SMILES
stringlengths 15
57
| split
stringclasses 1
value | dataset
stringclasses 1
value | __index_level_0__
int64 0
1.94M
|
|---|---|---|---|
CCCS(=O)c1ccc2[nH]c(=NC(=O)OC)[nH]c2c1
|
train
|
moses
| 0
|
CC(C)(C)C(=O)C(Oc1ccc(Cl)cc1)n1ccnc1
|
train
|
moses
| 1
|
CC1C2CCC(C2)C1CN(CCO)C(=O)c1ccc(Cl)cc1
|
train
|
moses
| 2
|
CC1Oc2ccc(Cl)cc2N(CC(O)CO)C1=O
|
train
|
moses
| 4
|
CCOC(=O)c1cncn1C1CCCc2ccccc21
|
train
|
moses
| 5
|
COc1ccccc1OC(=O)c1ccccc1OC(C)=O
|
train
|
moses
| 6
|
O=C1Nc2ccc(Cl)cc2C(c2ccccc2Cl)=NC1O
|
train
|
moses
| 7
|
Cc1nc2c([nH]1)c(=O)n(C)c(=O)n2CC1CC=CCC1
|
train
|
moses
| 9
|
COc1cc2c(cc1O)N=CC1CCC(O)N1C2=O
|
train
|
moses
| 10
|
COc1cc(C)c(Cc2cnc(N)nc2N)cc1OC
|
train
|
moses
| 11
|
O=C1Nc2ccc(Cl)cc2C(c2ccccc2)=NC1O
|
train
|
moses
| 12
|
CC1CC(OC(=O)CN2CCCC2=O)CC(C)(C)C1
|
train
|
moses
| 13
|
COc1ccc(OC)c(Cc2cnc3nc(N)nc(N)c3c2C)c1
|
train
|
moses
| 14
|
COC(=O)c1c[nH]c2cc(OC(C)C)c(OC(C)C)cc2c1=O
|
train
|
moses
| 15
|
CCC1NC(=O)c2cc(S(N)(=O)=O)c(Cl)cc2N1
|
train
|
moses
| 16
|
COc1cc(C(=O)N2CCOCC2)cc(OC)c1OC
|
train
|
moses
| 17
|
COc1ccc(C=C2CCCN=C2c2cccnc2)c(OC)c1
|
train
|
moses
| 18
|
CC(=O)Nc1ccc(S(=O)(=O)c2ccc(NC(C)=O)cc2)cc1
|
train
|
moses
| 19
|
CC1(C)C(=O)Nc2cc3nc(-c4ccncc4)[nH]c3cc21
|
train
|
moses
| 20
|
Cc1nnc2n1-c1ccc(Cl)cc1C(c1ccccc1)=NC2
|
train
|
moses
| 21
|
CC(C)(C#N)c1cc(Cn2cncn2)cc(C(C)(C)C#N)c1
|
train
|
moses
| 22
|
COc1ccc(-c2nnc(C)nc2-c2ccc(OC)cc2)cc1
|
train
|
moses
| 24
|
Cc1cc(Cc2cnc(N)nc2N)c2cccnc2c1N(C)C
|
train
|
moses
| 25
|
CC(=O)Nc1ccc(OC(=O)c2ccccc2OC(C)=O)cc1
|
train
|
moses
| 26
|
CC1(C)C=C(n2ccccc2=O)c2cc(C#N)ccc2O1
|
train
|
moses
| 27
|
CCC1(O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3ccccc3nc2-1
|
train
|
moses
| 32
|
NS(=O)(=O)c1cc2c(cc1Cl)CN(C1CCCCC1)C2=O
|
train
|
moses
| 33
|
Nc1nc2c(ncn2C2CC(CO)C2CO)c(=O)[nH]1
|
train
|
moses
| 34
|
CC12CCC3=C(CCc4cc(O)ccc43)C1CCC2=O
|
train
|
moses
| 35
|
NC(=O)c1cc(Br)cc(Br)c1O
|
train
|
moses
| 37
|
OCCN(CCO)c1nc(-c2ccccc2)c(-c2ccccc2)o1
|
train
|
moses
| 38
|
O=C1OCC(Cc2cccc(O)c2)C1Cc1cccc(O)c1
|
train
|
moses
| 40
|
Clc1ccc2c(c1)C(c1ccccc1)=NCc1nncn1-2
|
train
|
moses
| 41
|
CCc1nc(N)nc(N)c1-c1ccc(Cl)c(Cl)c1
|
train
|
moses
| 44
|
COc1ccc(-c2cc(=O)c3c(O)c(OC)c(OC)cc3o2)cc1O
|
train
|
moses
| 45
|
CN1C(=O)CN=C(c2ccccc2F)c2cc(Cl)ccc21
|
train
|
moses
| 46
|
Cc1cn(C2OC(CO)C(O)C2F)c(=O)[nH]c1=O
|
train
|
moses
| 48
|
