484 lines
322 KiB
Plaintext
Executable File
484 lines
322 KiB
Plaintext
Executable File
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"SMILES is valid.\n"
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]
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},
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{
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"data": {
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",
|
||
"text/plain": [
|
||
"<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x800>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from rdkit import Chem\n",
|
||
"from rdkit.Chem import Draw\n",
|
||
"\n",
|
||
"# smiles = \"O[C@H]1[C]([C@H]([C@H](OC[14C@@H]2[C@@H](CC)OC(C[C@H]([C@H](C)[14C@H]([C@@H](CC=O)C[C@@H](C)C(/C=C/C(/C)=C/2)=O)O[C@H]2[C@@H]([C@H]([C@@H]([C@@H](C)O2)O[C@H]2C[C@](C)([C@@H]([C@@H](C)O2)O)O)[N@](C)C)O)O)=O)O[C@@H]1C)OC)OC\"\n",
|
||
"smiles = '[14*]C1/C=C(/C=C/C(C(CC(CC=O)C(C(C(CC(OC1CC)=O)O)C)[14*])C)=O)\\C'\n",
|
||
"\n",
|
||
"try:\n",
|
||
" molecule = Chem.MolFromSmiles(smiles)\n",
|
||
" if molecule is not None:\n",
|
||
" print(\"SMILES is valid.\")\n",
|
||
" img = Draw.MolToImage(molecule, size=(800, 800))\n",
|
||
" img.show()\n",
|
||
" else:\n",
|
||
" print(\"SMILES is invalid.\")\n",
|
||
"except Exception as e:\n",
|
||
" print(f\"Error while processing SMILES: {e}\")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 设计一套规则，当检测到替换位点时，仅允许替换那些已经被验证不会破坏整体语法的 SELFIES 片段。这种方法要求事先建立一套拼接规则，确保新片段与母核之间的连接能正确生成有效的 SELFIES（SMILES）。\n",
|
||
"# SELFIES：由于每个符号本身已经内嵌了语法信息，局部替换后整体字符串通常仍是合法的。这使得设计拼接规则时可以“局部修改”而不必担心整体语法崩溃。\n",
|
||
"# SMILES：需要手动管理括号、环号等，这要求拼接规则更加严格和复杂，替换片段必须与母核的相应位置在化学键连接上完全匹配，否则容易导致不合法的 SMILES。\n",
|
||
"# 对于 SELFIES：可以提前验证候选替换片段在不同连接情境下的合法性，然后通过预定义的模板或规则进行替换。\n",
|
||
"# 对于 SMILES：建议采用基于化学反应规则或者借助成熟的化学工具（例如 RDKit 中的反应 SMARTS），在化学上预定义连接点和反应规则来实现拼接，而不是直接字符串拼接。这样不仅能确保语法正确，也更符合化学实际。"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[I][=N-1][S][N][F][=N][=P][=Ring3][#B] I[N-1]SNF\n",
|
||
"selfies:[I][=N-1][S][N][F][=N][=P][=Ring3][#B],smiles:I[N-1]SNF\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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2bOAdiJNvv2UXXCD8HC64gH37Le9A/ERFjfpVVrIFC5hczohYWhpbt455vbwzhYvLxQoLWXw8I2IqFVu0iEXTnquQ+PxzdtZZQolcdhk7cIB3oDCyWFh2NvPvLDaZ2IYNzOfjnYmrKKpRv9272cUXC6/+885jO3fyDhR627axCROEpzx9Oisq4h1osPC/pU1KCrylranhnSnE2ttZbi6LiWFETKfDtKQg6mqUMebzsU2b2LBhgemC48d5ZwqNw4fZtdcKBTpuHPvwQ96BBqPGRpaTw9RqRsQSE1l+Puvo4J0pBPy/NcOHB6YZButvzQBEY436+f+u+qcLdLrBNl0QJb/bkWNw/8Xas4dNnRqYltyxg3egCBO9NepXXh6YLhgce3mi8J1m5Bh8+0+sVrZggTAt6Z9RwLTkL0V7jfp98QWbNEl49U+bxvbv5x1ooKJ53iNCDJrZPP8T8R/f4n8i0Xl8S1+gRgX+jbjkZKluxHXdrI7mo3AihNSPLduyhY0eHdgNWlbGO1BkQ43+TFMTy8kRzsdISGD5+RI4HwPHhEcsKZ7p8OOP7JprAuf+ffQR70BSgBrtRkkJmzVLeCWNHcu2buUdqAf+yVOzGWcoRjSpnHfrvxKFUilMS+JKFH2HGu3Rtm3sjDMC0wWHDvEO9HPffccuvFCIN3ky+/pr3oGgZ3Z7RF8Fxu1m69YJ05JKJVuwgNXW8s4kKYPtQnnB5XbTiy9Sbi61tJBKRQsXUl4eJST0tkplJX3zTeDmr35FyX34FPS9e+noUWE8Ywb1foFwh4Pmz6c33xQubffkk3Tzzbh6mwQM4JqE33xDlZXCOCaGZvXto0s3byavl4goMZGmTz/Nwp99RkuX0g8/EBFdfjkVFtKZg/ADt0KMd49LQNfpAv9l93qZLnj3XWEL0f9v3rw+PcSCBYFViotPv/xVVwkXB2ht7euzgAjx3/+y//kf4f96yhS2a1dvC8+Z87OX0/vv9+khdLrAeXq9KC1l8+YJS2Zmsk2b+vEsoCvUaF/t28cuvVR4zZ19Nvvyy+4XO6VGifq0a7W/NVpaGrm72OC0TrnsXnY2q6rqfslTatRs7tPegNPWqH9a0j+V6p+WjPyp1Eg2CD4jOkzOOYe++oq2bKGRI2n/fpo2jWbPpmPHTr/i3XdTe3uQw2Rm0ogRQb5PCBuZjG65hcrKKDeX1Gp64w3KzKRVq6ij4zQrWiyUlyfqoRmj11+nzEzKyyOXi7KzqayMVq2iwfVJneGGGu2f2bOpqIjy8ykujj74gLKyaPFiamvrbZUTJ+iJJ8KVD6QjNpZWraJDh2jePGpvp7w8mjiR3n77NGsVFtL+/QN8xO++o4suoltvpepqmjKFvvmGXn+dUqPxQwuDDFNMA1RRQTk59NZbxBiZTPThh3TWWUREmzfT3LnCMrGxwnaoWk3ff08TJvR4b3fcQevXC+PiYho/PvCtp56iAwe6X0uppNdeE/tEIBL85z+0dCkVFxMRzZxJW7cKU09z59LmzcIynS+nCy+knTtJ3vMmUGws2e1EROedR3v2CF9cuJDWrSPGyGymNWvoppswLRk8vPcqSJv/qCOzmbW3C1/pum/0oYeEo/CI2NSpvZ2t38u+0auvPnVna+c/lSqETw3CrPOoo2XLAl/sum/04YcD45df7u2uut03WlAQicdaDQ5K3jUubZMn086dVF5OOl033x03jm69lV55hYho50567TW6/fZ+P8Ttt9Oll3b/rUH9mbVRR6mkBQto7lxS9vBLuWIFrV9PNTVERDk5dN11lJbWj/u/6y6aO5fM5iBEhVOgRsWSy3ub7cnLo3/+U3gvtmIFzZ7d7097/s1vxKQDiTEae/yWXk8PP0x3301E1NJCy5fTxo39uGeVCh0aKphiCq2MDFq5UhjX11NODtc0IHF33insgieif/yDPvuMaxo4CTUacsuX05gxwvjVV+mLL7imASlTKKigIHBz4UJyOvmlgZNQoyGn0dCTTwpjxuiee8jl4hoIpOzyy2nOHGFcWhp4aQFHqNFwuOGGwKnNRUX09NNc04DErV1LMTHCOD+fSku5pgHUaNi8+GLgRJFHHw1ciASgv0aODOxwdzpp/nzCwd98oUbDZMwYWrZMGDscdNddXNOAxK1cSePGCeOvvqK33uKaJuqhRsPnoYdo+HBh/Mkn9O67XNOAlKnV9OyzgZvLllFzM780UQ81Gj46HRUWBm4uXSqcsQcwADNm0I03CuOaGlq9mmua6IYaDavrrw9ceddiobVruaYBiSsoIL1eGD/3HBUVcU0TxVCj4fb88xQbK4zz86m8nGsakDKTiXJzhbHHQ0uXck0TxVCj4TZ8eOBcJoeD7r+faxqQuMWLaeJEYbxtG338Mdc00Qo1ykFOTmCa9a23aNcurmlAylQqeumlwCXvli0jj4droKiEGuVArabnnhPGjNHKlTjuDwZu6lTKzhbGhw/Tq69yTROVUKN8XHklzZsnjLdvp23buKYBiVuzJvCBtatWYYM03FCj3Dz7bOCDlI8f55kEpC4lhR57TBhbrbhoQ7ihRrlJS6OHH+YdAgaLhQtpyhTeIaIVapSnJUto0iTeIWBQkMvphRfwgQh8oEZ5Uirp+efxyWIQHOefT3/8I+8QUQk1ylnXaVYAkf78Z0pO5h0i+qBG+XvqKUpM5B0CBoXERMrP5x0i+uBz6gEARMHWKACAKPiAZYDIdeiQMNBqKTOzr2uVl1NrqzAeO5bU6uAHg67wph4gQrndgQY880w6eLCvK86eTR98IIxLS/vRvzAweFMPACAKahQAQBTUKACAKKhRAABRUKMAAKKgRgEAREGNAgCIghoFABAFNQoAIApqFABAFJxTDyABLhcdPdrXhe32UEaBX0CNAkhASQmNHs07BPQAb+oBAERBjQIAiII39QASMGEC7djR14Vvvpn+/e9QpoGfQ40CSIBCQUOG9HVhlSqUUeAX8KYeAEAU1CgAgCioUQAAUVCjAACioEYBAERBjQIAiIIaBQAQBTUKACAKahQAQBTUKACAKKhRAABRZIwx3hkAoHs//SQMNBoaPryva1mtZLMJ45EjcYp9yKFGAQBEwZt6AABRUKMAAKKgRgEAREGNAgCIghoFABAFNQoAIApqFABAFNQoAIAoqFEAAFFQowAAoqBGAQBEQY0CAIiCGgUAEAU1CgAgCmoUAECU/wdiD61E+BtmlQAAAIV6VFh0cmRraXRQS0wgcmRraXQgMjAyNC4wOS4zAAB4nHu/b+09BiAQAGImBghgBWIWIG5gNGVQANKM7ApKQOo/kwCYy8TOkACiGDkhstwMjAyMTAxMzAzMLAxOIAPE3UDiDDDjHrqpHZg1c6YdiPPQbdn+tLRn+2CSSOL2MHGgegeYuBgAOccaQSWnVosAAADMelRYdE1PTCByZGtpdCAyMDI0LjA5LjMAAHicjVBLDoIwEN33FO8CNNOf0oULoIjEUBJB7+De+8c2WgsmEmc6yXzevMwrQ7SLO98f+Jh0jAG08ay1uCkiYgNigrrteo9mrurUacarnycY6LARfI2s5nFIHYEeheTGlrTfgXjkpbDB6Z0koIRHIbi0llSJgrg2X0g0p+5QiLSgMC2Gv4l1IN7kTUCDI/65tPVuJfEluh69y6KjyywtFFD5cBFC5/tECLNkX3LFOn19yNkTuuJZL40zst8AAABSelRYdFNNSUxFUyByZGtpdCAyMDI0LjA5LjMAAHicc/MLjvbTjfVUqNEw0jO1tDCw0DHQM9axNtQzsrQ0MNHRNdAzMdWxNoCI6qIJ6yLr0awBAJOrEECMxvXLAAAAAElFTkSuQmCC",
