ars.els-cdn.com · Web view3.0822 YES 186. Training CCCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12 -0.2550-0.2505 16.0581 No 187. Validation COCCCalibrationCc1cc(cs1)-c1n[nH]c2

Monte Carlo method for Predicting of Cardiac Toxicity:

hERG blocker compounds

Marco Gobbi1, Marten Beeg1, Mariya A. Toropova1,2, Andrey A. Toropov3,*, Mario Salmona4

1 Department of Molecular Biochemistry and Pharmacology, Laboratory of Pharmacodynamics

and Pharmacokinetics, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19,

20156 Milano, Italy2Dipartimento di Scienze Farmaceutiche, Universita` degli Studi di Milano, Via L. Mangiagalli,

25, 20133 Milan, Italy3Department of Environmental Health Science, Laboratory of Environmental Chemistry and

Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156

Milano, Italy4 Department of Molecular Biochemistry and Pharmacology, Laboratory of Biochemistry and

Protein Chemistry, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19,

20156 Milano, Italy

Supplementary materials

Table S1Correlation weights of SMILES attributes which are stable promoter of increase or decrease of cardiac toxicity for three different distributions into the training, calibration and validation sets obtained in three runs of the Monte Carlo optimization.

Table S2Three distribution into the training, calibration, and validation sets examined in this work; Experimental and calculated values of pIC50; and domain of applicability according to inequality

Table S1Correlation weights of SMILES attributes which are stable promoter of increase or decrease of cardiac toxicity for three different distributions into the training, calibration and validation sets obtained in three runs of the Monte Carlo optimization.

No. Ak CWs(Ak) Probe 1

CWs(Ak) Probe 2

CWs(Ak) Probe 3

NT(Ak)* NC(Ak)* Defectk**

Distribution 1 1 c........... 0.31607 0.12892 0.24656 287 52 0.0001 2 C...C....... 1.19103 1.30859 1.06745 265 51 0.0003 3 c...c...c... 0.81421 0.44116 1.62766 263 51 0.0003 4 N...C....... 0.99648 0.37893 0.00004 246 44 0.0000 5 ++++N---O=== 1.12206 1.81135 1.55756 240 48 0.0004 6 NOSP11000000 5.37898 4.62824 5.37745 201 47 0.0009 7 C...C...(... 1.68912 1.24744 1.81705 199 39 0.0003 8 c...c...(... 0.49710 0.74914 1.68856 195 33 0.0001 9 c...2....... 0.62992 0.37692 0.56074 186 30 0.0003 10 ++++O---B2== 0.37475 0.19042 1.25424 184 30 0.0002 11 HALO00000000 3.93776 4.12148 3.18918 172 34 0.0003 12 N...(...C... 3.00030 2.37305 1.87524 168 29 0.0001 13 C...N...(... 1.49822 1.99501 2.74531 162 26 0.0003 14 =...O...(... 1.49528 0.55946 1.00461 160 28 0.0000 15 (...C...(... 1.31001 1.00432 1.25222 157 32 0.0004 16 C...1....... 0.06656 0.62904 0.30989 152 35 0.0008 17 [...C....... 3.44242 0.69212 1.19054 143 38 0.0014 18 C...C...C... 2.00005 1.62043 2.18405 120 28 0.0009 19 C...(...=... 1.43942 1.18693 0.87724 118 23 0.0003 20 C...C...1... 0.80931 0.43599 0.56407 117 27 0.0008 1 C........... -0.62386 -0.62569 -1.00393 292 52 0.0000 2 (........... -0.56330 -0.50293 -0.93554 289 52 0.0000 3 N........... -0.93661 -0.24977 -1.25423 271 50 0.0001 4 c...(....... -0.37935 -0.56701 -0.31740 268 47 0.0000 5 O........... -1.62752 -1.50124 -1.05774 248 49 0.0003 6 N...(....... -1.94083 -1.43913 -0.44041 212 33 0.0004 7 =........... -1.81118 -1.00289 -1.12047 195 31 0.0003 8 N...C...C... -0.43628 -0.62397 -0.18828 176 33 0.0002 9 [........... -0.87284 -1.00057 -0.87578 176 41 0.0009 10 O...=....... -1.81625 -1.37103 -1.06744 171 30 0.0000 11 c...2...c... -0.93332 -0.74943 -0.18944 167 28 0.0002 12 H........... -1.18665 -0.19200 -1.93437 161 36 0.0007 13 [...H....... -0.31429 -1.43364 -0.62376 161 36 0.0007 14 n........... -1.99935 -0.81628 -1.31010 124 21 0.0001 15 N...1....... -1.94088 -1.18762 -1.81648 114 23 0.0004 16 N...1...C... -2.93636 -3.50486 -1.68705 92 16 0.0000 17 (...(....... -2.12800 -1.87378 -1.93975 77 17 0.0007 18 3........... -1.43971 -1.24912 -1.18485 74 10 0.0007 19 C...(...1... -2.43783 -1.68755 -2.24647 72 19 0.0013 20 C...@@...... -0.12123 -0.68849 -0.93600 72 22 0.0019

Distribution 2 1 c...1....... 0.81379 0.24651 1.43747 275 50 0.0001 2 C...C....... 1.87824 1.43570 0.81013 263 52 0.0002 3 c...c...c... 0.99909 0.74780 0.81750 262 50 0.0001 4 C...C...(... 1.06278 1.49808 2.00070 198 38 0.0001 5 NOSP11000000 4.62481 3.74629 3.87814 198 45 0.0006 6 c...c...(... 0.49855 0.43427 0.44129 192 37 0.0001 7 HALO00000000 2.75419 3.74968 2.80975 173 30 0.0002 8 c...c...2... 1.12337 0.87995 1.18770 166 27 0.0004 9 N...(...C... 2.05870 2.18325 1.99605 164 30 0.0001 10 1...(....... 0.37745 0.12907 0.12608 161 36 0.0006 11 (...C...(... 1.00198 1.00145 0.50042 159 31 0.0001 12 C...N...(... 1.50482 2.56426 2.18688 155 29 0.0000 13 [...C....... 0.68659 1.37158 1.69043 146 36 0.0009 14 O...C....... 0.69194 0.12563 0.06696 132 31 0.0007 15 C...(...C... 0.24996 1.06687 0.69176 130 24 0.0000 16 C...C...C... 1.43748 1.99833 2.81257 120 22 0.0000 17 c...(...C... 1.68666 1.81279 2.18693 120 18 0.0006 18 C...(...=... 1.74625 0.93703 0.68780 113 27 0.0008 19 c...C....... 1.68761 1.44023 1.55837 107 22 0.0003 20 2...(....... 1.31052 0.56051 0.68619 105 18 0.0002 1 C........... -0.75251 -0.93355 -1.00133 288 54 0.0000 2 (........... -0.62289 -0.49780 -0.75286 284 54 0.0001 3 N........... -1.30869 -0.43445 -0.81192 267 52 0.0001 4 O........... -1.31316 -1.25085 -1.06417 242 50 0.0003 5 N...(....... -0.24882 -0.75324 -0.24523 209 33 0.0005 6 =........... -1.37614 -0.87198 -1.49901 189 36 0.0001 7 ++++N---B2== -0.12702 -0.93300 -0.81704 182 35 0.0001 8 [........... -0.81461 -1.00248 -0.62315 177 40 0.0006 9 O...=....... -1.00446 -1.31557 -1.68638 166 35 0.0004 10 H........... -0.50003 -0.75061 -0.81240 159 39 0.0009 11 [...H....... -0.43769 -0.99525 -0.87979 159 39 0.0009 12 C...1....... -0.06715 -0.74719 -0.18813 149 33 0.0005 13 n........... -1.50103 -1.49922 -1.74732 129 18 0.0008 14 [...(....... -0.30785 -0.56015 -0.99988 120 28 0.0007 15 N...1....... -0.69196 -0.37086 -0.12061 112 24 0.0004 16 c...1...(... -0.93877 -0.25465 -1.12289 92 21 0.0006 17 @........... -0.99860 -0.31509 -0.06386 90 21 0.0007 18 N...1...C... -1.68475 -1.87376 -3.50068 89 19 0.0004 19 n...c....... -0.49505 -1.12176 -1.05766 84 11 0.0009 20 C...(...1... -0.80889 -0.80980 -1.68372 74 13 0.0002 Distribution 2 1 c...1....... 0.25039 0.06159 0.31019 283 49 0.0000 2 c...c...c... 0.87695 0.93748 1.62727 275 44 0.0002 3 c...c...1... 1.80848 1.00217 1.25467 271 47 0.0000 4 C...C....... 1.37835 1.06189 1.06334 270 48 0.0001 5 N...C....... 1.68903 0.43866 0.81564 247 43 0.0001 6 NOSP11000000 3.25233 3.37347 4.62986 205 34 0.0001 7 C...C...(... 0.93665 1.18371 1.18431 201 36 0.0001

8 c...c...(... 0.37149 0.18506 0.37890 198 36 0.0002 9 HALO00000000 1.30991 2.31626 2.87545 176 29 0.0001 10 c...c...2... 0.55860 1.75228 2.24879 169 26 0.0003 11 N...(...C... 1.37723 1.31536 1.31006 166 32 0.0004 12 =...O...(... 1.12841 1.18888 0.44240 164 31 0.0003 13 C...N...(... 2.00294 3.31706 1.81341 162 26 0.0002 14 (...C...(... 0.37667 0.37501 0.24936 161 35 0.0008 15 1...c...(... 0.74959 0.18994 0.00158 156 31 0.0005 16 C...1....... 0.62578 1.56728 0.87182 151 26 0.0000 17 [...C....... 2.06275 2.37601 0.99603 146 37 0.0013 18 C...(...C... 0.12964 0.44232 0.55807 130 30 0.0010 19 C...(...=... 1.06436 1.19053 1.49543 123 21 0.0000 20 c...(...C... 1.37470 1.87185 1.50137 123 18 0.0004 1 C........... -0.87049 -0.87502 -0.87186 297 51 0.0000 2 (........... -0.81609 -0.69049 -0.81340 294 51 0.0000 3 N........... -0.68257 -0.37647 -0.12766 275 46 0.0001 4 O........... -0.68740 -1.12372 -0.68985 252 45 0.0001 5 N...(....... -0.24845 -1.19153 -0.62209 210 38 0.0002 6 O...(....... -0.37754 -0.25492 -0.31218 207 37 0.0001 7 =........... -1.12067 -1.00050 -0.25022 198 32 0.0002 8 N...C...C... -1.37898 -0.68683 -0.87776 178 33 0.0002 9 [........... -0.50075 -1.00142 -1.00437 178 40 0.0009 10 O...=....... -1.12490 -1.06741 -1.24845 176 32 0.0002 11 [...H....... -1.87406 -0.93912 -1.06334 161 37 0.0009 12 n........... -1.12473 -1.18447 -0.56734 127 20 0.0002 13 N...1...C... -3.93330 -4.50386 -3.81066 91 10 0.0011 14 (...(....... -2.06434 -2.00250 -1.94061 79 18 0.0009 15 C...(...1... -1.50407 -2.06621 -0.30857 77 11 0.0005 16 3........... -1.18730 -1.62710 -1.75320 73 10 0.0006 17 ++++F---O=== -2.62802 -3.12205 -1.87820 60 14 0.0010 18 -........... -1.30888 -1.18433 -0.62344 60 6 0.0013 19 C...C...2... -0.49863 -0.37074 -0.68884 60 6 0.0013 20 n...1....... -0.56696 -0.87375 -0.49951 59 10 0.0000

*) NT(Ak) and NC(Ak) are the number of Ak in the training and calibration sets, respectively**) defect is the defect of Ak calculated with Eq. 6

Table S2Three distribution into the training, calibration, and validation sets examined in this work; Experimental and calculated values of pIC50; and domain of applicability according to inequality

ID

Set SMILES pIC50(Expr) pIC50(Calc) Defect(SMILES) Domain of Applicability

Distribution 1 Eq.3

1.

Training Fc1ccc(cc1)C(N1CCNCC1)c1ccc(F)cc1

-0.2040 -0.5152 2.0233 YES

2.

Training CN1CCN(CC1)C1=Nc2ccccc2Nc2sc(CO)cc12

-1.0640 -1.0255 6.0573 YES

3.

Validation Fc1ccc(cc1)C(=O)c1ccc(F)cc1

-1.8570 -2.0886 2.0155 YES

4.

Training OC(c1ccc(F)cc1)c1ccc(F)cc1

-1.9960 -2.6468 0.0177 YES

5.

Training Nc1ccncc1 -3.6430 -3.4898 0.0122 YES

6.

Training O=c1ccc2c(OCCCCc3ccccc3)c3ccoc3cc2o1

-0.6990 -0.7064 8.0305 No

7.

Training CCCNC[C@@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.2383 0.0589 YES

8.

Validation CCCNC[C@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.3266 0.0564 YES

9.

Training Cc1nc2CC[C@@H](O)Cn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

-0.1140 -0.0893 1.0820 YES

10.

Training Cc1nc2CC[C@H](O)Cn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

-0.1140 -0.1776 1.0796 YES

11.

Training CC[C@@H](OC(C)=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.7623 0.0750 YES

12.

Validation CC[C@H](OC(C)=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8506 0.0725 YES

13.

Training CC[C@@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.6740 0.0775 YES

14.

Training CC[C@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.7623 0.0750 YES

15.

Training [H][C@]12CN(Cc3ccccc3)C[C@]([H])(CN(C1)C(=O)c1ccc(N)cc1)C2

-0.5560 -0.5304 9.1014 No

16.

Training CCCCc1oc2ccccc2c1C(=O)c1cc(I)c(OCCN(CC)CC)c(I)c1

-0.4470 -0.4307 18.0375 No

17.

Training CN(C)CC\C=C1\c2ccccc2CCc2ccccc12

-1.0000 -1.0176 14.0281 No

18.

Training COc1cc(NS(C)(=O)=O)ccc1Nc1c2ccccc2nc2ccccc12

0.6780 0.7277 8.0489 No

19.

Training CCCN[C@H](C)C(=O)Nc1c(C)csc1C(=O)OC

-2.3500 -2.3530 2.0538 YES

20.