Nc1nc2c(ncn2COC(CO)CO)c(=O)[nH]1
|
train
|
moses
| 49
|
Cc1nc2ccccc2c(=O)n1-c1ccc(Cl)cc1
|
train
|
moses
| 52
|
Cc1cc2c(cc1S(N)(=O)=O)S(=O)(=O)CCC2
|
train
|
moses
| 53
|
COc1ccc(C2Cc3cccc(O)c3C(=O)O2)cc1O
|
train
|
moses
| 55
|
Clc1ccccc1-c1nc(-c2ccncc2)no1
|
train
|
moses
| 56
|
C#CCN1C(=O)CN=C(c2ccccc2)c2cc(Cl)ccc21
|
train
|
moses
| 57
|
CC(C)(Oc1ccc(Cl)cc1)C(=O)OCc1cccc(CO)n1
|
train
|
moses
| 58
|
Cc1c2c(cn1C)NC(=O)CN=C2c1ccccc1
|
train
|
moses
| 59
|
CCn1ccc(NS(=O)(=O)c2ccc(N)cc2)nc1=O
|
train
|
moses
| 60
|
Nc1ccc(S(=O)(=O)Nc2cnccn2)cc1
|
train
|
moses
| 61
|
CC(=O)N(c1onc(C)c1C)S(=O)(=O)c1ccc(N)cc1
|
train
|
moses
| 62
|
NS(=O)(=O)c1ccc(N2CCCCS2(=O)=O)cc1
|
train
|
moses
| 63
|
Cc1ncc(Cn2c(C)c(CCO)sc2=O)c(N)n1
|
train
|
moses
| 64
|
Cc1nnc2n1-c1ccc(Cl)cc1C(c1ccccc1Cl)=NC2
|
train
|
moses
| 65
|
Oc1c(Br)cc(Cl)c2cccnc12
|
train
|
moses
| 68
|
Cc1nn(C)c2c1C(c1cccc(Cl)c1)=NCCN2
|
train
|
moses
| 70
|
NS(=O)(=O)c1cc(C(=O)c2ccc(O)cc2)cs1
|
train
|
moses
| 71
|
COC1C(O)C(CO)OC1n1cnc2c(N)ncnc21
|
train
|
moses
| 72
|
N#Cc1ccc(Nc2ncnc3c2CCC3O)cc1
|
train
|
moses
| 74
|
CN(C)c1ncnc2c1ncn2Cc1ccccc1
|
train
|
moses
| 75
|
O=C1c2cccnc2CN1Cc1c(F)cccc1F
|
train
|
moses
| 76
|
COc1ccc(CN2Cc3ncccc3C2=O)cc1
|
train
|
moses
| 77
|
O=C1c2cccnc2CN1Cc1ccc(Cl)cc1
|
train
|
moses
| 78
|
O=C1c2cccnc2CN1Cc1ccccc1Cl
|
train
|
moses
| 79
|
O=C1c2cccnc2CN1Cc1ccccc1C(F)(F)F
|
train
|
moses
| 80
|
CCc1nc(C#N)c(N2CCc3ccccc3CC2)nc1C
|
train
|
moses
| 81
|
COc1cccc(-c2csc(-c3cccnc3)n2)c1
|
train
|
moses
| 82
|
O=C(NC1CCc2ccccc2C1)c1ccncc1
|
train
|
moses
| 83
|
CC1(F)OC(n2cc(F)c(=O)[nH]c2=O)C(O)C1O
|
train
|
moses
| 84
|
CSc1nc2ccccc2n1Cc1ccccn1
|
train
|
moses
| 85
|
Cn1c(=O)c2c(ncn2CC2OCCO2)n(C)c1=O
|
train
|
moses
| 86
|
CC(=O)c1ccc(NS(C)(=O)=O)c(Oc2ccc(F)cc2F)c1
|
train
|
moses
| 87
|
Cn1c(=O)c2c(ncn2CC(=O)N2CCOCC2)n(C)c1=O
|
train
|
moses
| 88
|
CN1Cc2c(C(=O)OC(C)(C)C)ncn2-c2ccsc2C1=O
|
train
|
moses
| 89
|
Nc1nc2c(ncn2C2OC(CO)C(O)C2F)c(=O)[nH]1
|
train
|
moses
| 90
|
COc1ccc(O)cc1Cc1cnc2nc(N)nc(N)c2c1C
|
train
|
moses
| 91
|
CNC(=O)OCc1nc(SC)n(C)c1COC(=O)NC
|
train
|
moses
| 92
|
OC(Cn1cncn1)(Cn1cncn1)c1ccc(F)cc1F
|
train
|
moses
| 93
|
O=c1[nH]c(=O)n(C2CC(F)C(CO)O2)cc1Cl
|
train
|
moses
| 94
|
CC(C)n1c(=O)c2c(-c3noc(C4CC4)n3)ncn2c2ccccc21
|
train
|
moses
| 95
|
O=C1CCCN1S(=O)(=O)c1ccc(Cl)cc1
|
train
|
moses
| 96
|
Cc1[nH]cnc1Cc1nc(-c2ccccc2)cs1
|
train
|
moses
| 97
|