|
||
"text/plain": [
|
||
"<rdkit.Chem.rdchem.Mol at 0x7f2c4af96570>"
|
||
]
|
||
},
|
||
"execution_count": 37,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import selfies as sf\n",
|
||
"import random\n",
|
||
"from rdkit import Chem\n",
|
||
"from rdkit.Chem import Draw\n",
|
||
"\n",
|
||
"alphabet=sf.get_semantic_robust_alphabet() # Gets the alphabet of robust symbols\n",
|
||
"rnd_selfies=''.join(random.sample(list(alphabet), 9))\n",
|
||
"rnd_smiles=sf.decoder(rnd_selfies)\n",
|
||
"print(rnd_selfies,rnd_smiles)\n",
|
||
"print(f'selfies:{rnd_selfies},smiles:{rnd_smiles}')\n",
|
||
"molecule = Chem.MolFromSmiles(rnd_smiles)\n",
|
||
"molecule"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 40,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'[H]', '[#C-1]', '[=Ring2]', '[=Branch1]', '[=B-1]', '[P-1]', '[S+1]', '[#P]', '[=Branch2]', '[Br]', '[#O+1]', '[=Branch3]', '[O+1]', '[=S]', '[#Branch1]', '[=P-1]', '[#B]', '[C+1]', '[=S+1]', '[=N+1]', '[=P+1]', '[N+1]', '[Cl]', '[=N]', '[#N]', '[#C]', '[#Branch2]', '[=B]', '[=S-1]', '[C]', '[P+1]', '[N]', '[C-1]', '[P]', '[Ring1]', '[=C+1]', '[=B+1]', '[Ring2]', '[B-1]', '[S-1]', '[O]', '[Branch1]', '[Ring3]', '[N-1]', '[=O+1]', '[=Ring3]', '[=P]', '[=N-1]', '[#S-1]', '[#C+1]', '[#S+1]', '[B+1]', '[S]', '[#Branch3]', '[=C]', '[#B-1]', '[Branch3]', '[=C-1]', '[Branch2]', '[B]', '[F]', '[#P+1]', '[#S]', '[#N+1]', '[#P-1]', '[I]', '[O-1]', '[=O]', '[=Ring1]'}\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"len(alphabet)\n",
|
||
"print(alphabet)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import selfies as sf\n",
|
||
"smiles = '[14*]C1/C=C(/C=C/C(C(CC(CC=O)C(C(C(CC(OC1CC)=O)O)C)[14*])C)=O)\\C'\n",
|
||
"benzene = smiles\n",
|
||
"\n",
|
||
"try:\n",
|
||
" benzene_sf = sf.encoder(benzene) # [C][=C][C][=C][C][=C][Ring1][=Branch1]\n",
|
||
" benzene_smi = sf.decoder(benzene_sf) # C1=CC=CC=C1\n",
|
||
"except sf.EncoderError:\n",
|
||
" pass # sf.encoder error!\n",
|
||
"except sf.DecoderError:\n",
|
||
" pass # sf.decoder error!\n",
|
||
"\n",
|
||
"len_benzene = sf.len_selfies(benzene_sf) # 8\n",
|
||
"\n",
|
||
"symbols_benzene = list(sf.split_selfies(benzene_sf))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"'[O][C@H1][CH0][Branch2][=Branch2][Branch1][C@H1][Branch2][Branch2][#C][C@H1][Branch2][Branch2][Branch1][O][C][14C@@H1][C@@H1][Branch1][Ring1][C][C][O][C][Branch2][#Branch1][#Branch1][C][C@H1][Branch2][=Branch1][P][C@H1][Branch1][C][C][14C@H1][Branch2][Ring1][#Branch2][C@@H1][Branch1][Ring2][C][C][=O][C][C@@H1][Branch1][C][C][C][Branch1][O][/C][=C][/C][Branch1][C][/C][=C][-/Ring2][Ring1][Branch2][=O][O][C@H1][C@@H1][Branch2][Ring2][=Branch2][C@H1][Branch2][Ring1][S][C@@H1][Branch1][Branch2][C@@H1][Branch1][C][C][O][Ring1][#Branch1][O][C@H1][C][C@][Branch1][C][C][Branch1][N][C@@H1][Branch1][Branch2][C@@H1][Branch1][C][C][O][Ring1][Branch2][O][O][N@][Branch1][C][C][C][O][O][=O][O][C@@H1][Ring2][Branch1][#Branch2][C][O][C][O][C]'"
