Molecule name stringlengths 9 9 | SMILES stringlengths 22 138 | LogD float64 -2 5.2 |
|---|---|---|
E-0010647 | CN(C)CCCNc1nc(Nc2ccncc2)nc2ccccc12 | 1.5 |
E-0011026 | COc1ccc(Nc2nccc(NCCc3ccncc3)n2)cc1 | 2.8 |
E-0011083 | CNc1ccnc(N(CCc2cccnc2)c2ccnc(Nc3ccc(Cl)cc3)n2)n1 | -0.1 |
E-0011133 | CNc1ccnc(N(CCc2cccnc2)c2ccnc(Nc3ccc(OC)cc3)n2)n1 | -0.6 |
E-0011137 | CNc1ccnc(N(CCc2ccncc2)c2ccnc(Nc3ccc(OC)cc3)n2)n1 | -0.6 |
E-0011305 | COc1cccc(-c2cn(C)c3ccc(OCCCN4CCCC4)cc23)c1 | 2.7 |
E-0011306 | COc1cncc(-c2cn(C)c3ccc(OCCCN4CCCC4)cc23)c1 | 2.1 |
E-0011316 | Cn1cc(-c2cccnc2)c2cc(OCCCN3CCCC3)ccc21 | 1.9 |
E-0011317 | Cc1cc(C#N)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.9 |
E-0011335 | Cc1ccc(CNc2cc(-c3ccccc3)[nH]c(=O)n2)cc1 | 3 |
E-0011366 | COc1ccc(-c2csc(Nc3ccccn3)n2)cc1 | 4.3 |
E-0011637 | Cc1cc(-n2cccn2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 3.1 |
E-0011638 | Cc1cc(-n2ccnc2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.8 |
E-0011646 | O=C1CCc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc2N1 | 2.6 |
E-0011647 | Cn1c(=O)ccc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc21 | 2.8 |
E-0011648 | c1cc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc2cn1 | 3.3 |
E-0011658 | CN1C(=O)CCc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc21 | 2.9 |
E-0011659 | COc1ccc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc2n1 | 4.4 |
E-0011660 | c1cc(OCCN2CCCCC2)cc(-c2ccc3ccnnc3c2)c1 | 2.4 |
E-0011661 | c1cc2ccc(-c3ccc(OCCN4CCCCC4)cc3)nc2cn1 | 2.5 |
E-0011662 | O=C1Cc2ccc(-c3ccc(O)cc3)cc2N1 | 2.5 |
E-0011663 | Oc1ccc(-c2ccc3ccncc3c2)cc1 | 3.6 |
E-0011664 | O=C1Cc2ccc(-c3cccc(O)c3)cc2N1 | 2.5 |
E-0011665 | CN1C(=O)Cc2ccc(-c3cccc(O)c3)cc21 | 2.6 |
E-0011666 | Oc1cccc(-c2ccc3ccncc3c2)c1 | 3.6 |
E-0011669 | COc1cc(Nc2nccc(=O)[nH]2)cc(OC)c1 | 1.3 |
E-0011670 | COc1cccc(Nc2nccc(=O)[nH]2)c1 | 1.1 |
E-0011671 | Cc1cccc(Nc2nccc(=O)[nH]2)c1 | 1.5 |
E-0011694 | Fc1cc(-c2ccnc(Nc3cccc(CN4CCOCC4)c3)n2)cc(N2CCOCC2)c1 | 4 |
E-0011695 | O=C1Cc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc2N1 | 2.5 |
E-0011696 | CN1C(=O)Cc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc21 | 2.6 |
E-0011697 | O=C1Cc2ccc(-c3cccc(OCCN4CCCCC4)c3)cc2N1 | 2.5 |
E-0011698 | c1cc2ccc(-c3ccc(OCCN4CCCCC4)cc3)cc2nn1 | 2.4 |
E-0011699 | c1cc(OCCN2CCCCC2)cc(-c2ccc3ccncc3c2)c1 | 3.5 |
E-0011700 | CN1C(=O)Cc2ccc(-c3ccc(O)cc3)cc21 | 2.6 |
