smiles
stringlengths
3
3.54k
[NH3+]C1CC([NH+]2CCN(CC3CC3)CC2)C1
CC(=O)c1cccc(NS(=O)(=O)c2cccc(C(=O)[O-])c2C)c1
C[NH2+]Cc1cnoc1C1CCOC1
CC(CNC(=O)OC(C)(C)C)NOCc1ccccc1
N#CC(=NNc1ccccc1)c1nc(-c2ccc3ccccc3c2)c(N=Nc2ccccc2)s1
Cc1ccc(C(OCCOC(c2ccccc2)c2ccc(C)cc2)c2ccccc2)cc1
COc1cccc2c(C)cc(SCC#N)nc12
CC1(C)C(=O)Nc2cccc(CNc3nc(Nc4ccc(C5CC[NH+](C(C)(C)O)CC5)c5c4OCO5)ncc3Cl)c21
CC1CN(CC(=O)NC2CCCC2)c2ccccc2S1
CCNC(=[NH+]Cc1nccn1Cc1ccccc1)N1CCC(OCC2CCCCO2)CC1
CCOC(=O)CCCCN1CC[NH+](Cc2cc3nc(N4CCOC(c5cccc6[nH]ncc56)C4)ncc3s2)CC1
N#CSCC(=Cc1ccccc1)SC#N
COC1OC(C)C(OCc2ccccc2)C(OCc2ccccc2)C1OC1OC(COC(C)=O)C(OC(C)=O)C(OC(C)=O)C1NC(=O)CCl
C=CCN1C(=O)C(=Cc2ccc(OC(C)CC)c(OC)c2)C(=O)NC1=S
CCCOc1nc(NN)nc(N(CC)C(C)C)n1
CC(C)c1ccc(NC(=O)C(=O)Nc2cc(C(F)(F)F)cc(C(F)(F)F)c2)cc1
Cc1ccc(NC(=O)c2ccc(C)c(NC(=O)C[NH+]3CCC(C(=O)N4CCCC4C(=O)Nc4cc(C(=O)NC5CCCCC5)ccc4Cl)CC3)c2)cc1F
CCCCCC[NH+]1CCC(C(=O)CC)(c2cccc(O)c2)CC1
O=C(C1CCN(c2ccc(Cl)cc2)C1=O)N1CCC(c2nc3ccccc3s2)CC1
O=C1c2cc(N=Nc3c(O)c(C(=O)Nc4ccccc4)cc4ccccc34)ccc2-c2ccc(N=Nc3c(O)c(C(=O)Nc4ccccc4)cc4ccccc34)cc21
CC(C)c1nc(=O)cc(N2CC(C[NH3+])OC(C)(C)C2)[nH]1
COc1ccccc1CN1C(=O)C(Nc2ccccc2OC)=C(c2ccc(C)c(C)c2)C1=O
O=C1NCC[NH+](Cc2cccc(OC3CCCC3)c2)C12CCCC2
CCCCn1c(SCC(=O)NCC(=O)NCC)nc2ccccc2c1=O
Cn1cc(C(=O)N2CCCC2CO)nn1
C[NH+](C)Cc1ccc(S(=O)(=O)Nc2ccc3c(c2)nc(C(C)(C)C)n3CC2CCCCC2)cc1
CCN(CC)C(=O)CNc1nc(C(N)=O)ccc1N
CCC(C(=O)[O-])[NH+]1CC(O)CCC1C
CC(C)Oc1cncc(NCc2c(C(F)(F)F)cnn2C)n1
N#Cc1cc(NCc2cc(F)ccc2Br)ccc1[N+](=O)[O-]
Clc1ccc(-c2nnc(NCc3ccco3)c3ccccc23)cc1
C[NH+](CC(=O)NC(C)(C)C)CC(=O)N1CCCCC1
CCCCC(C)=CC=C(C)[NH3+]
CC(C)c1ncc(-n2ccc(C3CC3)n2)c(CCl)n1
Cc1cc(C)cc(NC(=O)CSC2=NC3(CC[NH+](C)CC3)N=C2c2ccc(F)cc2)c1
CCCCCCCCCCCOc1cscc1C(=O)OC
Cc1ccccc1NC(=O)N(CCc1ccccc1)Cc1ccccn1