|
||
]
|
||
},
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"benzene_sf"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<rdkit.Chem.rdchem.Mol at 0x7fc1bb199540>"
|
||
]
|
||
},
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"molecule\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 100,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"SMILES is valid.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/jpeg": 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",
|
||
"text/plain": [
|
||
"<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x800>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"new_smiles = '[17O][13C@H]1[13C]([13C@H]([13C@H]([17O][13C][14C@@H]2[C@@H](CC)OC(C[C@H]([C@H](C)[14C@H]([C@@H](CC=O)C[C@@H](C)[13C](/C=C/C(/C)=C/2)=O)[18O][13C@H]2[C@@H]([C@H]([C@@H]([C@@H](C)[18O]2)[19O][C@H]2C[C@](C)([C@@H]([C@@H](C)O2)O)O)[N@](C)C)O)O)=O)O[16C@@H]1[16C])OC)[20C]'\n",
|
||
"# [17O][13C@H]1[13C]([13C@H]([13C@H]([17O][13C][14C@@H]2[C@@H][*]OC(C[C@H]([C@H](C)[14C@H]([C@@H](CC=O)C[C@@H](C)C(/C=C/C(/C)=C/2)=O)O[C@H]2[C@@H]([C@H]([C@@H]([C@@H](C)O2)O[C@H]2C[C@](C)([C@@H]([C@@H](C)O2)O)O)[N@](C)C)O)O)=O)O[C@@H]1C)OC)C\n",
|
||
"\n",
|
||
"try:\n",
|
||
" molecule = Chem.MolFromSmiles(new_smiles)\n",
|
||
" if molecule is not None:\n",
|
||
" print(\"SMILES is valid.\")\n",
|
||
" img = Draw.MolToImage(molecule, size=(800, 800))\n",
|
||
" img.show()\n",
|
||
" else:\n",
|
||
" print(\"SMILES is invalid.\")\n",
|
||
"except Exception as e:\n",
|
||
" print(f\"Error while processing SMILES: {e}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 119,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"SMILES is valid.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/jpeg": 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",
|
||
"text/plain": [
|
||
"<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x800>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"new_smiles = 'F[13C@@H]1[C@@H](CC)OC(C[C@H]([C@H](C)[13C@@H](F)[C@@H](CC=O)C[C@@H](C)C(/C=C/C(/C)=C/1)=O)O)=O'\n",
|
||
"\n",
|
||
"try:\n",
|
||
" molecule = Chem.MolFromSmiles(new_smiles)\n",
|
||
" if molecule is not None:\n",
|
||
" print(\"SMILES is valid.\")\n",
|
||
" img = Draw.MolToImage(molecule, size=(800, 800))\n",
|
||
" img.show()\n",
|
||
" else:\n",
|
||
" print(\"SMILES is invalid.\")\n",
|
||
"except Exception as e:\n",
|
||
" print(f\"Error while processing SMILES: {e}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"core_selfies = '[O][C@H1][CH0][Branch2][=Branch2][Branch1][C@H1][Branch2][Branch2][#C][C@H1][Branch2][Branch2][Branch1][O][C][14C@@H1][C@@H1][Branch1][Ring1][C][C][O][C][Branch2][#Branch1][#Branch1][C][C@H1][Branch2][=Branch1][P][C@H1][Branch1][C][C][14C@H1][Branch2][Ring1][#Branch2][C@@H1][Branch1][Ring2][C][C][=O][C][C@@H1][Branch1][C][C][C][Branch1][O][/C][=C][/C][Branch1][C][/C][=C][-/Ring2][Ring1][Branch2][=O][O][C@H1][C@@H1][Branch2][Ring2][=Branch2][C@H1][Branch2][Ring1][S][C@@H1][Branch1][Branch2][C@@H1][Branch1][C][C][O][Ring1][#Branch1][O][C@H1][C][C@][Branch1][C][C][Branch1][N][C@@H1][Branch1][Branch2][C@@H1][Branch1][C][C][O][Ring1][Branch2][O][O][N@][Branch1][C][C][C][O][O][=O][O][C@@H1][Ring2][Branch1][#Branch2][C][O][C][O][C]'\n",
