def sym_it(coords, center, cyclic_symmetry_axis, reflection_axis=None):

  def rotation_matrix(axis, theta):
      axis = axis / np.linalg.norm(axis)
      a = np.cos(theta / 2)
      b, c, d = -axis * np.sin(theta / 2)
      return np.array([[a*a+b*b-c*c-d*d, 2*(b*c-a*d), 2*(b*d+a*c)],
                      [2*(b*c+a*d), a*a+c*c-b*b-d*d, 2*(c*d-a*b)],
                      [2*(b*d-a*c), 2*(c*d+a*b), a*a+d*d-b*b-c*c]])

  def align_axes(coords, source_axis, target_axis):
      rotation_axis = np.cross(source_axis, target_axis)
      rotation_angle = np.arccos(np.dot(source_axis, target_axis))
      rot_matrix = rotation_matrix(rotation_axis, rotation_angle)
      return np.dot(coords, rot_matrix)

  # Center the coordinates
  coords = coords - center

  # Align cyclic symmetry axis with Z-axis
  z_axis = np.array([0, 0, 1])
  coords = align_axes(coords, cyclic_symmetry_axis, z_axis)

  if reflection_axis is not None:
    # Align reflection axis with X-axis
    x_axis = np.array([1, 0, 0])
    coords = align_axes(coords, reflection_axis, x_axis)
  return coords

def fix_partial_contigs(contigs, parsed_pdb):
  INF = float("inf")

  # get unique chains
  chains = []
  for c, i in parsed_pdb["pdb_idx"]:
    if c not in chains: chains.append(c)

  # get observed positions and chains
  ok = []
  for contig in contigs:
    for x in contig.split("/"):
      if x[0].isalpha:
        C,x = x[0],x[1:]
        S,E = -INF,INF
        if x.startswith("-"):
          E = int(x[1:])
        elif x.endswith("-"):
          S = int(x[:-1])
        elif "-" in x:
          (S,E) = (int(y) for y in x.split("-"))
        elif x.isnumeric():
          S = E = int(x)      
        for c, i in parsed_pdb["pdb_idx"]:
          if c == C and i >= S and i <= E:
            if [c,i] not in ok: ok.append([c,i])

  # define new contigs
  new_contigs = []
  for C in chains:
    new_contig = []
    unseen = []
    seen = []
    for c,i in parsed_pdb["pdb_idx"]:
      if c == C:
        if [c,i] in ok:
          L = len(unseen)
          if L > 0:
            new_contig.append(f"{L}-{L}")
            unseen = []
          seen.append([c,i])
        else:
          L = len(seen)
          if L > 0:
            new_contig.append(f"{seen[0][0]}{seen[0][1]}-{seen[-1][1]}")
            seen = []
          unseen.append([c,i])
    L = len(unseen)
    if L > 0:
      new_contig.append(f"{L}-{L}")
    L = len(seen)
    if L > 0:
      new_contig.append(f"{seen[0][0]}{seen[0][1]}-{seen[-1][1]}")
    new_contigs.append("/".join(new_contig))

  return new_contigs

def fix_contigs(contigs,parsed_pdb):
  def fix_contig(contig):
    INF = float("inf")
    X = contig.split("/")
    Y = []
    for n,x in enumerate(X):
      if x[0].isalpha():
        C,x = x[0],x[1:]
        S,E = -INF,INF
        if x.startswith("-"):
          E = int(x[1:])
        elif x.endswith("-"):
          S = int(x[:-1])
        elif "-" in x:
          (S,E) = (int(y) for y in x.split("-"))
        elif x.isnumeric():
          S = E = int(x)      
        new_x = ""
        c_,i_ = None,0
        for c, i in parsed_pdb["pdb_idx"]:
          if c == C and i >= S and i <= E:
            if c_ is None:
              new_x = f"{c}{i}"
            else:
              if c != c_ or i != i_+1:
                new_x += f"-{i_}/{c}{i}"
            c_,i_ = c,i
        Y.append(new_x + f"-{i_}")
      elif "-" in x:
        # sample length
        s,e = x.split("-")
        m = np.random.randint(int(s),int(e)+1)
        Y.append(f"{m}-{m}")
      elif x.isnumeric() and x != "0":
        Y.append(f"{x}-{x}")
    return "/".join(Y)
  return [fix_contig(x) for x in contigs]