E-0011702 | Fc1ccc(-c2csc(Nc3ccncc3)n2)cc1 | 4.2 |
E-0011706 | Nc1ccnc2cc(-c3ccccc3)nn12 | 3 |
E-0011758 | Cc1cc(-c2nccs2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 3.3 |
E-0011759 | CN1C(=O)Cc2ccc(-c3cccc(OCCN4CCCCC4)c3)cc21 | 2.2 |
E-0011760 | Cc1cc(C2(C#N)CC2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.8 |
E-0011761 | Cc1cc(C#N)cc2c3cc(OCCN4CCCCC4)ccc3n(C)c12 | 3.3 |
E-0011762 | O=c1ccnc(Nc2cc(Cl)cc(Cl)c2)[nH]1 | 2.6 |
E-0011763 | O=c1ccnc(Nc2cccc(Cl)c2)[nH]1 | 1.7 |
E-0011791 | CS(=O)(=O)Nc1cccc(-c2ccnc(Nc3ccc(CC(N)=O)cc3)n2)c1 | 1.7 |
E-0011802 | Cc1cc(C#N)cc2c3cc(Oc4ccnc(N)c4)ccc3n(C)c12 | 4.3 |
E-0011803 | COCCNC(=O)c1ccc2c(c1)c1cc(C#N)cc(C)c1n2C | 3.1 |
E-0011804 | COc1cc(Nc2nc(-c3ccccc3)cc(=O)[nH]2)cc(OC)c1 | 4 |
E-0011805 | Nc1cc(C2CC2)nc2cc(-c3ccccc3)nn12 | 3.8 |
E-0011806 | COc1ccc(-c2cc(N)n3nc(-c4ccccc4)cc3n2)cc1 | 4.8 |
E-0011807 | COc1cccc(-c2cc(N)n3nc(-c4ccccc4)cc3n2)c1 | 3.8 |
E-0011808 | COC(=O)c1n[nH]cc1Nc1ccccc1 | 1.5 |
E-0011833 | CC(C)c1cc(N)n2nc(-c3ccccc3)cc2n1 | 3.9 |
E-0011834 | C#Cc1cc(N)n2nc(-c3ccccc3)cc2n1 | 3.2 |
E-0011835 | COc1ccccc1-c1cc2nc(-c3ccccc3)cc(N)n2n1 | 4.5 |
E-0011836 | COC(=O)c1nn(Cc2ccccc2)cc1N | 1.1 |
E-0011837 | COC(=O)c1c(N)cnn1Cc1ccccc1 | 1.7 |
E-0011838 | Cc1cc(-c2cnccn2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.8 |
E-0011839 | Cc1cc(-c2cncs2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 3.3 |
E-0011840 | Cc1cc(C#N)cc2c3cc(OCCNC4CCC(F)(F)CC4)ccc3n(C)c12 | 3.9 |
E-0011841 | Cc1c2ccncc2cc2c3cc(OCC4CNC4)ccc3n(C)c12 | 1.1 |
E-0011842 | Cc1c2ccncc2cc2c3cc(OC4CCNC4)ccc3n(C)c12 | 1.7 |
E-0011863 | COC(=O)c1n[nH]cc1N(C)C | 0.2 |
E-0011865 | Nc1cc(-c2ccccc2)nc2c(-c3ccccc3)cnn12 | 5 |
E-0011866 | CCCc1cc(N)n2nc(-c3ccccc3)cc2n1 | 4.1 |
E-0011867 | CN(C)c1cc(-c2ccccc2)nc2cc(-c3ccccc3)nn12 | 5 |
E-0011868 | Cc1cc2nc(-c3ccccc3)cc(N)n2n1 | 3.1 |
E-0011869 | COc1ccc(-c2cc3nc(-c4ccccc4)cc(N)n3n2)cc1 | 4.9 |
E-0011870 | COc1cccc(-c2cc3nc(-c4ccccc4)cc(N)n3n2)c1 | 4.1 |
E-0011871 | OCCNc1cc(-c2ccccc2)nc2cc(-c3ccccc3)nn12 | 4.3 |
E-0011872 | O=C(c1n[nH]c2ccccc12)N1CCC(Nc2ccc(Cl)cc2)CC1 | 3.8 |
E-0011873 | O=C(c1n[nH]c2ccccc12)N1CCC(NCc2ccc(Cl)cc2)CC1 | 2.7 |
E-0011874 | O=C(c1n[nH]c2ccccc12)N1CCN(Cc2ccc(C(F)(F)F)cc2)CC1 | 4.1 |
E-0011875 | Cc1c2ccncc2cc2c3cc(OCC4(C)CNC4)ccc3n(C)c12 | 1.8 |
E-0011877 | Cc1c2ccncc2cc2c3cc(OCC4CCN4)ccc3n(C)c12 | 2 |
E-0011880 | Fc1cccc(-c2ccnc(Nc3ccc(CN4CCOCC4)cc3)n2)c1 | 3.9 |