|
||
"\n",
|
||
"\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'H': 1,\n",
|
||
" 'F': 1,\n",
|
||
" 'Cl': 1,\n",
|
||
" 'Br': 1,\n",
|
||
" 'I': 1,\n",
|
||
" 'B': 3,\n",
|
||
" 'B+1': 2,\n",
|
||
" 'B-1': 4,\n",
|
||
" 'O': 2,\n",
|
||
" 'O+1': 3,\n",
|
||
" 'O-1': 1,\n",
|
||
" 'N': 3,\n",
|
||
" 'N+1': 4,\n",
|
||
" 'N-1': 2,\n",
|
||
" 'C': 4,\n",
|
||
" 'C+1': 5,\n",
|
||
" 'C-1': 3,\n",
|
||
" 'P': 5,\n",
|
||
" 'P+1': 6,\n",
|
||
" 'P-1': 4,\n",
|
||
" 'S': 6,\n",
|
||
" 'S+1': 7,\n",
|
||
" 'S-1': 5,\n",
|
||
" '?': 8}"
|
||
]
|
||
},
|
||
"execution_count": 48,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import selfies as sf\n",
|
||
"sf.get_preset_constraints('default')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "AttributeError",
|
||
"evalue": "module 'selfies' has no attribute 'customize_symbols'",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
|
||
"Cell \u001b[0;32mIn[46], line 6\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrdkit\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Chem\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# 配置自定义符号\u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m \u001b[43msf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcustomize_symbols\u001b[49m(\n\u001b[1;32m 7\u001b[0m additions\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[14*]\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m 8\u001b[0m constraints\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[14*]\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m2\u001b[39m} \u001b[38;5;66;03m# 假设需要形成两个键\u001b[39;00m\n\u001b[1;32m 9\u001b[0m )\n\u001b[1;32m 11\u001b[0m \u001b[38;5;66;03m# 定义母核结构（示例）\u001b[39;00m\n\u001b[1;32m 12\u001b[0m core_selfies \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 13\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[C][C@@H1][Branch1][Ring1][14*][O][C(=O)O][Ring2][14*]\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 14\u001b[0m )\n",
|
||
"\u001b[0;31mAttributeError\u001b[0m: module 'selfies' has no attribute 'customize_symbols'"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import selfies as sf\n",
|
||
"import random\n",
|
||
"from rdkit import Chem\n",
|
||
"\n",
|
||
"# 配置自定义符号\n",
|
||
"sf.customize_symbols(\n",
|
||
" additions=[\"[14*]\"],\n",
|
||
" constraints={\"[14*]\": 2} # 假设需要形成两个键\n",
|
||
")\n",
|
||
"\n",
|
||
"# 定义母核结构（示例）\n",
|
||
"core_selfies = (\n",
|
||
" \"[C][C@@H1][Branch1][Ring1][14*][O][C(=O)O][Ring2][14*]\"\n",
|
||
")\n",
|
||
"\n",
|
||
"# 生成侧链\n",
|
||
"def generate_valid_side_chain():\n",
|
||
" chains = [\n",
|
||
" \"[Cl]\", \n",
|
||
" \"[Branch1][O][C][H]\", \n",