Training CCCN[C@@H](C)C(=O)Nc1c(C)csc1C(=O)OC

-2.3500 -2.2648 2.0563 YES

21.

Validation COc1ccc(CCN2CCC(CC2)Nc2nc3ccccc3n2Cc2ccc(F)cc2)cc1

-0.0000 0.0668 7.0519 YES

22.

Training CN1[C@H]2CC[C@H]1C[C@H](C2)OC(=O)C(O)c1ccccc1

0.2520 0.2315 1.0981 YES

23.

Training CN1CCN(CCCCN2C(=O)CN(\N=C\c3ccc(o3)-c3ccc(Cl)cc3)C2=O)CC1

0.2150 0.1951 22.0587 No

24.

Training CC(=O)OCOC(=O)CN(CC(=O)OCOC(C)=O)c1ccccc1OCCOc1ccccc1N(CC(=O)OCOC(C)=O)CC(=O)OCOC(C)=O

-0.1140 -0.1249 4.0776 YES

25.

Calibration CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-0.9080 -0.4239 0.0434 YES

26.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(Cl)cc2)CC1=O

-0.5190 -0.7670 0.0474 YES

27.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccc(c2)C(F)(F)F)CC1=O

-0.2300 -0.2459 0.0580 YES

28.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCC2CCCCC2)CC1=O

-0.5190 -0.2170 0.0463 YES

29.

Validation CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccs2)CC1=O

-1.1210 -1.0964 1.0547 YES

30.

Training Fc1ccc(CCN2CCN(C3CCc4cc(CN5CCC(CC5)C(F)(F)F)ccc4C3)C(=O)C2)cc1

-0.3010 -0.3435 18.0785 No

Training Fc1ccc(CCN2CCN(C3CCc -0.6020 -0.6504 17.0713 No

31. 4cc(Cn5ccnc5)ccc4C3)C(=O)C2)cc1

32.

Training Fc1ccc(CCN2CCN(C3CCc4cc(CN5CCOCC5)ccc4C3)C(=O)C2)cc1

-1.0410 -1.0989 18.0649 No

33.

Validation CS(=O)(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.1140 -1.1697 7.0607 YES

34.

Training Fc1ccc(CCN2CCN(C3CCc4cc(CN5CCS(=O)(=O)CC5)ccc4C3)C(=O)C2)cc1

-1.3800 -1.3750 26.0735 No

35.

Training CC(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -1.2657 0.0514 YES

36.

Training CN(C)C(=O)C(CO)N(C)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -1.4257 0.0548 YES

37.

Training Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)-c1ccccc1

1.0460 1.0572 7.0658 YES

38.

Validation Fc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=S)c2ccccc12

2.0000 1.0986 8.0542 No

39.

Training CC(C)(O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.0088 0.0626 YES

40.

Validation CC(C)(O)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.0971 0.0651 YES

41.

Training Fc1ccc(cc1)N1C[C@@H](C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

1.6990 1.4244 6.0645 YES

42.

Validation Fc1ccc(cc1)N1C[C@H](C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

1.6990 1.3361 6.0621 YES

43.

Training Fc1ccc(cc1)-n1cc(C2CCNCC2)c2cc(Cl)ccc12

0.6990 0.9379 2.0429 YES

44.

Training CN(C)Cc1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

2.0000 0.7111 2.0376 YES

45.

Training CCCc1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-1.4150 -0.8246 3.0353 YES

46.

Validation CCC(CC)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.1700 -0.7631 3.0348 YES

Validation C[C@@H](O)c1cn(- -0.6580 -0.5435 2.0558 YES

47. c2ccc(F)cc2)c2ccc(Cl)cc12

48.

Training C[C@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.6580 -0.6318 2.0533 YES

49.

Training CCC(=O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.2900 0.0824 2.0391 YES

50.

Training Fc1ccc(cc1)-n1cc(C2=CCN(CCN3CCNC3=O)CC2)c2cc(Cl)ccc12

2.0000 2.0260 6.0635 YES

51.

Training CCC(O)(CC)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-1.1960 -0.8548 2.0402 YES

52.

Validation CC[C@@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.3420 0.0498 2.0577 YES

53.

Training CC[C@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.3420 -0.0385 2.0552 YES

54.

Training CCc1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.5440 -1.1519 3.0341 YES

55.

Training Fc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

2.0000 1.3287 6.0497 YES

56.

Training OC(=O)Cc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

0.2370 0.2595 4.0622 YES

57.

Training OC(=O)c1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

-1.8750 -0.2628 4.0596 YES

58.

Training Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)C1CCCCC1

0.8540 0.8172 7.0668 YES

59.

Training COC(=O)Cc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

0.8860 0.8175 4.0637 YES

60.

Training COC(=O)c1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

1.3980 0.2952 4.0611 YES

61.

Training COc1ccc(CCN(C)CCCN(C(=O)c2ccc(cc2)[N+]([O-])=O)c2ccc(OC)c(OC)c2)cc1OC

1.6990 2.1085 9.0784 No

62.

Training COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.0668 0.1220 YES

63.

Calibration COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1O

-1.1460 -1.1551 0.1195 YES

C 64.

Validation COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1551 0.1195 YES

65.

Training COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.2434 0.1170 YES

66.

Training Fc1ccc(cc1)C(=O)CCCN1CCC(CC1)n1c2ccccc2[nH]c1=O

-0.0000 -0.0267 4.0431 YES

67.

Training CC(C)COC[C@@H](CN(Cc1ccccc1)c1ccccc1)N1CCCC1

0.2600 0.4128 0.0534 YES

68.

Calibration CC(C)COC[C@H](CN(Cc1ccccc1)c1ccccc1)N1CCCC1

0.2600 0.3245 0.0509 YES

69.

Training COc1ccc2cc3-c4cc5OCOc5cc4CC[n+]3cc2c1OC

-0.4910 -0.4875 18.0768 No

70.

Training CC(C)CN1C[C@H]2CN(C[C@@H](C1)C21CCCCC1)C(C)C

-1.7970 -1.6777 3.0791 YES

71.

Training O=C1NC(=O)C(c2c[nH]c3ccccc23)=C1c1c[nH]c2ccccc12

-0.0000 0.0498 13.0540 No

72.

Training Clc1ccc(cc1)C(c1ccc(Cl)cc1)n1cc[n+](C[C@@H](OCc2ccc(Cl)cc2Cl)c2ccc(Cl)cc2Cl)c1

1.5230 1.5260 14.0750 No

73.

Validation CN(C)CC[C@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.3364 9.0376 No

74.

Training CN(C)CC[C@@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.2481 9.0401 No

75.

Training CC(C)(C)N1CCC(CC1)(c1ccccc1)c1ccccc1

-1.0090 -0.6260 0.0315 YES

76.

Calibration CCCCN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.3283 0.0547 YES

77.

Training CCCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.2400 0.0572 YES

78.

Training CC(C)CN1CCC(CC1)CNC(=O)c1cc(Cl)c(N)n2cc(C)nc12

-0.4100 -0.3874 2.0485 YES

79.

Training Cn1cnc2n(C)c(=O)n(C)c(=O)c12

-0.6900 -0.6199 4.0335 YES

80.

Training NC(=O)N1c2ccccc2C=Cc2ccccc12

-2.4000 -2.3663 3.0298 YES

81.

Training COc1ccccc1OCCNC[C@@H](O)COc1cccc2[nH]c3ccccc3c12

0.2920 0.3533 3.0755 YES

82.

Training COc1ccccc1OCCNC[C@H]

0.2920 0.2650 3.0730 YES

(O)COc1cccc2[nH]c3ccccc3c12

83.

Training CC(C)(O)C(Cl)(Cl)Cl -3.6430 -3.6527 4.0169 YES

84.

Training CN(C)CCCN1c2ccccc2Sc2ccc(Cl)cc12

-0.1930 0.1033 3.0311 YES

85.

Training CCN(CC)CCC[C@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 -0.0745 0.0499 YES

86.

Validation CCN(CC)CCC[C@@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 0.0138 0.0524 YES

87.

Training CN(C)CC[C@@H](c1ccc(Cl)cc1)c1ccccn1

-1.1140 -0.9487 1.0445 YES

88.

Training CN(C)CC[C@H](c1ccc(Cl)cc1)c1ccccn1

-1.1140 -1.0370 1.0420 YES

89.

Training C1CN=C(N1)[C@@H]1CC1(c1ccccc1)c1ccccc1

-0.5680 -0.4818 2.0626 YES

90.

Training C1CN=C(N1)[C@H]1CC1(c1ccccc1)c1ccccc1

-0.5680 -0.5701 2.0601 YES

91.

Training OC(=O)c1cn(C2CC2)c2cc(N3CCNCC3)c(F)cc2c1=O

-2.9850 -3.0570 1.0588 YES

92.

Training CO[C@H]1CN(CCCOc2ccc(F)cc2)CC[C@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 1.9584 0.1083 YES

93.

Training CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.0467 0.1108 YES

94.

Calibration CO[C@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.0467 0.1108 YES

95.

Training CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.1350 0.1133 YES

96.

Training CN(C)CCC[C@]1(OCc2cc(ccc12)CCalibrationN)c1ccc(F)cc1

-0.6000 -0.6160 3.0580 YES

97.

Training CN(C)CCC[C@@]1(OCc2cc(ccc12)CCalibrationN)c1ccc(F)cc1

-0.6000 -0.5959 3.0592 YES

98.

Calibration COc1cc(N)c(Cl)cc1C(=O)NC1CCN(CC1)Cc1ccccc1

0.2080 -0.3305 0.0450 YES

99.

Training CN1CCC[C@H]1CCO[C@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.8221 0.0898 YES

100.

Training CN1CCC[C@@H]1CCO[C@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.9104 0.0923 YES

101.

Calibration CN1CCC[C@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.6652 0.0860 YES

102.

Calibration CN1CCC[C@@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.7535 0.0885 YES

103.

Calibration CCCCCCC[N+](CC)(CC)CCCCc1ccc(Cl)cc1

0.6020 -0.1483 0.0485 YES

104.

Training CCN(CC)CCOc1ccc(cc1)C(\c1ccccc1)=C(\Cl)c1ccccc1

0.7450 0.7576 14.0376 No

105.

Training CCN(CC)CCOc1ccc(cc1)C(\c1ccccc1)=C(/Cl)c1ccccc1

0.7450 0.7496 14.0376 No

106.

Training CN1CCN(CC1)C1=c2ccccc2=Nc2ccc(Cl)cc2N1

0.4950 0.4559 4.0454 YES

107.

Training CN1CCN(CC1)[C@H]1N(O)c2cc(Cl)ccc2Nc2ccccc12

-2.1250 -2.2200 2.0598 YES

108.

Calibration CCOC(=O)[C@H]1[C@H](C[C@H]2CC[C@@H]1N2C)OC(=O)c1ccccc1

-0.6020 -0.8254 0.1280 YES

109.

Training COC(=O)[C@H]1[C@H](C[C@@H]2CC[C@H]1N2C)OC(=O)c1ccccc1

-0.7480 -0.7448 0.1269 YES

110.

Training C[C@@H](CN(C)C)CN1c2ccccc2Sc2ccc(cc12)CCalibrationN

0.3280 0.2846 3.0572 YES

111.

Training C[C@H](CN(C)C)CN1c2ccccc2Sc2ccc(cc12)CCalibrationN

0.3280 0.1963 3.0547 YES

112.

Training CCC(=O)O[C@](Cc1ccccc1)([C@H](C)CNC)c1ccccc1

-1.5210 -0.9716 0.0783 YES

113.

Calibration CCC(=O)O[C@](Cc1ccccc1)([C@@H](C)CNC)c1ccccc1

-1.5210 -0.8833 0.0808 YES

114.

Training CCC(=O)O[C@@](Cc1ccccc1)([C@H](C)CNC)c1ccccc1

-1.5210 -1.1285 0.0746 YES

115.

Training CCC(=O)O[C@@](Cc1ccccc1)([C@@H](C)CNC)c1ccccc1

-1.5210 -1.0402 0.0771 YES

116.

Calibration Coc1ccc(CCN(C)CCC[C@](CCalibrationN)(C(C)C)c2ccc(O)c(O)c2)cc1OC

-0.3420 -0.3632 0.0817 YES

117.

Training Coc1ccc(CCN(C)CCC[C@@](CCalibrationN)(C(C)C)c2ccc(O)c(O)c2)cc1OC

-0.3420 -0.5201 0.0779 YES

118.

Validation COc1ccc(CCN[C@@H](C)COc2c(C)cccc2C)cc1OC

-0.7850 -0.3499 1.0641 YES

Training COc1ccc(CCN[C@H] -0.7850 -0.4381 1.0616 YES

119. (C)COc2c(C)cccc2C)cc1OC

120.

Training COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.2059 0.3473 YES

121.

Calibration COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1176 0.3498 YES

122.

Calibration COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.0293 0.3523 YES

123.

Validation COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1176 0.3498 YES

124.

Training Oc1ccc(CCN2CCC(CC2)Nc2nc3ccccc3n2Cc2ccc(F)cc2)cc1

-0.0000 0.0050 7.0492 YES

125.

Calibration Cc1cc2=C(Nc3ccccc3N=c2s1)N1CCNCC1

-1.1520 0.5432 0.0866 YES

126.

Training CCCCNC[C@@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.7400 -0.6385 16.0664 No

127.

Training CCCCNC[C@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.7400 -0.7268 16.0639 No

128.

Validation CNCCCN1c2ccccc2CCc2ccccc12

-0.1430 -0.0776 0.0266 YES

129.

Training Clc1ccc2c(CCc3cccnc3\C2=C2/CCNCC2)c1

-0.6530 -0.6590 16.0398 No

130.

Training CCN[C@H](C)Cc1cccc(c1)C(F)(F)F

-2.7300 -2.6468 1.0477 YES

131.

Training CCN[C@@H](C)Cc1cccc(c1)C(F)(F)F

-2.7300 -2.5585 1.0502 YES

132.

Training COc1ccc(cc1)[C@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@H]1OC(C)=O

-1.2380 -1.2750 0.1154 YES

133.