Oc1ccc(-c2cncc(C[NH+]3CC=C(c4ccccc4)CC3)c2)cc1
CC(=CCCC[NH3+])c1ccc(C2CCCCC2)cc1
CC(CO)([NH2+]CC(O)COc1cnsn1)c1ccccc1
[NH3+]CCCSCCCF
CC(C)n1c(CNC(=O)c2ccc(Cl)cc2)n[nH]c1=S
COCCOc1ccc(C(=O)[O-])c2ccccc12
CC(C)(C)[Si](C)(C)OC1CC(=O)C2C(c3ccccc3)=NOC12
O=C(NCCSc1ccccc1)c1cc2c(ccc3ccccc32)o1
CCc1nnc(SCc2cccc(C)c2)n1N=Cc1ccc(OC(C)(C)C)cc1
COc1c(C(C)=CC(=O)Nc2ccc(SC)cc2)cc2c(C)coc2c1C
Cc1nc(C(=O)N2CCCC2(C)c2nc3c(C)cccc3n2C)c(-c2cccc(Cl)c2)s1
Cc1ncccc1NC(=O)c1nc2c(s1)CCCN2C(=O)C1CC1
CCn1ccc2ccc(C[NH2+]CC3(COC)CCC3)cc21
CC12Oc3ccc(Oc4ccnc5c4CCC(=O)N5)cc3C1C2NC(=O)c1ccc(C[NH+]2CCCC(O)C2)c(C(F)(F)F)c1
CC(C)(C)CC(=O)N(Cc1ccc(NC(=O)c2ccccc2)cc1)Cc1cccc(C[NH3+])c1
Cc1ccc(N(c2ccc(C)cc2)c2ccc(-c3ccc(CCC(=O)[O-])cc3)cc2)cc1
Cc1ccc(-c2cnc3c(C)cn(CC(=O)N(C)C)c3c2)s1
COc1ccc(C2Sc3cc(Cc4cccs4)ccc3N(CC[NH+](C)C)CC2OC(C)=O)cc1
Cc1ccccc1C(C(=O)NCCC(C)C)N(CC[NH+]1CCOCC1)C(=O)Cn1nnc2ccccc21
NNC(Cc1cccc(F)c1F)c1ccc(Br)cc1Br
CCc1ccc(-c2csc(NC(=O)CSc3nnc(COc4cccc(C)c4)o3)n2)cc1
Cc1ccc(NC(=O)c2ccc(C)c(NC(=O)C(C)[NH+]3CCC(C(=O)NC(C(=O)Nc4ccc(NC(=O)c5ccccc5Cl)c(C)c4)C(C)C)CC3)c2)cc1F
O=C(CN1C(=O)C(=O)N(Cc2ccccc2)C1=O)Nc1ccc(F)cc1F
CC(C)N(C(=O)c1c(C=C(O[Si](C)(C)C)c2ccccc2)ccc2ccccc12)C(C)C
COc1ccc(NC(=O)c2cc(-c3ccccc3F)on2)cc1S(=O)(=O)N1CCOCC1
CCCC1(c2ccccc2Cl)N=C(C[NH3+])OC(CC)C1=O
CC[NH2+]C(Cc1sccc1Br)c1cc(C)ccc1OC
Cc1cc(-c2c(C)nn(-c3nc(C#Cc4ccccc4)c(SC(C)C)s3)c2C(=O)[O-])cc(C)n1
CCCC[Sn](CCCC)(CCCC)c1cccc(COCOC)n1
CCOC(=O)c1ccc(-c2ccc3c(C(N)=O)c(NC(N)=O)[nH]c3c2)cc1
Cc1nn(C(C)C)c(N(C)C(C)(C)CO)c1N
CC(C)COc1ccc(C2=C([NH+]3CCCC(CO)C3)C(=O)N(Cc3ccccc3)C2=O)cc1
CCCN(CC)c1ccc(N)s1
CCCCOc1ccc(-c2[nH]ncc2C(=O)NCc2ccc(OC)cc2OC)cc1
CSc1ccc(-c2ccc3c(c2)C(=O)N2CCN(C(=O)CCC(=O)[O-])CC2C(=O)N3)cc1
CCC1CCN(c2nc3cc(C)ccn3n2)C(C[NH3+])C1