|
||
" \"[Branch1][N][C][H]\",\n",
|
||
" \"[Branch1][C][=O][O]\" # -COO\n",
|
||
" ]\n",
|
||
" return random.choice(chains)\n",
|
||
"\n",
|
||
"# 定位替换位点\n",
|
||
"core_symbols = list(sf.split_selfies(core_selfies))\n",
|
||
"sub_positions = [i for i, s in enumerate(core_symbols) if s == \"[14*]\"]\n",
|
||
"\n",
|
||
"# 替换并验证\n",
|
||
"modified_symbols = core_symbols.copy()\n",
|
||
"for pos in sub_positions:\n",
|
||
" modified_symbols[pos] = generate_valid_side_chain()\n",
|
||
"\n",
|
||
"new_selfies = \"\".join(modified_symbols)\n",
|
||
"\n",
|
||
"try:\n",
|
||
" smiles = sf.decoder(new_selfies)\n",
|
||
" mol = Chem.MolFromSmiles(smiles)\n",
|
||
" if mol:\n",
|
||
" print(f\"成功生成分子: {smiles}\")\n",
|
||
" img = Draw.MolToImage(mol)\n",
|
||
" img.show() # 显示分子结构\n",
|
||
" else:\n",
|
||
" print(\"生成SMILES无效\")\n",
|
||
"except Exception as e:\n",
|
||
" print(f\"解码失败: {str(e)}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 49,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "EncoderError",
|
||
"evalue": "failed to parse input\n\tSMILES: [*R*][N@@](C)[*R*]",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mSMILESParserError\u001b[0m Traceback (most recent call last)",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/encoder.py:65\u001b[0m, in \u001b[0;36mencoder\u001b[0;34m(smiles, strict, attribute)\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 65\u001b[0m mol \u001b[38;5;241m=\u001b[39m \u001b[43msmiles_to_mol\u001b[49m\u001b[43m(\u001b[49m\u001b[43msmiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattributable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattribute\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SMILESParserError \u001b[38;5;28;01mas\u001b[39;00m err:\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/utils/smiles_utils.py:217\u001b[0m, in \u001b[0;36msmiles_to_mol\u001b[0;34m(smiles, attributable)\u001b[0m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m tokens:\n\u001b[0;32m--> 217\u001b[0m i \u001b[38;5;241m=\u001b[39m \u001b[43m_derive_mol_from_tokens\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmol\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msmiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtokens\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 218\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m mol\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/utils/smiles_utils.py:242\u001b[0m, in \u001b[0;36m_derive_mol_from_tokens\u001b[0;34m(mol, smiles, tokens, i)\u001b[0m\n\u001b[1;32m 241\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minvalid atom symbol \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(symbol)\n\u001b[0;32m--> 242\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m SMILESParserError(smiles, err_msg, tok\u001b[38;5;241m.\u001b[39mstart_idx)\n\u001b[1;32m 244\u001b[0m curr, i \u001b[38;5;241m=\u001b[39m _attach_atom(mol, bond_char, curr, prev_atom, i, tok)\n",