Validation COc1ccc(cc1)[C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@H]1OC(C)=O

-1.2380 -1.1867 0.1179 YES

134.

Calibration COc1ccc(cc1)[C@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

-1.2380 -1.1867 0.1179 YES

Validation COc1ccc(cc1) -1.2380 -1.0984 0.1204 YES

135. [C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

136.

Training CN(C)CCOC(c1ccccc1)c1ccccc1

-1.4770 -0.5363 0.0193 YES

137.

Calibration CC(C)N(CC[C@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.5484 0.0767 YES

138.

Calibration CC(C)N(CC[C@@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.7053 0.0729 YES

139.

Training CN(CCOc1ccc(NS(C)(=O)=O)cc1)CCc1ccc(NS(C)(=O)=O)cc1

2.0000 1.9418 13.0497 No

140.

Training Clc1ccc2n(C3CCN(CCCn4c5ccccc5[nH]c4=O)CC3)c(=O)[nH]c2c1

0.7960 0.7816 17.0964 No

141.

Calibration COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1COc2ccccc2O1

0.2290 0.9653 0.1150 YES

142.

Calibration COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1COc2ccccc2O1

0.2290 1.0536 0.1175 YES

143.

Training CN(C)CC\C=C1/c2ccccc2COc2ccccc12

-0.8130 -0.8350 15.0322 No

144.

Training CCCCN(CCCC)CCCOc1ccc(cc1)C(=O)c1c(CCCC)oc2ccc(NS(C)(=O)=O)cc12

-0.9640 -0.9503 8.0569 No

145.

Training Cc1cccc(CCN2CCC(CC2)C(=O)c2ccc(NS(C)(=O)=O)cc2)n1

2.0000 2.0109 9.0464 No

146.

Training Oc1cc(O)c2C[C@@H](OC(=O)c3cc(O)c(O)c(O)c3)[C@H](Oc2c1)c1cc(O)c(O)c(O)c1

-0.7780 -0.7904 2.0932 YES

147.

Training COc1ccc(CNc2nnc(N3CCC4(CC3)CC(O)C4)c3ccc(cc23)CCalibrationN)cc1Cl

1.3980 1.4325 20.0610 No

148.

Training CC(C)(C)c1ccc(cc1)C(=O)CCCN1CCC(CC1)OC(c1ccccc1)c1ccccc1

0.5230 0.1592 1.0385 YES

149.

Validation CS(=O)(=O)Nc1ccc(OC[C@](O)CNCCOc2ccc(cc2)-n2ccnc2)cc1

0.3980 0.5384 8.0845 No

150.

Training CS(=O)(=O)Nc1ccc(OC[C@@](O)CNCCOc2ccc(cc2)-

0.3980 0.3815 8.0807 No

n2ccnc2)cc1 151.

Calibration CCC(=O)N(C1CCN(CC1)CCc1ccccc1)c1ccccc1

-0.2550 -0.3603 0.0324 YES

152.

Training CC(C)(C(O)=O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

-1.3620 -1.1624 0.0672 YES

153.

Training CC(C)(C(O)=O)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

-1.3620 -1.0741 0.0697 YES

154.

Calibration FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@H]1CCCCN1

-0.5920 -0.7105 0.0925 YES

155.

Training FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@@H]1CCCCN1

-0.5920 -0.6222 0.0950 YES

156.

Training Fc1ccc(cc1)C(N1CCN(CC1)C\C=C\c1ccccc1)c1ccc(F)cc1

2.0000 1.9747 15.0340 No

157.

Validation CNCC[C@@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.4042 0.0561 YES

158.

Training CNCC[C@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.4925 0.0537 YES

159.

Training Fc1ccc(cc1)C(CCCN1CCC2(CC1)N(CNC2=O)c1ccccc1)c1ccc(F)cc1

-0.3690 0.4332 5.0457 YES

160.

Training COCCCC\C(c1ccc(cc1)C(F)(F)F)=N/OCCN

-0.5800 -0.5806 13.0354 No

161.

Validation COc1c(N2CCN[C@@H](C)C2)c(F)cc2c1n(cc(C(O)=O)c2=O)C1CC1

-2.1140 -2.1917 2.0790 YES

162.

Training COc1c(N2CCN[C@H](C)C2)c(F)cc2c1n(cc(C(O)=O)c2=O)C1CC1

-2.1140 -2.2800 2.0765 YES

163.

Training Fc1ccc(cc1)C(OCCN1CCN(CCCc2ccccc2)CC1)c1ccc(F)cc1

-0.0000 0.3542 2.0372 YES

164.

Training COc1ccc(Cl)cc1C(=O)NCCc1ccc(cc1)S(=O)(=O)NC(=O)NC1CCCCC1

-1.8740 -1.8622 7.0579 YES

165.

Training CCCCCCCCC(=O)NCc1ccc(C[C@H](O)CO)c(OC)c1

1.0000 0.9985 1.0489 YES

166.

Training CCCCCCCCC(=O)NCc1ccc(C[C@@H](O)CO)c(OC)c1

1.0000 1.0868 1.0514 YES

167.

Training C[C@H]1CN(CCN1)c1cc2n(cc(C(O)=O)c(=O)c2c(C)c1F)C1CC1

-1.6990 -1.7723 3.0704 YES

168.

Validation C[C@@H]1CN(CCN1)c1cc2n(cc(C(O)=O)c(=O)c2c(C)c1F)C1CC1

-1.6990 -1.6840 3.0729 YES

169.

Training CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.3564 5.1057 YES

170.

Training CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.4447 5.1082 YES

171.

Training CN([C@@H]1[C@@H](O)C(C)(C)Oc2ccc(OCCCC(F)(F)F)cc12)S(C)(=O)=O

-1.1000 -1.0206 9.1115 No

172.

Training CCCCN(CCCC)CC[C@@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.3980 1.6195 0.0741 YES

173.

Training CCCCN(CCCC)CC[C@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.3980 1.5312 0.0716 YES

174.

Training OC1(CCN(CCCC(=O)c2ccc(F)cc2)CC1)c1ccc(Cl)cc1

1.5230 1.4795 0.0427 YES

175.

Training COc1ccc(cc1O)[C@H]1CC(=O)c2c(O)cc(O)cc2O1

-2.4610 -1.9983 1.0778 YES

176.

Training CC(C)N[C@H](C)[C@H](O)COc1ccc(C)c2CCCc12

-0.9640 -1.2174 1.0700 YES

177.

Training CCCCCCCN(CC)CCC[C@@H](O)c1ccc(NS(C)(=O)=O)cc1

1.6990 1.5787 7.0562 YES

178.

Training CCCCCCCN(CC)CCC[C@H](O)c1ccc(NS(C)(=O)=O)cc1

1.6990 1.4904 7.0537 YES

179.

Calibration CN(C)CCCN1c2ccccc2CCc2ccccc12

-0.5310 -0.2009 0.0277 YES

180.

Training CCCCC1=NC2(CCCC2)C(=O)N1Cc1ccc(cc1)-c1ccccc1-c1nn[nH]n1

-2.2860 -2.2788 12.0569 No

181.

Training CC(C)Cn1c2nc[nH]c2c(=O)n(C)c1=O

-1.0000 -1.0096 7.0357 YES

182.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationC)c1

-0.1490 -0.2394 0.0646 YES

183.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNS(=O)(=O)c2ccccc2)c1

-0.6880 -0.7008 9.0823 No

184.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-

-0.4390 -0.0965 2.0882 YES

c2csc(c2)CCalibrationCCNC(=O)Oc2ccccc2)c1

185.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNC(=O)Nc2ccccc2)c1

-0.8980 -1.2110 3.0822 YES

186.

Training CCCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12

-0.2550 -0.2505 16.0581 No

187.

Validation COCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12

-0.7150 -0.8704 16.0602 No

188.

Calibration CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCCOc2ccccc2)c1

0.3470 0.0088 0.0820 YES

189.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2Cl)c1

0.1020 0.1053 3.0864 YES

190.

Calibration CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccc(Cl)c2)c1

-0.4130 -0.0058 0.0900 YES

191.

Validation CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(Cl)cc2)c1

-0.5550 -0.1567 0.0900 YES

192.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(C)c(C)c2)c1

-0.3980 -0.0742 0.0844 YES

193.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccnc2)c1

-0.5300 -1.1840 0.0859 YES

194.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCCc2ccccc2)c1

-0.6810 -0.1222 0.0749 YES

195.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNc2ccccc2)c1

-0.2430 -0.4058 2.0721 YES

196.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNC(=O)c2ccccc2)c1

-0.8730 -0.1919 2.0817 YES

197.

Calibration CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-

-0.2410 -0.1669 0.0781 YES

c2csc(c2)CCalibrationCCOc2ccccc2)c1

198.

Training CN1CCN(CC1)CCc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.7690 -0.4157 0.0820 YES

199.

Training CC1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

1.0970 0.7106 0.0790 YES

200.

Training CN1CCC(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.3220 0.0179 0.0792 YES

201.

Training O=CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.7290 -0.7193 4.0848 YES

202.

Training CN1CCN(CC1)C(=O)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.2360 -0.9744 2.0842 YES

203.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.0450 -0.3185 0.0808 YES

204.

Training C(Oc1ccccc1)CCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(cc3Cc12)-n1ccnc1

-0.1550 -0.0934 8.0786 No

205.

Training CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(CN3CCOCC3)cc2)c1

-0.4080 -0.4768 0.1021 YES

206.

Training COCCOCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(cc3Cc12)N1CCN(C)CC1

-0.9630 -0.9249 7.0683 YES

207.

Training CN1CCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.0220 -0.3946 0.0700 YES

208.

Validation CN(C)[C@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.2220 0.1964 0.1006 YES

209.

Training CCN[C@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.3770 -0.0205 1.0995 YES

210.

Training CN(C)CC1CCN(CC1)CC(=O)Nc1cc(nc(n1)-

-0.2230 0.5833 0.0737 YES

c1ccc(C)o1)-n1nc(C)cc1C

211.

Training CN(C)C[C@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.2700 -0.0876 0.1008 YES

212.

Calibration CN(C)C[C@@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.0040 0.0007 0.1033 YES

213.

Calibration CN(C)CCC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.1870 0.2526 0.0644 YES

214.

Training CN(C)[C@H]1CCN(CCC(=O)Nc2cc(nc(n2)-c2ccc(C)o2)-n2nc(C)cc2C)C1

-0.3580 -0.3718 9.0903 No

215.

Training CN1CCC(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.6200 -0.2098 0.0711 YES

216.

Training CN1CCCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.5380 -0.0672 0.0712 YES

217.

Training CC(C)(Oc1ccc(Cl)cc1)C(=O)N[C@H]1[C@H]2C[C@H]3C[C@@H]1C[C@](C3)(C2)NS(C)(=O)=O

-1.1020 -1.1051 13.1890 No

218.

Training Coc1ccc(CCN(C)CCOc2ccc(NS(C)(=O)=O)cc2N)cc1OC

-0.0000 0.1066 7.0561 YES

219.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.2687 11.1017 No

220.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.1804 11.1042 No

221.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.4256 11.0979 No

222.

Validation CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.3373 11.1004 No

223.

Validation CN1C(=O)[C@H](NC(=O)Nc2cccc(C)c2)N=C(c2ccccc2)c2ccccc12

-0.6990 -0.7710 4.0611 YES

224.

Training CN1C(=O)[C@@H](NC(=O)Nc2cccc(C)c2)N

-0.6990 -0.6827 4.0636 YES

=C(c2ccccc2)c2ccccc12 225.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CCc4ccc5nonc5c4)CC3)CC(=O)c2c1

2.0000 2.0205 21.0856 No

226.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@@H]3CCc4cc(ccc4C3)CCalibrationN)CC(=O)c2c1

2.0000 1.5735 16.1051 No

227.

Training FC(F)(F)CN1C(=O)[C@H](NC(=O)Cc2ccc(cc2C(F)(F)F)C(F)(F)F)N=C(c2ccccc2)c2ccccc12

-0.7780 -0.8486 3.1115 YES

228.

Training FC(F)(F)CN1C(=O)[C@@H](NC(=O)Cc2ccc(cc2C(F)(F)F)C(F)(F)F)N=C(c2ccccc2)c2ccccc12

-0.7780 -0.7603 3.1140 YES

229.

Training CCCCCCCN(CC)CCCCc1ccc(cc1)[N+]([O-])=O

1.5230 1.6153 8.0508 No

230.

Training C[C@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-2.9610 -3.0483 0.0912 YES

231.

Training C[C@@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-2.9610 -2.9600 0.0937 YES

232.

Training Cc1cccc(C)c1NC(=O)CN1CCN(CCCC(c2ccc(F)cc2)c2ccc(F)cc2)CC1

1.6990 1.5411 0.0456 YES

233.

Training CCN(CC)CC(=O)Nc1c(C)cccc1C

-2.4200 -2.5249 0.0185 YES

234.

Training CCCCC\C=C/C\C=C/CCCCCCCC(N)=O

-0.6990 -0.7043 25.0387 No

235.

Training CCn1cc(C(O)=O)c(=O)c2cc(F)c(N3CCN[C@H](C)C3)c(F)c12

-3.3800 -3.4150 3.0707 YES

236.

Training CCn1cc(C(O)=O)c(=O)c2cc(F)c(N3CCN[C@@H](C)C3)c(F)c12

-3.3800 -3.3268 3.0732 YES

237.

Training CCOC(=O)N1CC\C(CC1)=C1/c2ccc(Cl)cc2CCc2cccnc12

-0.6020 -0.5738 16.0452 No

238.

Training CCCCN(CCCC)C[C@@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.9100 -0.9331 16.0671 No

Training CCCCN(CCCC)C[C@H] -0.9100 -1.0214 16.0646 No

239. (O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

240.

Validation CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.4420 16.1229 No

241.

Validation CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.5303 16.1254 No

242.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@H](O)c2c1

0.9210 1.3537 16.1204 No

243.

Validation CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@H](O)c2c1

0.9210 1.4420 16.1229 No

244.

Training CNCCC[C@]12CC[C@@H](c3ccccc13)c1ccccc21

-0.7160 -0.7096 7.0680 YES

245.