CCCC[NH+](CC)CC(O)c1ccc(C)cc1
NC(=[NH2+])c1ccc(N2CCC(c3ccccc3)C2)nc1
CCOC(=O)c1cn[nH]c1S(=O)(=O)N(C)CC1CC1C
Cc1ccc(S(=O)(=O)NCCCC[NH3+])cc1Br
O=C(NCC1(c2ccccc2)CCC1)C1CCN(C(=O)c2ccco2)CC1
C#CCCCC[n+]1ccc(-c2ccncc2)cc1
O=C(Nc1ccc(SC(F)F)cc1)C1CC(=O)N(c2ccccc2)C1
Cc1ccccc1C(=O)NCCOc1cccc(NC(=O)OC(C)(C)C)c1
CNC(=O)C[NH+]1CCC(NC(NCC(C)Oc2ccccc2)=[NH+]C)CC1
CCCOc1ccc(C[NH+]2CCN(CC)CC2)cc1-c1nc(=O)c2cc3c(cc2[nH]1)ncn3Cc1ccccc1OC
C(=Cc1ccc2cc(N3CCCc4ccccc43)ccc2c1)c1ccc2c(c1)C1(c3ccccc3-c3ccccc31)c1cc(N3CCCc4ccccc43)ccc1-2
Cc1occc1-c1nnc2sc(-c3ccccc3I)nn12
CCC(=O)Nc1ccc(-c2cc3c(o2)CCN(C(=O)c2ccc(C(F)(F)F)cc2)C3)cc1
CC[NH2+]C(c1ccc(C)cc1)C(C)CC
Cc1cc(C)c2sc(N(Cc3ccco3)C(=O)c3ccc(SC(C)C)cc3)nc2c1
COC(=O)c1ccc(NC(C)Cn2ccnc2)c(F)c1F
CN(Cc1ccccc1)C(=O)CCNc1ccccc1Cl
Cc1oncc1C(=O)NCC=CC[NH3+]
COc1cc(CC(=O)[O-])nc(OC(F)(F)F)c1C(F)F
C#CCN(CCc1c[nH]c2[nH]c(N)nc(=O)c12)c1ccc(C(=O)NC(CCC(=O)NC(CCC(=O)NC(CCC(=O)[O-])C(=O)[O-])C(=O)[O-])C(=O)[O-])c(Cl)c1
CCN(C(=O)c1ccc(=O)n(Cc2cccc([N+](=O)[O-])c2)c1)c1ccccc1C
CCNc1ncc(C2=NOC(C(=O)OCC)C2)cn1
CC=CC(=O)N(C)CCOc1ccc(Cl)cc1
CCC1NC(=O)CN(CC(C2CC2)C2CC2)C1=O
Cc1ccc(C(=O)Nc2cc(NC(=O)CNC(=O)C3CC[NH+](C(C)C(=O)Nc4ccc(Cl)c(C(=O)NCC(C)C)c4)CC3)ccc2C)cc1
CSCC(C)[NH2+]Cc1nc(C)c(C)s1
O=C1CCC(C(=O)N2CCCN(C(=O)c3c[nH]c4ccccc34)CC2)=NN1

dataset description

We downloaded PubChem-10m dataset from here and canonicalized it. We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.

from rdkit import Chem
def canonicalize(mol):
    mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
    return mol 

We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.

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Models trained or fine-tuned on sagawa/pubchem-10m-canonicalized