def fix_pdb(pdb_str, contigs):
  def get_range(contig):
    L_init = 1
    R = []
    sub_contigs = [x.split("-") for x in contig.split("/")]
    for n,(a,b) in enumerate(sub_contigs):
      if a[0].isalpha():
        if n > 0:
          pa,pb = sub_contigs[n-1]
          if pa[0].isalpha() and a[0] == pa[0]:
            L_init += int(a[1:]) - int(pb) - 1
        L = int(b)-int(a[1:]) + 1
      else:
        L = int(b)
      R += range(L_init,L_init+L)  
      L_init += L
    return R
  
  contig_ranges = [get_range(x) for x in contigs]
  R,C = [],[]
  for n,r in enumerate(contig_ranges):
    R += r
    C += [alphabet_list[n]] * len(r)
  
  pdb_out = []
  r_, c_,n = None, None, 0 
  for line in pdb_str.split("\n"):
    if line[:4] == "ATOM":
      c = line[21:22]
      r = int(line[22:22+5])
      if r_ is None: r_ = r
      if c_ is None: c_ = c
      if r != r_ or c != c_:
        n += 1
        r_,c_ = r,c
      pdb_out.append("%s%s%4i%s" % (line[:21],C[n],R[n],line[26:]))
    if line[:5] == "MODEL" or line[:3] == "TER" or line[:6] == "ENDMDL":
      pdb_out.append(line)
      r_, c_,n = None, None, 0 
  return "\n".join(pdb_out)

def get_ca(pdb_filename, get_bfact=False):
  xyz = []
  bfact = []
  for line in open(pdb_filename, "r"):
    line = line.rstrip()
    if line[:4] == "ATOM":
      atom = line[12:12+4].strip()
      if atom == "CA":
        x = float(line[30:30+8])
        y = float(line[38:38+8])
        z = float(line[46:46+8])
        xyz.append([x, y, z])
        if get_bfact:
          b_factor = float(line[60:60+6].strip())
          bfact.append(b_factor)
  if get_bfact:
    return np.array(xyz), np.array(bfact)
  else:
    return np.array(xyz)

def get_Ls(contigs):
  Ls = []
  for contig in contigs:
    L = 0
    for n,(a,b) in enumerate(x.split("-") for x in contig.split("/")):
      if a[0].isalpha():
        L += int(b)-int(a[1:]) + 1
      else:
        L += int(b)
    Ls.append(L)
  return Ls

def make_animation(pos, plddt=None, Ls=None, ref=0, line_w=2.0, dpi=100):
  if plddt is None:
    plddt = [None] * len(pos)

  # center inputs
  pos = pos - pos[ref,None].mean(1,keepdims=True)

  # align to best view
  best_view = _np_kabsch(pos[ref], pos[ref], return_v=True, use_jax=False)
  pos = np.asarray([p @ best_view for p in pos])

  fig, (ax1) = plt.subplots(1)
  fig.set_figwidth(5)
  fig.set_figheight(5)
  fig.set_dpi(dpi)

  xy_min = pos[...,:2].min() - 1
  xy_max = pos[...,:2].max() + 1
  z_min = None #pos[...,-1].min() - 1
  z_max = None #pos[...,-1].max() + 1 

  for ax in [ax1]:
    ax.set_xlim(xy_min, xy_max)
    ax.set_ylim(xy_min, xy_max)
    ax.axis(False)

  ims=[]
  for pos_,plddt_ in zip(pos,plddt):
    if plddt_ is None:
      if Ls is None:
        img = plot_pseudo_3D(pos_, ax=ax1, line_w=line_w, zmin=z_min, zmax=z_max)
      else:
        c = np.concatenate([[n]*L for n,L in enumerate(Ls)])
        img = plot_pseudo_3D(pos_, c=c, cmap=pymol_cmap, cmin=0, cmax=39, line_w=line_w, ax=ax1, zmin=z_min, zmax=z_max)
    else:
      img = plot_pseudo_3D(pos_, c=plddt_, cmin=50, cmax=90, line_w=line_w, ax=ax1, zmin=z_min, zmax=z_max)    
    ims.append([img])
    
  ani = animation.ArtistAnimation(fig, ims, blit=True, interval=120)
  plt.close()
  return ani.to_html5_video()