Training O[C@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3460 0.1103 YES

246.

Calibration O[C@H]([C@@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.2577 0.1128 YES

247.

Calibration O[C@@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.2577 0.1128 YES

248.

Calibration O[C@@H]([C@@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.1694 0.1153 YES

249.

Training CCOC(=O)C1(CCN(C)CC1)c1ccccc1

-1.8750 -1.4261 0.0261 YES

250.

Training CN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-2.1940 -2.0181 0.0544 YES

251.

Validation CN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-2.1940 -2.1064 0.0519 YES

Training CN1CCCC[C@H]1CCN1c 0.4950 0.4993 9.0723 No

252. 2ccccc2Sc2ccc(cc12)S(C)=O

253.

Validation CN1CCCC[C@@H]1CCN1c2ccccc2Sc2ccc(cc12)S(C)=O

0.4950 0.5876 9.0748 No

254.

Validation CCC(=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -1.4998 0.0493 YES

255.

Calibration CCC(=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -1.4115 0.0518 YES

256.

Training CCN(CC)CCNC(=O)c1cc(Cl)c(N)cc1OC

-0.7320 -1.6383 0.0319 YES

257.

Validation CC(C)NC[C@H](O)COc1ccc(CCO)cc1

-2.1610 -1.3100 0.0454 YES

258.

Validation CC(C)NC[C@@H](O)COc1ccc(CCO)cc1

-2.1610 -1.2217 0.0478 YES

259.

Training COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@H]1C(C)C

-0.1550 -0.1624 0.1363 YES

260.

Calibration COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.0741 0.1388 YES

261.

Training COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@H]1C(C)C

-0.1550 -0.1824 0.1351 YES

262.

Calibration COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.0941 0.1376 YES

263.

Training Clc1ccc(CO[C@@H](Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

-0.3220 -0.3085 6.0643 YES

264.

Training Clc1ccc(CO[C@H](Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

-0.3220 -0.3968 6.0618 YES

265.

Training Oc1ccc(c(O)c1)-c1oc2cc(O)cc(O)c2c(=O)c1O

-2.0470 -2.0582 2.0386 YES

266.

Training CCOc1cc(N)c(Cl)cc1C(=O)NC[C@H]1CN(CCO1)Cc1ccc(F)cc1

-0.6020 -0.6260 1.0821 YES

267.

Validation CCOc1cc(N)c(Cl)cc1C(=O)NC[C@@H]1CN(CCO1)Cc1ccc(F)cc1

-0.6020 -0.5377 1.0846 YES

268.

Training CCCCCCCCCC[N+](CC)(CC)CC

-0.5560 -0.6232 0.0402 YES

269.

Calibration NC[C@H](O)COc1ccccc1C(=O)CCc

-0.7620 -1.1523 0.0520 YES

1ccccc1 270.

Calibration NC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.7620 -1.0640 0.0545 YES

271.

Training CCCCNCC[C@@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.8155 0.0701 YES

272.

Calibration CCCCNCC[C@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.7272 0.0677 YES

273.

Training Clc1ccc2N=c3ccccc3=C(Nc2c1)N1CCNCC1

-0.6520 -0.6650 6.0469 YES

274.

Training Cc1cc2c(Nc3ccccc3N=C2N2CCNCC2)s1

-1.1520 -1.1527 5.0661 YES

275.

Training CCCCCCCC[N+](CC)(CC)CC

-0.9240 -1.2779 0.0379 YES

276.

Training CCCCCCCC[N+](C)(C)C -2.5020 -2.0881 0.0364 YES

277.

Calibration Oc1ccc(cc1)[C@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -2.1117 0.0745 YES

278.

Training Oc1ccc(cc1)[C@@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -2.0235 0.0769 YES

279.

Training CN1CCC[C@H]1c1cccnc1

-2.3890 -2.4613 3.0403 YES

280.

Training CN1CCC[C@@H]1c1cccnc1

-2.3890 -2.3730 3.0428 YES

281.

Training Cn1c(NCCN(CCO)CCCc2ccc(cc2)[N+]([O-])=O)cc(=O)n(C)c1=O

-0.8980 -0.9993 12.0593 No

282.

Training COC(=O)C1=C(C)NC(C)=C([C@H]1c1ccccc1[N+]([O-])=O)C(=O)OCC(C)C

-1.3620 -1.4189 13.0956 No

283.

Training COC(=O)C1=C(C)NC(C)=C([C@@H]1c1ccccc1[N+]([O-])=O)C(=O)OCC(C)C

-1.3620 -1.3306 13.0981 No

284.

Training CC[C@@H](OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.7996 0.0719 YES

285.

Training CC[C@H](OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.8879 0.0694 YES

286.

Validation CC[C@@H](OC(C)=O)C(C[C@@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.7113 0.0744 YES

287.

Validation CC[C@H](OC(C)=O)C(C[C@@H]

-1.0790 -0.7996 0.0719 YES

(C)NC)(c1ccccc1)c1ccccc1

288.

Training Fc1ccc(Cn2c(NC3CCNCC3)nc3ccccc23)cc1

1.5230 1.6026 7.0424 YES

289.

Calibration CCC(=O)O[C@](Cc1ccccc1)([C@H](C)CNC)c1ccccc1

-0.5600 -0.9716 0.0783 YES

290.

Training CCC(=O)O[C@](Cc1ccccc1)([C@@H](C)CNC)c1ccccc1

-0.5600 -0.8833 0.0808 YES

291.


-0.5600 -1.1285 0.0746 YES

292.


-0.5600 -1.0402 0.0771 YES

293.

Calibration Coc1ccc(CCNCCC[C@](CCalibrationN)(C(C)C)c2ccc(OC)c(OC)c2)cc1OC

-0.5800 0.0622 0.0857 YES

294.

Training Coc1ccc(CCNCCC[C@@](CCalibrationN)(C(C)C)c2ccc(OC)c(OC)c2)cc1OC

-0.5800 -0.0947 0.0819 YES

295.

Validation C[C@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-3.1520 -3.0483 0.0912 YES

296.

Calibration C[C@@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-3.1520 -2.9600 0.0937 YES

297.

Training CN1CCN(CC1)C1=c2cc(C)sc2=Nc2ccccc2N1

0.6380 0.6245 7.0458 YES

298.

Training Cc1nccn1C[C@@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0943 0.0814 YES

299.

Calibration Cc1nccn1C[C@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0060 0.0789 YES

300.

Training CN(C)CCO[C@@H](c1ccccc1)c1ccccc1C

0.0710 0.2257 1.0425 YES

301.

Training CN(C)CCO[C@H](c1ccccc1)c1ccccc1C

0.0710 0.1374 1.0400 YES

302.

Training COc1ccc(Cc2nccc3cc(OC)c(OC)cc23)cc1OC

-0.8630 -1.0307 1.0446 YES

303.

Training [H]\N=C(/N)c1ccc(OCCCCCOc2ccc(cc2)C(\N)=N\[H])cc1

-2.4010 -2.4196 28.0559 No

304.

Training C1CCC(CC1)C(C[C@H]1CCCCN1)C1CCCCC1

-0.8920 -1.2022 0.0645 YES

305.

Validation C1CCC(CC1)C(C[C@@H]1CCCCN1)C1CCCCC1

-0.8920 -1.1139 0.0670 YES

306.

Training OCCN1CCN(CCCN2c3ccccc3Sc3ccc(Cl)cc23)CC1

-0.0000 0.0597 7.0369 YES

Training CCC1(C(=O)NC(=O)NC1= -3.4770 -3.6751 0.0223 YES

307. O)c1ccccc1 308.

Training O=C1NC(=O)C(N1)(c1ccccc1)c1ccccc1

-2.3800 -2.3545 2.0305 YES

309.

Training Cc1cccc(C)c1NC(=O)CC12CCCN1CCC2

-1.3100 -1.4626 2.0268 YES

310.

Training Fc1ccc(cc1)C(CCCN1CCC(CC1)n1c2ccccc2[nH]c1=O)c1ccc(F)cc1

1.3010 1.3424 4.0469 YES

311.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)c1ccco1

-0.1960 -0.1884 2.0514 YES

312.

Training CCN(CC)CCNC(=O)c1ccc(N)cc1

-2.1430 -1.6818 0.0183 YES

313.

Validation CCCNC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.3010 -0.0888 0.0574 YES

314.

Calibration CCCNC[C@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.3010 -0.1771 0.0549 YES

315.

Training CNCCCC1c2ccccc2CCc2ccccc12

-0.0720 -0.4952 0.0292 YES

316.

Training COCCCN1CCC(CC1)NC(=O)c1cc(Cl)c(N)c2CCOc12

-0.7560 -0.7278 0.0467 YES

317.

Validation COc1ccc(CN(CCN(C)C)c2ccccn2)cc1

-0.7780 -0.6181 1.0286 YES

318.

Training OCCOCCN1CCN(CC1)C1=Nc2ccccc2Sc2ccccc12

-0.7610 -0.8607 6.0382 YES

319.

Training Cc1ccc(cc1C)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.6990 1.6021 0.0704 YES

320.

Calibration Cc1ccc(cc1C)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.6990 1.6904 0.0729 YES

321.

Training O[C@@H](CCCN1CCC(O)(CC1)c1ccc(Cl)cc1)c1ccc(F)cc1

-0.4150 -0.4934 0.0566 YES

322.

Training O[C@H](CCCN1CCC(O)(CC1)c1ccc(Cl)cc1)c1ccc(F)cc1

-0.4150 -0.5817 0.0542 YES

323.

Training COc1cc(N)c(Cl)cc1C(=O)N[C@H]1CCN2CCC[C@@H]1C2

-0.2550 0.0279 3.1025 YES

324.

Calibration Cc1nc2CCCCn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

0.8240 -0.4276 0.0617 YES

325.

Training CC(C)[C@H](NC(=O)N(C)Cc1csc(n1)C(C)C)C(=O)N[C@H](C[C@H](O)[C@H](Cc1ccccc1)NC(=O)OCc1cncs1)Cc1ccccc1

-0.9140 -0.8870 7.1523 YES

326.

Validation CCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.4470 -1.5673 0.0560 YES

327.

Training Coc1ccc(CCNCCCNC(=O)c2ccc(cc2)[N+]([O-])=O)cc1OC

0.3770 -0.0492 9.0637 No

328.

Training CCN(CC)CCNC(=O)c1ccc(NS(C)(=O)=O)cc1

-1.6990 -1.2944 7.0308 YES

329.

Training Fc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

2.0000 1.6759 6.0562 YES

330.

Training CCCc1nn(C)c2c1[nH]c(nc2=O)-c1cc(ccc1OCC)S(=O)(=O)N1CCN(C)CC1

-0.5190 -0.4983 15.0731 No

331.

Training CC\C(c1ccccc1)=C(\c1ccccc1)c1ccc(OCCN(C)C)cc1

-1.6560 -1.7041 14.0277 No

332.

Training CC\C(c1ccccc1)=C(/c1ccccc1)c1ccc(OCCN(C)C)cc1

-1.6560 -1.6693 14.0277 No

333.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1CCCO1

-1.2480 -1.2985 0.0858 YES

334.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1CCCO1

-1.2480 -1.2102 0.0883 YES

335.

Calibration CC(C)(C)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 0.5779 0.0628 YES

336.

Calibration CC(C)(C)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 0.6662 0.0653 YES

337.

Calibration COc1ccc(cc1OC)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.5230 1.6528 0.0781 YES

338.

Training COc1ccc(cc1OC)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.5230 1.7411 0.0806 YES

339.

Training C[C@@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.2138 0.0437 YES

340.

Validation C[C@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.3021 0.0412 YES

341.

Validation CSc1ccc2Sc3ccccc3N(CC[C@H]3CCCCN3C)c2c1

0.4090 0.3208 8.0642 No

342.

Training CSc1ccc2Sc3ccccc3N(CC[C@@H]3CCCCN3C)c2c1

0.4090 0.4091 8.0667 No

Validation COc1ccc(CNC[C@H] 0.0180 -0.0410 1.0862 YES

343. (O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

344.

Training COc1ccc(CNC[C@@H](O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

0.0180 0.0473 1.0887 YES

345.

Training CC(C)N(CC[C@@H](c1ccccc1)c1cc(C)ccc1O)C(C)C

1.6990 1.2772 2.0480 YES

346.

Validation CC(C)N(CC[C@H](c1ccccc1)c1cc(C)ccc1O)C(C)C

1.6990 1.1889 2.0455 YES

347.

Training Clc1cccc(c1)N1CCN(CCCn2nc3ccccn3c2=O)CC1

-0.4620 -0.4850 7.0381 YES

348.

Training S1c2ccccc2N(CCC[N+]2CC[N+](C)CC2)C2CC(CCC12)C(F)(F)F

-0.1490 -0.1039 5.0996 YES

349.

Training CCCc1nc(C)c2n1[nH]c(nc2=O)-c1cc(ccc1OCC)S(=O)(=O)N1CCN(CC)CC1

-1.1070 -1.1052 12.0787 No

350.

Training Coc1ccc(cc1OC)[C@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.8539 1.0797 YES

351.

Validation Coc1ccc(cc1OC)[C@@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.6970 1.0760 YES

352.

Training COc1ccc(cc1OC)C(=O)N1CCN(CC1)c1ccc2NC(=O)CCc2c1

-0.0250 -0.0729 1.0465 YES

353.

Training CC(C)CCCC(C)CCCC(C)CCC\C(C)=C\CC1=C(C)C(=O)c2ccccc2C1=O

-0.7600 -0.7151 15.0468 No

354.

Training CN1Cc2ccccc2[C@H](N=C1CCc1ccccc1)c1ccccc1

1.0460 1.0226 4.0502 YES

355.

Training CN1Cc2ccccc2[C@@H](N=C1CCc1ccccc1)c1ccccc1

1.0460 1.1109 4.0527 YES

356.

Training COc1ccc(NC(=O)c2ccc(cc2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

-0.2550 -0.1951 0.0689 YES

357.

Calibration COc1ccc(NC(=O)c2ccc(cc2F)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

-0.3220 -0.0474 0.0704 YES

358.