|
||
"\u001b[0;31mSMILESParserError\u001b[0m: \n\tSMILES: [*R*][N@@](C)[*R*]\n\t ^\n\tIndex: 0\n\tReason: invalid atom symbol '[*R*]'",
|
||
"\nThe above exception was the direct cause of the following exception:\n",
|
||
"\u001b[0;31mEncoderError\u001b[0m Traceback (most recent call last)",
|
||
"Cell \u001b[0;32mIn[49], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m new_smiles \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m[*R*][N@@](C)[*R*]\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m----> 2\u001b[0m \u001b[43msf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoder\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnew_smiles\u001b[49m\u001b[43m)\u001b[49m\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/encoder.py:68\u001b[0m, in \u001b[0;36mencoder\u001b[0;34m(smiles, strict, attribute)\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SMILESParserError \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m 67\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfailed to parse input\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124mSMILES: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(smiles)\n\u001b[0;32m---> 68\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m EncoderError(err_msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m mol\u001b[38;5;241m.\u001b[39mkekulize():\n\u001b[1;32m 71\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkekulization failed\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124mSMILES: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(smiles)\n",
|
||
"\u001b[0;31mEncoderError\u001b[0m: failed to parse input\n\tSMILES: [*R*][N@@](C)[*R*]"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"new_smiles = '[*R*][N@@](C)[*R*]'\n",
|
||
"sf.encoder(new_smiles)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 50,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "EncoderError",
|
||
"evalue": "failed to parse input\n\tSMILES: CC[C@H]1OC(=O)[*][*sugar*][C@H](C)[*sugar*][*]C[*]C(=O)[*][C@@H](O)[*]1",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mSMILESParserError\u001b[0m Traceback (most recent call last)",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/encoder.py:65\u001b[0m, in \u001b[0;36mencoder\u001b[0;34m(smiles, strict, attribute)\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 65\u001b[0m mol \u001b[38;5;241m=\u001b[39m \u001b[43msmiles_to_mol\u001b[49m\u001b[43m(\u001b[49m\u001b[43msmiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattributable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattribute\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SMILESParserError \u001b[38;5;28;01mas\u001b[39;00m err:\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/utils/smiles_utils.py:217\u001b[0m, in \u001b[0;36msmiles_to_mol\u001b[0;34m(smiles, attributable)\u001b[0m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m tokens:\n\u001b[0;32m--> 217\u001b[0m i \u001b[38;5;241m=\u001b[39m \u001b[43m_derive_mol_from_tokens\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmol\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msmiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtokens\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 218\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m mol\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/utils/smiles_utils.py:242\u001b[0m, in \u001b[0;36m_derive_mol_from_tokens\u001b[0;34m(mol, smiles, tokens, i)\u001b[0m\n\u001b[1;32m 241\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minvalid atom symbol \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(symbol)\n\u001b[0;32m--> 242\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m SMILESParserError(smiles, err_msg, tok\u001b[38;5;241m.\u001b[39mstart_idx)\n\u001b[1;32m 244\u001b[0m curr, i \u001b[38;5;241m=\u001b[39m _attach_atom(mol, bond_char, curr, prev_atom, i, tok)\n",
|
||
"\u001b[0;31mSMILESParserError\u001b[0m: \n\tSMILES: CC[C@H]1OC(=O)[*][*sugar*][C@H](C)[*sugar*][*]C[*]C(=O)[*][C@@H](O)[*]1\n\t ^\n\tIndex: 14\n\tReason: invalid atom symbol '[*]'",
|
||
"\nThe above exception was the direct cause of the following exception:\n",
|
||
"\u001b[0;31mEncoderError\u001b[0m Traceback (most recent call last)",
|
||
"Cell \u001b[0;32mIn[50], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43msf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoder\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mCC[C@H]1OC(=O)[*][*sugar*][C@H](C)[*sugar*][*]C[*]C(=O)[*][C@@H](O)[*]1\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||
"File \u001b[0;32m~/micromamba/envs/frage/lib/python3.10/site-packages/selfies/encoder.py:68\u001b[0m, in \u001b[0;36mencoder\u001b[0;34m(smiles, strict, attribute)\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SMILESParserError \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m 67\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfailed to parse input\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124mSMILES: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(smiles)\n\u001b[0;32m---> 68\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m EncoderError(err_msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m mol\u001b[38;5;241m.\u001b[39mkekulize():\n\u001b[1;32m 71\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkekulization failed\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124mSMILES: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(smiles)\n",
|
||
"\u001b[0;31mEncoderError\u001b[0m: failed to parse input\n\tSMILES: CC[C@H]1OC(=O)[*][*sugar*][C@H](C)[*sugar*][*]C[*]C(=O)[*][C@@H](O)[*]1"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"sf.encoder('CC[C@H]1OC(=O)[*][*sugar*][C@H](C)[*sugar*][*]C[*]C(=O)[*][C@@H](O)[*]1')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "frage",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.10.16"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|