E-0011881 | c1cc2ccc(-n3cc(OCCN4CCCCC4)cn3)cc2cn1 | 2.2 |
E-0011882 | c1cc2ccc(-n3cc(OCCN4CCCCC4)cn3)cc2nn1 | 1.4 |
E-0011883 | CNc1cc2ccncc2cc1-n1cc(OCCN2CCCCC2)cn1 | 2.1 |
E-0011884 | Cc1c2ccncc2cc2c3cc(OCCNC4CCOCC4)ccc3n(C)c12 | 3.2 |
E-0011885 | Cc1c2ccncc2cc2c3cc(OC[C@H](C)NC4CCOCC4)ccc3n(C)c12 | 3.5 |
E-0011888 | Nc1cc(-c2ccccc2)nc2nc(-c3ccccc3)cn12 | 3.9 |
E-0011889 | COC(=O)c1nn(-c2ccccc2)cc1N | 1.5 |
E-0011890 | COC(=O)c1nn(C(C)C)cc1N | 0.2 |
E-0011891 | O=C(c1nn(CCO)c2ccccc12)N1CCC(Oc2ccc(Cl)cc2)CC1 | 3.6 |
E-0011892 | CN(C)CCn1nc(C(=O)N2CCC(Oc3ccc(Cl)cc3)CC2)c2ccccc21 | 3.7 |
E-0011893 | CN1CCN(c2cccc(Nc3nc(-c4ccc(F)cc4)cs3)c2)CC1 | 4.4 |
E-0011894 | CN(C)CCCOc1ccccc1Nc1nc(-c2ccc(F)cc2)cs1 | 3.4 |
E-0011895 | O=C(c1n[nH]c2ccccc12)N1CCC(Oc2ccccc2Cl)CC1 | 4.2 |
E-0011896 | O=C(c1n[nH]c2ccccc12)N1CCC(Oc2cccc(Cl)c2)CC1 | 4 |
E-0011897 | O=C(c1n[nH]c2ccccc12)N1CCC(Oc2ccc(C(F)(F)F)cc2)CC1 | 4.6 |
E-0011898 | O=C(c1n[nH]c2ccccc12)N1CC(NCc2ccc(Cl)cc2)C1 | 3.5 |
E-0011899 | O=C(c1n[nH]c2ccccc12)N1CCN(Cc2ccccc2Cl)CC1 | 3.6 |
E-0011900 | O=C(c1n[nH]c2ccccc12)N1CCN(Cc2cccc(Cl)c2)CC1 | 3.7 |
E-0011901 | O=C(c1n[nH]c2ccccc12)N1CCN(Cc2ccc(F)cc2)CC1 | 3.1 |
E-0011908 | Cc1ccc2[nH]nc(C(=O)N3CCC(Oc4ccc(Cl)cc4)CC3)c2c1 | 4.3 |
E-0011913 | COc1ccc2c(C(=O)N3CCC(Oc4ccc(Cl)cc4)CC3)n[nH]c2c1 | 4.2 |
E-0011920 | O=C(c1n[nH]c2ncccc12)N1CCC(Oc2ccc(Cl)cc2)CC1 | 3.9 |
E-0011924 | Cc1cc(-c2ccccn2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 3.2 |
E-0011925 | Cc1cc(-c2ncccn2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.9 |
E-0011927 | Cc1cc(-c2ccncn2)cc2c3cc(OCCCN4CCCC4)ccc3n(C)c12 | 2.8 |
End of preview. Expand in Data Studio
ExpansionRx-OpenADMET LogD
LogD dataset from the ExpansionRx-OpenADMET Blind Challenge [1] [2]. It is intended to be used through scikit-fingerprints library.
The task is to predict LogD of molecules.
| Characteristic | Description |
|---|---|
| Tasks | 1 |
| Task type | regression |
| Total samples | 7309 |
| Recommended split | time |
| Recommended metric | MAE |
References
[1] OpenADMET team "Announcement 1: ExpansionRx-OpenADMET Blind Challenge" https://openadmet.ghost.io/expansionrx-openadmet-blind-challenge/
[2] HuggingFace Hub - ExpansionRx-OpenADMET challenge full dataset https://huggingface.co/datasets/openadmet/openadmet-expansionrx-challenge-data
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