Calibration COc1ccc(NC(=O)c2ccc(cc2N2CCCCC2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

0.6990 0.7583 0.0892 YES

359.

Training CN(C)C(=N)c1ccc(cc1)C(=O)Nc1ccc(Cl)cc1C(=O)Nc1ccc(Cl)cn1

0.9590 0.6202 0.0487 YES

360.

Training CN(C)C(=N)c1ccc(C(=O)Nc2ccc(Cl)cc2C(=O)Nc2ccc(Cl)cn2)c(F)c1

0.3770 0.6695 3.0523 YES

361.

Training Cc1ncc(C)c(n1)C(=O)N1CCC(CC1)[C@H](N)Cc1cc(F)c(F)cc1F

-1.9290 -1.9618 3.0677 YES

362.

Training Cc1nccnc1C(=O)N1CCC(CC1)[C@H](N)Cc1cc(F)c(F)cc1F

-1.7400 -1.5567 4.0664 YES

363.

Training N[C@H](Cc1cc(F)c(F)cc1F)C1CCN(CC1)C(=O)c1cnc2ncccn12

-1.7710 -1.7555 5.0686 YES

364.

Training Cc1cc2ncc(C(=O)N3CCC(CC3)[C@H](N)Cc3cc(F)c(F)cc3F)c(C)n2n1

-1.2550 -1.2518 6.0791 YES

365.

Training C1C[C@@H](CN1)OCc1ccc2ccccc2c1

-1.1960 -1.0159 2.0460 YES

366.

Training C1C[C@H](CN1)OCc1ccc2ccccc2c1

-1.2150 -1.1041 2.0435 YES

367.

Training NCalibrationCc1ccc2cc(CO[C@H]3CCNC3)ccc2c1

-0.6530 -0.7348 2.0558 YES

368.

Training Fc1ccc2cc(CO[C@@H]3CCNC3)ccc2c1

-1.0130 -0.9930 3.0545 YES

369.

Training CCCCN(C1CCNCC1)S(=O)(=O)c1ccc2ccccc2c1

0.1430 0.1698 7.0378 YES

370.

Training CCCCN([C@H]1CCNC1)S(=O)(=O)c1ccc2ccccc2c1

0.3850 0.3042 8.0621 No

371.

Training C1CC(CCN1)COc1ccc2ccccc2c1

-0.5800 -0.7139 0.0309 YES

372.

Training Cc1ccc2ccc(OCC3CCNCC3)cc2c1

-0.5440 -0.4413 1.0394 YES

373.

Training Fc1ccc2cc(OCN3CCNCC3)ccc2c1

-0.5440 -0.5285 3.0353 YES

374.

Training Cc1c(CCN2CCNCC2)ccc2cc(F)ccc12

-1.0040 -0.4685 1.0284 YES

375.

Training Clc1ccccc1OC1CN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.5330 -0.3444 9.0533 No

376.

Training Clc1cccc(OC2CN(C2)S(=O)(=O)c2ccc3CCNCCc3c2)c1

-0.5670 -0.4244 12.0563 No

377.

Training Clc1ccc(OC2CN(C2)S(=O)(=O)c2ccc3CCNCCc3c2)cc1

-0.3200 -0.4336 12.0563 No

378.

Validation Clc1ccccc1C[C@@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.5350 -1.2571 9.0774 No

379.

Validation Clc1ccccc1C[C@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.7190 -1.3454 9.0750 No

380.

Training Clc1ccccc1OC1CCN(CC1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.4620 -0.5329 9.0542 No

381.

Training FC1(F)CCN(C1)C(=O)[C@@H]1C[C@@H](CN1)N1CCN(CC1)c1ncccn1

-2.1000 -2.1744 2.1004 YES

382.

Validation F[C@H]1CN(C[C@H]1F)C(=O)[C@@H]1C[C@@H](CN1)N1CCN(CC1)c1ncccn1

-1.7320 -2.8805 2.1419 YES

383.

Training CC(C)(C)CNc1nc(nc(N2CCOCC2)c1N)CCalibrationN

-1.8450 -1.8916 1.0437 YES

384.

Training CC(C)CNc1nc(nc(N2CCNCC2)c1N)CCalibrationN

-1.7160 -1.6506 1.0394 YES

385.

Training Nc1ccnc(c1)N1CCC(CC1)(C(=O)Nc1ccc2ccccc2n1)c1ccccc1

1.6990 1.7916 0.0464 YES

386.

Calibration CCOC(=O)N1CCN(CC1)C(=O)C1(CCN(CC1)c1cc(N)ccn1)c1ccccc1

0.7700 -0.5054 0.0507 YES

387.

Training Nc1ccnc(c1)N1CCC(CC1)(C(=O)N1CCc2ccccc2C1)c1ccccc1

1.3980 1.1699 1.0432 YES

388.

Training COc1ccc(CNC(=O)C2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)cc1

0.6990 0.7396 1.0548 YES

389.

Training COc1ccc(C(=O)NC2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)c(OC)c1

1.0970 0.6324 2.0538 YES

390.

Validation COc1ccc(C(=O)NC2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)c(Cl)c1

0.4690 0.3756 2.0557 YES

391.

Training Nc1ccnc(c1)N1CCC(CC1)(NC(=O)c1ccccn1)c1ccccc1

0.2600 -0.0868 0.0475 YES

392.

Training COc1ccc(cc1)C(=O)N(C1CCN(CC1)c1cc(N)ccn1)c1ccc(C)cn1

1.5230 1.0904 0.0545 YES

393.

Training COc1cccc(c1)C(=O)N(C1CCN(CC1)c1cc(N)ccn1)c1ccccn1

-0.9860 -0.1603 0.0524 YES

394.

Training Nc1ccnc(c1)N1CCC2(CC1)OC(c1ccccc1)c1ccccc2

1.6990 1.7634 2.0394 YES

1 395.

Training CN(C)C(=O)[C@H]1OC2(CCN(CC2)c2cc(N)ccn2)c2ccccc12

-0.6730 -0.7259 2.0721 YES

396.

Training COc1cccc(c1)C1(C)CN(C1)c1cc(N)ccn1

-0.2650 -0.6574 0.0385 YES

397.

Training COc1ccc(cc1)-n1c2cccnc2n(C2CCN(CC2)c2cc(N)ccn2)c1=O

0.0600 0.1201 1.0684 YES

398.

Training Nc1ccnc(c1)N1CCC(CC1)n1c2ncccc2n(-c2ccccc2)c1=O

0.0460 0.2412 1.0536 YES

399.

Training Nc1ccnc(c1)N1CCC(CC1)n1c2ncccc2n(Cc2ccccc2)c1=O

0.2840 0.0808 0.0505 YES

400.

Calibration Nc1ccnc(c1)N1CCC(CC1)n1c2ncccc2n(CC2CC2)c1=O

0.1250 -1.0309 0.0520 YES

Distribution 2 Eq. 4

1.

Calibration Fc1ccc(cc1)C(N1CCNCC1)c1ccc(F)cc1

-0.2040 -0.8128 0.0238 YES

2.

Calibration CN1CCN(CC1)C1=Nc2ccccc2Nc2sc(CO)cc12

-1.0640 -1.4606 0.0656 YES

3.

Training Fc1ccc(cc1)C(=O)c1ccc(F)cc1

-1.8570 -1.9525 0.0227 YES

4.


-1.9960 -2.4674 0.0246 YES

5.


6.


-0.6990 -0.6962 11.0390 No

7.

Training CCCNC[C@@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.3997 0.0506 YES

8.

Training CCCNC[C@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.3474 0.0382 YES

9.


-0.1140 -0.1497 6.0737 No

10.

Training Cc1nc2CC[C@H](O)Cn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

-0.1140 -0.0975 6.0613 No

11.

Training CC[C@@H](OC(C)=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8906 0.0630 YES

12.

Validation CC[C@H](OC(C)=O)C(C[C@H](C)N(C)C)

-0.4770 -0.8384 0.0505 YES

(c1ccccc1)c1ccccc1 13.

Validation CC[C@@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.9428 0.0754 YES

14.

Calibration CC[C@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8906 0.0630 YES

15.


-0.5560 -0.5937 7.0818 No

16.


-0.4470 -0.4315 20.0240 No

17.


-1.0000 -0.9921 14.0188 No

18.


0.6780 0.7759 6.0359 No

19.


-2.3500 -2.2747 2.0454 YES

20.

Training CCCN[C@@H](C)C(=O)Nc1c(C)csc1C(=O)OC

-2.3500 -2.3270 2.0578 YES

21.

Training COc1ccc(CCN2CCC(CC2)Nc2nc3ccccc3n2Cc2ccc(F)cc2)cc1

-0.0000 -0.0786 3.0577 YES

22.


0.2520 0.1944 1.0727 YES

23.


0.2150 0.2061 17.0629 No

24.


-0.1140 -0.2120 5.0918 YES

25.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-0.9080 -0.7283 0.0388 YES

26.


-0.5190 -1.1119 0.0310 YES

27.

Calibration CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccc(c2)C(F)(F)F)CC1=O

-0.2300 -0.2440 0.0517 YES

Training CCN(CC)Cc1ccc2CC(CCc -0.5190 -0.0911 0.0329 YES

28. 2c1)N1CCN(CCC2CCCCC2)CC1=O

29.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccs2)CC1=O

-1.1210 -1.1413 2.0438 YES

30.

Validation Fc1ccc(CCN2CCN(C3CCc4cc(CN5CCC(CC5)C(F)(F)F)ccc4C3)C(=O)C2)cc1

-0.3010 -0.1291 9.0708 No

31.

Training Fc1ccc(CCN2CCN(C3CCc4cc(Cn5ccnc5)ccc4C3)C(=O)C2)cc1

-0.6020 -0.5500 8.0559 No

32.


-1.0410 -1.1140 10.0544 No

33.

Validation CS(=O)(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.1140 -1.4621 1.0570 YES

34.


-1.3800 -1.4040 12.0642 No

35.

Calibration CC(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -1.3868 0.0466 YES

36.

Calibration CN(C)C(=O)C(CO)N(C)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -1.7289 0.0483 YES

37.

Training Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)-c1ccccc1

1.0460 1.0464 4.0394 YES

38.

Training Fc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=S)c2ccccc12

2.0000 1.9916 6.0510 No

39.

Calibration CC(C)(O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.1865 0.0459 YES

40.

Training CC(C)(O)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.1343 0.0583 YES

41.

Training Fc1ccc(cc1)N1C[C@@H](C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

1.6990 1.6574 0.0672 YES

42.

Training Fc1ccc(cc1)N1C[C@H](C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

1.6990 1.7096 0.0548 YES

43.


0.6990 0.8829 0.0367 YES

Training CN(C)Cc1cn(- 2.0000 0.5115 0.0343 YES

44. c2ccc(F)cc2)c2ccc(Cl)cc12

45.


-1.4150 -0.6775 1.0307 YES

46.

Training CCC(CC)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.1700 -0.5013 1.0307 YES

47.

Validation C[C@@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.6580 -0.4514 0.0580 YES

48.

Calibration C[C@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.6580 -0.3992 0.0456 YES

49.

Validation CCC(=O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.2900 -0.0060 0.0378 YES

50.


2.0000 1.9291 4.0564 YES

51.


-1.1960 -0.6109 0.0379 YES

52.

Training CC[C@@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.3420 -0.0600 0.0583 YES

53.


-0.3420 -0.0077 0.0458 YES

54.


-0.5440 -1.0024 1.0305 YES

55.


2.0000 1.3423 0.0512 YES

56.


0.2370 0.1337 0.0570 YES

57.


-1.8750 -0.1753 0.0537 YES

58.

Validation Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)C1CCCCC1

0.8540 1.4311 4.0343 YES

59.

Calibration COC(=O)Cc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

0.8860 0.6418 0.0598 YES

60.


1.3980 0.3328 0.0565 YES

61.

Training COc1ccc(CCN(C)CCCN(C(=O)c2ccc(cc2)[N+]

1.6990 2.0252 9.0575 No

([O-])=O)c2ccc(OC)c(OC)c2)cc1OC

62.

Validation COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1523 0.1452 YES

63.

Training COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1001 0.1328 YES

64.

Calibration COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1001 0.1328 YES

65.

Validation COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.0479 0.1204 YES

66.


-0.0000 -0.0410 0.0599 YES

67.


0.2600 0.4300 0.0453 YES

68.

Training CC(C)COC[C@H](CN(Cc1ccccc1)c1ccccc1)N1CCCC1

0.2600 0.4823 0.0328 YES

69.


-0.4910 -0.4750 16.0515 No

70.


-1.7970 -1.6332 2.0671 YES

71.


-0.0000 -0.0136 11.0510 No

72.


1.5230 1.5224 6.0633 No

73.

Training CN(C)CC[C@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.2452 9.0254 No

74.

Validation CN(C)CC[C@@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.2975 9.0379 No

75.

Training CC(C)(C)N1CCC(CC1)(c1ccccc1)c1ccccc1

-1.0090 -0.5794 0.0238 YES

76.

Calibration CCCCN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.2358 0.0343 YES

77.

Training CCCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.2880 0.0468 YES

78.


-0.4100 -0.3797 3.0308 YES

Training Cn1cnc2n(C)c(=O)n(C)c( -0.6900 -0.6916 8.0305 No

79. =O)c12 80.


-2.4000 -2.4149 4.0207 YES

81.


0.2920 0.2962 0.0940 YES

82.

Calibration COc1ccccc1OCCNC[C@H](O)COc1cccc2[nH]c3ccccc3c12

0.2920 0.3485 0.0816 YES

83.


84.


-0.1930 0.1429 4.0159 YES

85.

Training CCN(CC)CCC[C@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 -0.3386 0.0322 YES

86.

Training CCN(CC)CCC[C@@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 -0.3908 0.0446 YES

87.


-1.1140 -0.9218 1.0386 YES

88.

Training CN(C)CC[C@H](c1ccc(Cl)cc1)c1ccccn1

-1.1140 -0.8695 1.0262 YES

89.

Training C1CN=C(N1)[C@@H]1CC1(c1ccccc1)c1ccccc1

-0.5680 -0.5884 1.0528 YES

90.