COc1ccc(-c2nc3n(c2-c2ccncc2)CCC3)cc1
|
train
|
moses
| 98
|
COc1cnc2c3c(nccc13)C(=O)c1ccccc1-2
|
train
|
moses
| 100
|
Cc1cccc(C)c1NC(=O)c1ccc(S(C)(=O)=O)cc1
|
train
|
moses
| 101
|
NC(=O)N1c2ccccc2CC(=O)c2ccccc21
|
train
|
moses
| 102
|
Cc1cc(=O)c(N)nn1-c1cccc(C(F)(F)F)c1
|
train
|
moses
| 104
|
Cc1ccnc2c1NC(=O)c1cccnc1N2C1CC1
|
train
|
moses
| 105
|
Nc1ccc(-c2cc(=O)c3cc(O)ccc3o2)cc1
|
train
|
moses
| 106
|
CC1(C)Oc2cc(C#N)sc2C(N2CCCC2=O)C1O
|
train
|
moses
| 107
|
Cc1oc2nc3c(c(NC(=O)CN4CCCC4=O)c2c1C)CCCC3
|
train
|
moses
| 108
|
CCOC(=O)C1CN(Cc2ccccc2)C(=O)C1=O
|
train
|
moses
| 109
|
COc1ccc(C2CNC(=O)C2)cc1OC1CCCC1
|
train
|
moses
| 110
|
O=C(c1ccccn1)c1cnn2c(-c3ccncc3)ccnc12
|
train
|
moses
| 111
|
COc1ccc(C2CNC(=O)NC2)cc1OC1CC2CCC1C2
|
train
|
moses
| 112
|
CCCn1c(=O)c2[nH]c(C3CCC(=O)C3)nc2n(CCC)c1=O
|
train
|
moses
| 113
|
O=C(NC1CCCCNC1=O)c1cccc(C(F)(F)F)c1
|
train
|
moses
| 114
|
C=C1C(CO)C(O)CC1n1cnc2c(=O)[nH]c(N)nc21
|
train
|
moses
| 115
|
COc1cc(Cc2cnc(N)nc2N)cc(OC)c1Br
|
train
|
moses
| 118
|
COc1cc(CNc2ccc(C)cc2)cc(OC)c1OC
|
train
|
moses
| 119
|
O=C(NCCc1cccc2ccccc12)C1CCC1
|
train
|
moses
| 120
|
O=c1c2ccccc2c(-c2cccnc2)nn1CCn1ccnc1
|
train
|
moses
| 121
|
Cc1nnc2n1-c1ccc(Cl)cc1C(c1cccc(O)c1)=NC2
|
train
|
moses
| 123
|
End of preview. Expand
in Data Studio
Dataset Details
Dataset Description
Molecular Sets (MOSES) is a benchmark platform for distribution learning based molecule generation. Within this benchmark, MOSES provides a cleaned dataset of molecules that are ideal of optimization. It is processed from the ZINC Clean Leads dataset.
- Curated by:
- License: CC BY 4.0
Dataset Sources
- Article about original dataset
- Link to publication of associated dataset - zinc
- Github repository concerning the dataset
Citation
BibTeX:
@article{10.3389/fphar.2020.565644,
title={{M}olecular {S}ets ({MOSES}): {A} {B}enchmarking {P}latform for {M}olecular {G}eneration {M}odels},
author={Polykovskiy, Daniil and Zhebrak, Alexander and Sanchez-Lengeling, Benjamin and Golovanov,
Sergey and Tatanov, Oktai and Belyaev, Stanislav and Kurbanov, Rauf and Artamonov,
Aleksey and Aladinskiy, Vladimir and Veselov, Mark and Kadurin, Artur and Johansson,
Simon and Chen, Hongming and Nikolenko, Sergey and Aspuru-Guzik, Alan and Zhavoronkov, Alex},
journal={Frontiers in Pharmacology},
year={2020}
}
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