-0.5680 -0.5362 1.0404 YES

91.


-2.9850 -2.9727 1.0477 YES

92.


2.0000 2.1766 0.0797 YES

93.

Training CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.1243 0.0921 YES

94.

Validation CO[C@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.1243 0.0921 YES

95.

Calibration CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.0721 0.1046 YES

96.

Training CN(C)CCC[C@]1(OCc2cc(ccc12)CCalibrationN)c1ccc(F)cc1

-0.6000 -0.6045 4.0445 YES

97.


-0.6000 -0.5398 4.0566 YES

98.

Training COc1cc(N)c(Cl)cc1C(=O)NC1CCN(CC1)Cc1ccccc1

0.2080 0.1365 0.0282 YES

99.


2.0000 1.6228 0.0578 YES

100.

Validation CN1CCC[C@@H]1CCO[C@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.5706 0.0702 YES

101.

Calibration CN1CCC[C@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.5710 0.0689 YES

102.

Calibration CN1CCC[C@@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.5188 0.0813 YES

103.

Calibration CCCCCCC[N+](CC)(CC)CCCCc1ccc(Cl)cc1

0.6020 0.3733 0.0275 YES

104.


0.7450 0.8120 14.0226 No

105.


0.7450 0.7621 14.0226 No

106.


0.4950 0.5488 4.0300 YES

107.

Training CN1CCN(CC1)[C@H]1N(O)c2cc(Cl)ccc2Nc2ccccc12

-2.1250 -2.2170 0.0484 YES

108.

Calibration CCOC(=O)[C@H]1[C@H](C[C@H]2CC[C@@H]1N2C)OC(=O)c1ccccc1

-0.6020 -0.8791 0.1103 YES

109.


-0.7480 -0.8209 0.1093 YES

110.

Validation C[C@@H](CN(C)C)CN1c2ccccc2Sc2ccc(cc12)CCalibrationN

0.3280 0.0743 5.0445 YES

111.


0.3280 0.1265 5.0321 YES

112.


-1.5210 -0.9853 0.0734 YES

113.


-1.5210 -1.0375 0.0858 YES

114.


-1.5210 -1.0370 0.0844 YES

115.

Calibration CCC(=O)O[C@@](Cc1ccccc1)([C@@H](C)CNC)c1ccccc1

-1.5210 -1.0893 0.0969 YES

116.

Training Coc1ccc(CCN(C)CCC[C@](CCalibrationN)(C(C)C)c2ccc(O)c(O)c2)c

-0.3420 -0.4360 5.0385 YES

c1OC 117.


-0.3420 -0.4877 5.0496 YES

118.


-0.7850 -0.4797 1.0512 YES

119.

Training COc1ccc(CCN[C@H](C)COc2c(C)cccc2C)cc1OC

-0.7850 -0.4274 1.0388 YES

120.

Validation COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1467 0.1627 YES

121.

Training COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1989 0.1751 YES

122.

Calibration COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.2512 0.1875 YES

123.

Training COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1989 0.1751 YES

124.


-0.0000 0.1133 3.0560 YES

125.

Training Cc1cc2=C(Nc3ccccc3N=c2s1)N1CCNCC1

-1.1520 -1.1618 10.0443 No

126.


-0.7400 -0.7809 16.0514 No

127.

Training CCCCNC[C@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.7400 -0.7286 16.0389 No

128.

Training CNCCCN1c2ccccc2CCc2ccccc12

-0.1430 -0.1461 1.0143 YES

129.

Training Clc1ccc2c(CCc3cccnc3\C2=C2/CCNCC2)c1

-0.6530 -0.6526 14.0366 No

130.


-2.7300 -2.6539 1.0420 YES

131.


-2.7300 -2.7061 1.0544 YES

132.


-1.2380 -1.2749 0.1035 YES

133.

Validation COc1ccc(cc1)[C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@H]1OC(C)=O

-1.2380 -1.3271 0.1159 YES

134.

Calibration COc1ccc(cc1)[C@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

-1.2380 -1.3271 0.1159 YES

135.

Calibration COc1ccc(cc1)[C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

-1.2380 -1.3793 0.1283 YES

136.


-1.4770 -0.6669 0.0138 YES

137.

Training CC(C)N(CC[C@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.9000 1.0440 YES

138.

Training CC(C)N(CC[C@@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.9518 1.0550 YES

139.


2.0000 1.9154 8.0427 No

140.


0.7960 0.7983 17.0495 No

141.

Validation COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1COc2ccccc2O1

0.2290 0.1220 0.0809 YES

142.

Validation COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1COc2ccccc2O1

0.2290 0.0698 0.0933 YES

143.


-0.8130 -0.8597 14.0203 No

144.


-0.9640 -0.9581 7.0442 No

145.

Training Cc1cccc(CCN2CCC(CC2)C(=O)c2ccc(NS(C)(=O)=O)cc2)n1

2.0000 2.0975 5.0424 YES

146.

Training Oc1cc(O)c2C[C@@H](OC(=O)c3cc(O)c(O)c(O)c3)[C@H](Oc2c1)c1cc(O)c(O)c(O)c1

-0.7780 -0.7751 0.0857 YES

147.


1.3980 1.4377 15.0498 No

148.

Training CC(C)(C)c1ccc(cc1)C(=O)CCCN

0.5230 0.2196 1.0268 YES

1CCC(CC1)OC(c1ccccc1)c1ccccc1

149.

Validation CS(=O)(=O)Nc1ccc(OC[C@](O)CNCCOc2ccc(cc2)-n2ccnc2)cc1

0.3980 0.4073 2.0641 YES

150.

Training CS(=O)(=O)Nc1ccc(OC[C@@](O)CNCCOc2ccc(cc2)-n2ccnc2)cc1

0.3980 0.3555 2.0751 YES

151.

Validation CCC(=O)N(C1CCN(CC1)CCc1ccccc1)c1ccccc1

-0.2550 0.1795 0.0195 YES

152.

Validation CC(C)(C(O)=O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

-1.3620 -0.6707 0.0514 YES

153.


-1.3620 -0.7229 0.0638 YES

154.

Training FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@H]1CCCCN1

-0.5920 -0.7006 2.0759 YES

155.

Validation FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@@H]1CCCCN1

-0.5920 -0.7528 2.0883 YES

156.


2.0000 2.0429 13.0326 No

157.

Training CNCC[C@@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.5060 0.0583 YES

158.

Calibration CNCC[C@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.4538 0.0459 YES

159.


-0.3690 0.1991 0.0409 YES

160.


-0.5800 -0.6066 14.0384 No

161.

Validation COc1c(N2CCN[C@@H](C)C2)c(F)cc2c1n(cc(C(O)=O)c2=O)C1CC1

-2.1140 -2.3550 1.0802 YES

162.


-2.1140 -2.3028 1.0678 YES

163.


-0.0000 0.1449 0.0326 YES

164.

Training COc1ccc(Cl)cc1C(=O)NCCc1ccc(cc1)S(=O)

-1.8740 -1.8357 0.0499 YES

(=O)NC(=O)NC1CCCCC1 165.


1.0000 1.0777 1.0372 YES

166.

Validation CCCCCCCCC(=O)NCc1ccc(C[C@@H](O)CO)c(OC)c1

1.0000 1.0254 1.0496 YES

167.


-1.6990 -1.7219 5.0485 YES

168.

Training C[C@@H]1CN(CCN1)c1cc2n(cc(C(O)=O)c(=O)c2c(C)c1F)C1CC1

-1.6990 -1.7741 5.0609 YES

169.

Training CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.3373 0.1111 YES

170.

Calibration CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.2851 0.1235 YES

171.


-1.1000 -0.9897 3.1146 YES

172.


1.3980 1.7055 1.0611 YES

173.


1.3980 1.7577 1.0487 YES

174.

Validation OC1(CCN(CCCC(=O)c2ccc(F)cc2)CC1)c1ccc(Cl)cc1

1.5230 0.8179 0.0370 YES

175.


-2.4610 -1.8291 1.0498 YES

176.


-0.9640 -1.3831 1.0495 YES

177.


1.6990 1.3043 4.0501 YES

178.

Training CCCCCCCN(CC)CCC[C@H](O)c1ccc(NS(C)(=O)=O)cc1

1.6990 1.3565 4.0377 YES

179.

Training CN(C)CCCN1c2ccccc2CCc2ccccc12

-0.5310 -0.0862 1.0146 YES

180.


-2.2860 -2.2261 10.0605 No

181.


-1.0000 -0.9625 8.0309 No

Training CN1CCN(CC1)Cc1ccc- -0.1490 -0.4708 0.0555 YES

182. 2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationC)c1

183.


-0.6880 -0.6863 4.0725 YES

184.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNC(=O)Oc2ccccc2)c1

-0.4390 -0.0968 1.0724 YES

185.


-0.8980 -1.2038 1.0695 YES

186.


-0.2550 -0.2853 16.0534 No

187.

Validation COCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12

-0.7150 -0.9028 16.0586 No

188.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCCOc2ccccc2)c1

0.3470 -0.0870 0.0628 YES

189.


0.1020 0.1024 1.0640 YES

190.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccc(Cl)c2)c1

-0.4130 -0.3320 1.0645 YES

191.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(Cl)cc2)c1

-0.5550 -0.6071 1.0648 YES

192.


-0.3980 0.1572 0.0658 YES

193.

Calibration CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccnc2)c1

-0.5300 -1.4590 0.0678 YES

194.


-0.6810 -0.1103 0.0591 YES

Calibration CN1CCN(CC1)Cc1ccc- -0.2430 -1.2514 0.0640 YES

195. 2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNc2ccccc2)c1

196.


-0.8730 -0.2805 1.0661 YES

197.

Calibration CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.2410 -0.2292 0.0597 YES

198.


-0.7690 -0.2116 0.0618 YES

199.


1.0970 0.6114 0.0595 YES

200.

Validation CN1CCC(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.3220 -0.0185 0.0590 YES

201.


-0.7290 -0.7185 3.0654 YES

202.


-0.2360 -0.8454 1.0660 YES

203.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.0450 -0.4120 0.0625 YES

204.


-0.1550 -0.0320 9.0740 No

205.

Training CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(CN3CCOCC3)cc2)c1

-0.4080 -0.4382 0.0716 YES

206.


-0.9630 -1.0195 8.0641 No

207.


0.0220 -0.5759 0.0737 YES

208.

Training CN(C)[C@H]1CCN(C1)CC(=O)

0.2220 0.3946 0.0908 YES

Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

209.


0.3770 0.0377 1.0908 YES

210.

Training CN(C)CC1CCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.2230 0.4644 0.0751 YES

211.


-0.2700 -0.1470 0.0917 YES

212.

Training CN(C)C[C@@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.0040 -0.1992 0.1041 YES

213.

Validation CN(C)CCC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.1870 -0.0997 0.0694 YES

214.


-0.3580 -0.3920 7.0781 No

215.


-0.6200 -0.3652 0.0730 YES

216.

Calibration CN1CCCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.5380 -0.2509 0.0740 YES

217.


-1.1020 -1.0658 7.1408 No

218.


-0.0000 0.1220 7.0385 No

219.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.2388 0.1141 YES

220.

Calibration CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.2910 0.1265 YES

221.

Validation CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.2906 0.1251 YES

222.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.3428 0.1376 YES

223.

Training CN1C(=O)[C@H](NC(=O)Nc2cccc(C)c2)N=C(c2ccccc2)c2ccccc12

-0.6990 -0.7837 0.0529 YES

224.

Calibration CN1C(=O)[C@@H](NC(=O)Nc2cccc(C)c2)N=C(c2ccccc2)c2ccccc12

-0.6990 -0.8359 0.0653 YES

225.


2.0000 2.0228 13.0631 No

226.


2.0000 1.5771 0.0997 YES

227.

Validation FC(F)(F)CN1C(=O)[C@H](NC(=O)Cc2ccc(cc2C(F)(F)F)C(F)(F)F)N=C(c2ccccc2)c2ccccc12

-0.7780 -0.6350 3.1101 YES

228.


-0.7780 -0.6872 3.1225 YES

229.


1.5230 1.8031 8.0366 No

230.


-2.9610 -3.0655 0.0871 YES

231.


-2.9610 -3.1177 0.0995 YES

232.


1.6990 1.3869 1.0420 YES

233.

Validation CCN(CC)CC(=O)Nc1c(C)cccc1C

-2.4200 -2.1891 0.0168 YES

234.


-0.6990 -0.6975 26.0195 No

235.


-3.3800 -3.4254 4.0636 YES

236.

Validation CCn1cc(C(O)=O)c(=O)c2cc(F)c(N3CCN[C@@H](C)C3)c(F)c12

-3.3800 -3.4776 4.0761 YES

237.


-0.6020 -0.5457 15.0380 No

238.

Validation CCCCN(CCCC)C[C@@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.9100 -0.7038 16.0538 No

239.

Validation CCCCN(CCCC)C[C@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.9100 -0.6516 16.0414 No

240.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.3481 0.1128 YES

241.

Validation CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.2959 0.1253 YES

242.

Calibration CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@H](O)c2c1

0.9210 1.4003 0.1004 YES

243.


0.9210 1.3481 0.1128 YES

244.


-0.7160 -0.7204 7.0529 No

245.

Training O[C@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3439 0.0907 YES

246.

Calibration O[C@H]([C@@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3961 0.1031 YES

247.

Training O[C@@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3961 0.1031 YES

248.

Calibration O[C@@H]([C@@H]1CCCCN1)c1cc

-0.4220 -0.4484 0.1155 YES

(nc2c(cccc12)C(F)(F)F)C(F)(F)F

249.


-1.8750 -0.9908 0.0202 YES

250.


-2.1940 -2.0041 0.0458 YES

251.

Training CN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-2.1940 -1.9519 0.0334 YES

252.

Training CN1CCCC[C@H]1CCN1c2ccccc2Sc2ccc(cc12)S(C)=O

0.4950 0.4959 6.0425 No

253.

Training CN1CCCC[C@@H]1CCN1c2ccccc2Sc2ccc(cc12)S(C)=O

0.4950 0.4437 6.0549 No

254.

Training CCC(=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -1.0930 0.0350 YES

255.

Calibration CCC(=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -1.1453 0.0475 YES

256.


-0.7320 -1.5297 0.0201 YES

257.

Validation CC(C)NC[C@H](O)COc1ccc(CCO)cc1

-2.1610 -1.8071 0.0306 YES

258.

Training CC(C)NC[C@@H](O)COc1ccc(CCO)cc1

-2.1610 -1.8593 0.0430 YES

259.

Calibration COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@H]1C(C)C

-0.1550 -0.1680 0.1522 YES

260.

Training COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.2202 0.1646 YES

261.


-0.1550 -0.2327 0.1400 YES

262.

Calibration COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.2850 0.1525 YES

263.

Validation Clc1ccc(CO[C@@H](Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

-0.3220 -0.4289 0.0589 YES

264.

Training Clc1ccc(CO[C@H](Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

-0.3220 -0.3767 0.0465 YES

265.


-2.0470 -2.0470 5.0326 YES

Training CCOc1cc(N)c(Cl)cc1C(=O -0.6020 -0.6083 0.0651 YES

266. )NC[C@H]1CN(CCO1)Cc1ccc(F)cc1

267.

Calibration CCOc1cc(N)c(Cl)cc1C(=O)NC[C@@H]1CN(CCO1)Cc1ccc(F)cc1

-0.6020 -0.6605 0.0775 YES

268.


-0.5560 -0.8020 0.0243 YES

269.

Training NC[C@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.7620 -0.7928 0.0348 YES

270.

Calibration NC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.7620 -0.8451 0.0472 YES

271.

Training CCCCNCC[C@@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.6780 1.0601 YES

272.

Validation CCCCNCC[C@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.7302 1.0477 YES

273.


-0.6520 -0.6524 5.0413 YES

274.


-1.1520 -1.1434 9.0351 No

275.

Validation CCCCCCCC[N+](CC)(CC)CC

-0.9240 -1.4519 0.0238 YES

276.

Training CCCCCCCC[N+](C)(C)C -2.5020 -2.3377 0.0230 YES

277.

Training Oc1ccc(cc1)[C@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -2.1686 0.0478 YES

278.

Calibration Oc1ccc(cc1)[C@@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -2.2208 0.0602 YES

279.


-2.3890 -2.3765 2.0266 YES

280.

Training CN1CCC[C@@H]1c1cccnc1

-2.3890 -2.4287 2.0390 YES

281.


-0.8980 -0.8352 14.0538 No

282.

Validation COC(=O)C1=C(C)NC(C)=C([C@H]1c1ccccc1[N+]([O-])=O)C(=O)OCC(C)C

-1.3620 -1.3179 13.0829 No

283.


-1.3620 -1.3701 13.0953 No

284.

Validation CC[C@@H](OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.9326 0.0619 YES

Training CC[C@H] -1.0790 -0.8804 0.0494 YES

285. (OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

286.

Training CC[C@@H](OC(C)=O)C(C[C@@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.9848 0.0743 YES

287.

Calibration CC[C@H](OC(C)=O)C(C[C@@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.9326 0.0619 YES

288.


1.5230 1.5767 3.0352 YES

289.

Calibration CCC(=O)O[C@](Cc1ccccc1)([C@H](C)CNC)c1ccccc1

-0.5600 -0.9853 0.0734 YES

290.


-0.5600 -1.0375 0.0858 YES

291.


-0.5600 -1.0370 0.0844 YES

292.

Calibration CCC(=O)O[C@@](Cc1ccccc1)([C@@H](C)CNC)c1ccccc1

-0.5600 -1.0893 0.0969 YES

293.

Training Coc1ccc(CCNCCC[C@](CCalibrationN)(C(C)C)c2ccc(OC)c(OC)c2)cc1OC

-0.5800 -0.1807 5.0426 YES

294.


-0.5800 -0.2325 5.0536 YES

295.


-3.1520 -3.0655 0.0871 YES

296.


-3.1520 -3.1177 0.0995 YES

297.


0.6380 0.6007 7.0325 No

298.

Validation Cc1nccn1C[C@@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0101 2.0686 YES

299.

Training Cc1nccn1C[C@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0623 2.0562 YES

300.

Validation CN(C)CCO[C@@H](c1ccccc1)c1ccccc1C

0.0710 0.2279 1.0437 YES

301.


0.0710 0.2801 1.0313 YES

302.


-0.8630 -1.1777 1.0390 YES

Training [H]\N=C(/ -2.4010 -2.4186 29.0365 No

303. N)c1ccc(OCCCCCOc2ccc(cc2)C(\N)=N\[H])cc1

304.

Calibration C1CCC(CC1)C(C[C@H]1CCCCN1)C1CCCCC1

-0.8920 -0.9455 0.0348 YES

305.

Training C1CCC(CC1)C(C[C@@H]1CCCCN1)C1CCCCC1

-0.8920 -0.9978 0.0472 YES

306.


-0.0000 0.0060 5.0380 YES

307.

Training CCC1(C(=O)NC(=O)NC1=O)c1ccccc1

-3.4770 -3.6568 0.0223 YES

308.

Validation O=C1NC(=O)C(N1)(c1ccccc1)c1ccccc1

-2.3800 -2.4127 2.0291 YES

309.


-1.3100 -1.4666 3.0190 YES

310.

Calibration Fc1ccc(cc1)C(CCCN1CCC(CC1)n1c2ccccc2[nH]c1=O)c1ccc(F)cc1

1.3010 1.3104 0.0652 YES

311.


-0.1960 -0.1535 3.0435 YES

312.


-2.1430 -1.6185 0.0146 YES

313.

Training CCCNC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.3010 -0.1472 0.0486 YES

314.


-0.3010 -0.0949 0.0362 YES

315.


-0.0720 -0.5370 0.0141 YES

316.

Calibration COCCCN1CCC(CC1)NC(=O)c1cc(Cl)c(N)c2CCOc12

-0.7560 -1.1366 0.0330 YES

317.

Calibration COc1ccc(CN(CCN(C)C)c2ccccn2)cc1

-0.7780 -0.7156 0.0198 YES

318.


-0.7610 -0.8734 3.0389 YES

319.

Training Cc1ccc(cc1C)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.6990 1.6508 0.0353 YES

320.

Validation Cc1ccc(cc1C)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.6990 1.5985 0.0477 YES

321.

Training O[C@@H](CCCN1CCC(O)(CC1)c1ccc(Cl)cc1)c1ccc(F)cc1

-0.4150 -0.4931 0.0580 YES

322.


-0.4150 -0.4409 0.0455 YES

323.


-0.2550 0.1790 2.0714 YES

324.

Training Cc1nc2CCCCn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

0.8240 0.8706 6.0479 No

325.


-0.9140 -0.9538 7.1224 No

326.

Training CCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.4470 -1.6130 0.0465 YES

327.


0.3770 -0.0688 12.0424 No

328.

Training CCN(CC)CCNC(=O)c1ccc(NS(C)(=O)=O)cc1

-1.6990 -1.1008 4.0273 YES

329.


2.0000 1.6125 0.0534 YES

330.


-0.5190 -0.5912 9.0615 No

331.


-1.6560 -1.7283 14.0201 No

332.


-1.6560 -1.6442 14.0201 No

333.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1CCCO1

-1.2480 -1.2163 0.0620 YES

334.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1CCCO1

-1.2480 -1.2685 0.0744 YES

335.

Training CC(C)(C)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 1.0430 0.0451 YES

336.

Validation CC(C)(C)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 0.9908 0.0575 YES

337.

Validation COc1ccc(cc1OC)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.5230 1.3021 0.0415 YES

338.

Validation COc1ccc(cc1OC)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.5230 1.2499 0.0539 YES

339.

Validation C[C@@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.6272 0.0371 YES

340.

Training C[C@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.5750 0.0247 YES

341.

Validation CSc1ccc2Sc3ccccc3N(CC[C@H]3CCCCN3C)c2c1

0.4090 0.4537 8.0361 No

342.

Training CSc1ccc2Sc3ccccc3N(CC[C@@H]3CCCCN3C)c2c1

0.4090 0.4014 8.0485 No

343.

Training COc1ccc(CNC[C@H](O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

0.0180 0.0612 2.0657 YES

344.

Training COc1ccc(CNC[C@@H](O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

0.0180 0.0090 2.0781 YES

345.


1.6990 1.3907 2.0370 YES

346.

Training CC(C)N(CC[C@H](c1ccccc1)c1cc(C)ccc1O)C(C)C

1.6990 1.4430 2.0245 YES

347.

Calibration Clc1cccc(c1)N1CCN(CCCn2nc3ccccn3c2=O)CC1

-0.4620 -1.1937 0.0523 YES

348.


-0.1490 -0.1285 5.0864 YES

349.

Validation CCCc1nc(C)c2n1[nH]c(nc2=O)-c1cc(ccc1OCC)S(=O)(=O)N1CCN(CC)CC1

-1.1070 -0.9790 4.0732 YES

350.

Validation Coc1ccc(cc1OC)[C@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.9450 5.0435 YES

351.

Training Coc1ccc(cc1OC)[C@@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.8932 5.0546 YES

352.


-0.0250 -0.1533 0.0349 YES

353.

Training CC(C)CCCC(C)CCCC(C)CCC\C(C)=C\CC1=C(C)C(=O)c2ccccc2C1=O

-0.7600 -0.7408 15.0344 No

354.


1.0460 1.0321 2.0454 YES

355.


1.0460 0.9799 2.0578 YES

Training COc1ccc(NC(=O)c2ccc(c -0.2550 -0.1426 2.0456 YES

356. c2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

357.

Training COc1ccc(NC(=O)c2ccc(cc2F)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

-0.3220 -0.3025 5.0492 YES

358.

Training COc1ccc(NC(=O)c2ccc(cc2N2CCCCC2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

0.6990 0.6668 3.0537 YES

359.


0.9590 0.7100 1.0434 YES

360.


0.3770 0.6401 1.0530 YES

361.


-1.9290 -1.8862 2.0694 YES

362.

Training Cc1nccnc1C(=O)N1CCC(CC1)[C@H](N)Cc1cc(F)c(F)cc1F

-1.7400 -1.5991 2.0686 YES

363.


-1.7710 -1.8327 4.0708 YES

364.


-1.2550 -1.2416 5.0776 YES

365.


-1.1960 -1.1091 2.0384 YES

366.


-1.2150 -1.0569 2.0260 YES

367.


-0.6530 -0.8334 3.0422 YES

368.


-1.0130 -0.8550 1.0549 YES

369.

Calibration CCCCN(C1CCNCC1)S(=O)(=O)c1ccc2ccccc2c1

0.1430 0.2040 0.0330 YES

370.


0.3850 0.2291 0.0485 YES

371.

Training C1CC(CCN1)COc1ccc2ccccc2c1

-0.5800 -1.0789 0.0163 YES

372.

Calibration Cc1ccc2ccc(OCC3CCNCC3)cc2c1

-0.5440 -1.9559 0.0152 YES

373.


-0.5440 -0.4770 1.0188 YES

374.


-1.0040 -0.6431 0.0283 YES

375.

Training Clc1ccccc1OC1CN(C1)S(=O)

-0.5330 -0.4909 0.0490 YES

(=O)c1ccc2CCNCCc2c1 376.

Validation Clc1cccc(OC2CN(C2)S(=O)(=O)c2ccc3CCNCCc3c2)c1

-0.5670 -0.3944 2.0489 YES

377.


-0.3200 -0.3113 2.0489 YES

378.

Training Clc1ccccc1C[C@@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.5350 -0.6522 0.0667 YES

379.

Validation Clc1ccccc1C[C@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.7190 -0.6000 0.0543 YES

380.

Calibration Clc1ccccc1OC1CCN(CC1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.4620 -1.0546 0.0489 YES

381.


-2.1000 -2.1513 3.1014 YES

382.

Training F[C@H]1CN(C[C@H]1F)C(=O)[C@@H]1C[C@@H](CN1)N1CCN(CC1)c1ncccn1

-1.7320 -1.7798 5.1249 YES

383.

Validation CC(C)(C)CNc1nc(nc(N2CCOCC2)c1N)CCalibrationN

-1.8450 -1.8664 1.0505 YES

384.


-1.7160 -1.7344 1.0442 YES

385.


1.6990 1.9643 0.0476 YES

386.

Training CCOC(=O)N1CCN(CC1)C(=O)C1(CCN(CC1)c1cc(N)ccn1)c1ccccc1

0.7700 0.3981 0.0437 YES

387.


1.3980 1.1249 1.0399 YES

388.

Training COc1ccc(CNC(=O)C2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)cc1

0.6990 0.8729 0.0388 YES

389.


1.0970 0.5949 0.0410 YES

390.

Calibration COc1ccc(C(=O)NC2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)c(Cl)c1

0.4690 0.4031 0.0387 YES

391.

Training Nc1ccnc(c1)N1CCC(CC1)(NC(=O)c1ccccn1)c1cccc

0.2600 -0.1185 1.0429 YES

c1 392.


1.5230 1.2482 0.0459 YES

393.


-0.9860 -0.0968 0.0425 YES

394.


1.6990 1.8218 2.0326 YES

395.


-0.6730 -0.7160 0.0587 YES

396.


-0.2650 -0.7086 0.0259 YES

397.


0.0600 0.0843 2.0560 YES

398.


0.0460 0.3232 1.0487 YES

399.


0.2840 0.2738 2.0447 YES

400.

Training Nc1ccnc(c1)N1CCC(CC1)n1c2ncccc2n(CC2CC2)c1=O

0.1250 -0.0916 2.0468 YES

Distribution 3 Eq. 5

1.

Calibration Fc1ccc(cc1)C(N1CCNCC1)c1ccc(F)cc1

-0.2040 -0.4840 0.0282 YES

2.

Training CN1CCN(CC1)C1=Nc2ccccc2Nc2sc(CO)cc12

-1.0640 -1.0268 9.0272 No

3.

Training Fc1ccc(cc1)C(=O)c1ccc(F)cc1

-1.8570 -1.9573 0.0223 YES

4.


-1.9960 -2.6110 0.0285 YES

5.


6.


-0.6990 -0.6950 11.0287 No

7.

Validation CCCNC[C@@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.2944 0.0377 YES

8.

Training CCCNC[C@H](O)COc1ccc(O)cc1C(=O)CCc1ccccc1

-0.2740 -0.3130 0.0400 YES

9.


-0.1140 -0.0890 5.0689 YES

Validation Cc1nc2CC[C@H] -0.1140 -0.1076 5.0713 YES

10. (O)Cn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

11.

Calibration CC[C@@H](OC(C)=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8207 0.0691 YES

12.

Training CC[C@H](OC(C)=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8393 0.0714 YES

13.

Validation CC[C@@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8021 0.0667 YES

14.

Training CC[C@H](OC(C)=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.4770 -0.8207 0.0691 YES

15.


-0.5560 -0.5550 7.0870 No

16.


-0.4470 -0.4545 20.0269 No

17.


-1.0000 -1.0092 13.0243 No

18.


0.6780 0.6523 1.0523 YES

19.


-2.3500 -2.3077 0.0485 YES

20.

Calibration CCCN[C@@H](C)C(=O)Nc1c(C)csc1C(=O)OC

-2.3500 -2.2891 0.0461 YES

21.

Validation COc1ccc(CCN2CCC(CC2)Nc2nc3ccccc3n2Cc2ccc(F)cc2)cc1

-0.0000 -0.1368 7.0497 No

22.


0.2520 0.2526 3.0895 YES

23.


0.2150 0.2061 18.0620 No

24.


-0.1140 -0.1201 4.0420 YES

Training CCN(CC)Cc1ccc2CC(CCc -0.9080 -0.4775 0.0545 YES

25. 2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

26.


-0.5190 -1.0201 0.0488 YES

27.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccc(c2)C(F)(F)F)CC1=O

-0.2300 -0.1819 0.0661 YES

28.

Training CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCC2CCCCC2)CC1=O

-0.5190 -0.3547 0.0470 YES

29.

Validation CCN(CC)Cc1ccc2CC(CCc2c1)N1CCN(CCc2cccs2)CC1=O

-1.1210 -0.9552 2.0440 YES

30.

Training Fc1ccc(CCN2CCN(C3CCc4cc(CN5CCC(CC5)C(F)(F)F)ccc4C3)C(=O)C2)cc1

-0.3010 -0.3006 13.0706 No

31.

Training Fc1ccc(CCN2CCN(C3CCc4cc(Cn5ccnc5)ccc4C3)C(=O)C2)cc1

-0.6020 -0.5995 13.0518 No

32.


-1.0410 -1.0547 13.0488 No

33.

Training CS(=O)(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.1140 -1.1096 1.0730 YES

34.


-1.3800 -1.3629 15.0608 No

35.

Calibration CC(=O)N1CCN(CC1)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -0.8615 0.0614 YES

36.

Training CN(C)C(=O)C(CO)N(C)Cc1ccc2CC(CCc2c1)N1CCN(CCc2ccc(F)cc2)CC1=O

-1.3980 -1.4926 0.0640 YES

37.

Validation Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)-c1ccccc1

1.0460 1.0077 3.0664 YES

38.

Training Fc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=S)c2ccccc12

2.0000 2.0069 6.0549 No

39.

Training CC(C)(O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.1955 0.0535 YES

40.

Training CC(C)(O)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

0.3370 0.2141 0.0511 YES

Calibration Fc1ccc(cc1)N1C[C@@H] 1.6990 1.7102 0.0667 YES

41. (C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

42.

Training Fc1ccc(cc1)N1C[C@H](C2CCN(CC2)CCN2CCNC2=O)c2ccccc12

1.6990 1.6916 0.0691 YES

43.


0.6990 0.9590 0.0409 YES

44.

Training CN(C)Cc1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

2.0000 0.7726 0.0425 YES

45.


-1.4150 -0.8492 0.0428 YES

46.

Calibration CCC(CC)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.1700 -0.7166 0.0417 YES

47.

Calibration C[C@@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.6580 -0.4993 0.0562 YES

48.

Training C[C@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.6580 -0.5178 0.0586 YES

49.

Training CCC(=O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.2900 -0.0127 0.0417 YES

50.


2.0000 1.9886 4.0761 YES

51.


-1.1960 -0.9264 0.0430 YES

52.

Calibration CC[C@@H](O)c1cn(-c2ccc(F)cc2)c2ccc(Cl)cc12

-0.3420 -0.0318 0.0589 YES

53.


-0.3420 -0.0504 0.0613 YES

54.


-0.5440 -1.1730 0.0425 YES

55.


2.0000 1.3957 0.0551 YES

56.


0.2370 0.2994 0.0646 YES

57.


-1.8750 -0.2638 0.0608 YES

58.

Training Clc1ccc2n(cc(C3CCN(CC3)CCN3CCNC3=O)c2c1)C

0.8540 0.8451 3.0643 YES

1CCCCC1 59.

Training COC(=O)Cc1ccc(cc1)-n1cc(C2CCN(CC2)CCN2CCNC2=O)c2cc(Cl)ccc12

0.8860 0.8058 0.0651 YES

60.


1.3980 0.2426 0.0612 YES

61.

Training COc1ccc(CCN(C)CCCN(C(=O)c2ccc(cc2)[N+]([O-])=O)c2ccc(OC)c(OC)c2)cc1OC

1.6990 2.0338 15.0409 No

62.

Training COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1413 0.1084 YES

63.

Calibration COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1599 0.1107 YES

64.

Training COc1cc2CCN3[C@@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1599 0.1107 YES

65.

Validation COc1cc2CCN3[C@H](Cc4ccc(OC)c(OC)c4[C@H]3Cc3ccccc3)c2cc1OC

-1.1460 -1.1785 0.1131 YES

66.


-0.0000 0.0155 0.0479 YES

67.


0.2600 0.3820 1.0399 YES

68.

Validation CC(C)COC[C@H](CN(Cc1ccccc1)c1ccccc1)N1CCCC1

0.2600 0.3634 1.0423 YES

69.


-0.4910 -0.5201 24.0325 No

70.


-1.7970 -1.7212 3.0691 YES

71.


-0.0000 0.0228 7.0595 No

72.


1.5230 1.5476 8.0658 No

73.

Training CN(C)CC[C@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.2433 8.0362 No

74.

Training CN(C)CC[C@@H](c1ccc(Br)cc1)c1ccccn1

-0.2300 -0.2247 8.0338 No

Training CC(C)(C)N1CCC(CC1) -1.0090 -0.7197 0.0283 YES

75. (c1ccccc1)c1ccccc1 76.

Validation CCCCN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.4176 0.0433 YES

77.

Calibration CCCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.3420 -1.3990 0.0409 YES

78.


-0.4100 -0.4407 2.0380 YES

79.

Training Cn1cnc2n(C)c(=O)n(C)c(=O)c12

-0.6900 -0.6238 4.0227 YES

80.


-2.4000 -2.3805 3.0229 YES

81.


0.2920 0.3055 2.0529 YES

82.

Training COc1ccccc1OCCNC[C@H](O)COc1cccc2[nH]c3ccccc3c12

0.2920 0.2870 2.0553 YES

83.


84.


-0.1930 0.0022 0.0302 YES

85.

Calibration CCN(CC)CCC[C@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 0.0507 0.0442 YES

86.

Training CCN(CC)CCC[C@@H](C)Nc1ccnc2cc(Cl)ccc12

-0.3980 0.0693 0.0418 YES

87.


-1.1140 -0.8534 0.0383 YES

88.

Calibration CN(C)CC[C@H](c1ccc(Cl)cc1)c1ccccn1

-1.1140 -0.8720 0.0406 YES

89.

Validation C1CN=C(N1)[C@@H]1CC1(c1ccccc1)c1ccccc1

-0.5680 -0.5856 4.0417 YES

90.


-0.5680 -0.6042 4.0441 YES

91.


-2.9850 -3.0611 1.0681 YES

92.


2.0000 2.1401 0.0935 YES

93.

Validation CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.1587 0.0911 YES

94.

Validation CO[C@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1NC(=O)c1cc(Cl)c(N)cc1OC

2.0000 2.1587 0.0911 YES

95.

Calibration CO[C@@H]1CN(CCCOc2ccc(F)cc2)CC[C@@H]1N

2.0000 2.1773 0.0887 YES

C(=O)c1cc(Cl)c(N)cc1OC 96.

Calibration CN(C)CCC[C@]1(OCc2cc(ccc12)CCalibrationN)c1ccc(F)cc1

-0.6000 -0.4924 0.0728 YES

97.


-0.6000 -0.5298 0.0733 YES

98.

Training COc1cc(N)c(Cl)cc1C(=O)NC1CCN(CC1)Cc1ccccc1

0.2080 0.1569 0.0330 YES

99.


2.0000 2.0266 0.0711 YES

100.

Training CN1CCC[C@@H]1CCO[C@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 2.0452 0.0687 YES

101.

Training CN1CCC[C@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.9227 1.0665 YES

102.

Training CN1CCC[C@@H]1CCO[C@@](C)(c1ccccc1)c1ccc(Cl)cc1

2.0000 1.9413 1.0642 YES

103.

Training CCCCCCC[N+](CC)(CC)CCCCc1ccc(Cl)cc1

0.6020 0.3861 6.0314 No

104.


0.7450 0.7341 15.0233 No

105.


0.7450 0.7344 15.0233 No

106.


0.4950 0.5491 9.0317 No

107.

Validation CN1CCN(CC1)[C@H]1N(O)c2cc(Cl)ccc2Nc2ccccc12

-2.1250 -1.3411 2.0488 YES

108.

Training CCOC(=O)[C@H]1[C@H](C[C@H]2CC[C@@H]1N2C)OC(=O)c1ccccc1

-0.6020 -0.7409 4.1057 YES

109.


-0.7480 -0.6362 4.1051 YES

110.

Training C[C@@H](CN(C)C)CN1c2ccccc2Sc2ccc(cc12)CCalibrationN

0.3280 0.2693 0.0533 YES

111.


0.3280 0.2507 0.0557 YES

112.


-1.5210 -0.9171 0.0547 YES

113.


-1.5210 -0.8985 0.0523 YES

114.


-1.5210 -1.0210 1.0501 YES

115.


-1.5210 -1.0024 1.0477 YES

116.

Validation Coc1ccc(CCN(C)CCC[C@](CCalibrationN)(C(C)C)c2ccc(O)c(O)c2)cc1OC

-0.3420 -0.4497 0.0617 YES

117.


-0.3420 -0.5536 1.0571 YES

118.


-0.7850 -0.4114 0.0426 YES

119.

Training COc1ccc(CCN[C@H](C)COc2c(C)cccc2C)cc1OC

-0.7850 -0.4300 0.0450 YES

120.

Training COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.2256 26.0830 No

121.

Validation COc1cc2CCN(C)[C@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.2071 26.0806 No

122.

Training COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.1885 26.0782 No

123.

Validation COc1cc2CCN(C)[C@@H](Cc3ccc(Oc4cc(C[C@H]5N(C)CCc6cc(OC)c(OC)cc56)ccc4O)cc3)c2cc1OC

-1.2040 -1.2071 26.0806 No

124.


-0.0000 0.0161 7.0492 No

125.

Training Cc1cc2=C(Nc3ccccc3N=c2s1)N1CCNCC1

-1.1520 -1.1399 12.0328 No

126.


-0.7400 -0.7325 16.0553 No

127.

Validation CCCCNC[C@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.7400 -0.7511 16.0576 No

128.

Training CNCCCN1c2ccccc2CCc2ccccc12

-0.1430 -0.1946 0.0195 YES

Training Clc1ccc2c(CCc3cccnc3\ -0.6530 -0.6459 14.0420 No

129. C2=C2/CCNCC2)c1 130.


-2.7300 -2.6278 0.0525 YES

131.


-2.7300 -2.6092 0.0501 YES

132.


-1.2380 -1.2829 0.0804 YES

133.

Calibration COc1ccc(cc1)[C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@H]1OC(C)=O

-1.2380 -1.2643 0.0780 YES

134.

Training COc1ccc(cc1)[C@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

-1.2380 -1.2643 0.0780 YES

135.

Training COc1ccc(cc1)[C@@H]1Sc2ccccc2N(CCN(C)C)C(=O)[C@@H]1OC(C)=O

-1.2380 -1.2457 0.0756 YES

136.


-1.4770 -0.6246 0.0118 YES

137.

Calibration CC(C)N(CC[C@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.7622 0.0519 YES

138.

Training CC(C)N(CC[C@@](C(N)=O)(c1ccccc1)c1ccccn1)C(C)C

-0.8590 -0.8661 1.0473 YES

139.


2.0000 2.1039 0.0807 YES

140.


0.7960 0.7989 22.0594 No

141.

Training COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1COc2ccccc2O1

0.2290 0.2999 0.0794 YES

142.

Calibration COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1COc2ccccc2O1

0.2290 0.3185 0.0770 YES

143.


-0.8130 -0.8748 13.0214 No

144.


-0.9640 -0.9449 3.0602 YES

145.

Calibration Cc1cccc(CCN2CCC(CC2)C(=O)c2ccc(NS(C)(=O)=O)cc2)n1

2.0000 1.3942 0.0632 YES

Training Oc1cc(O)c2C[C@@H] -0.7780 -0.7668 2.0792 YES

146. (OC(=O)c3cc(O)c(O)c(O)c3)[C@H](Oc2c1)c1cc(O)c(O)c(O)c1

147.


1.3980 1.3864 9.0884 No

148.

Training CC(C)(C)c1ccc(cc1)C(=O)CCCN1CCC(CC1)OC(c1ccccc1)c1ccccc1

0.5230 0.3150 0.0300 YES

149.

Training CS(=O)(=O)Nc1ccc(OC[C@](O)CNCCOc2ccc(cc2)-n2ccnc2)cc1

0.3980 0.4309 3.0650 YES

150.

Training CS(=O)(=O)Nc1ccc(OC[C@@](O)CNCCOc2ccc(cc2)-n2ccnc2)cc1

0.3980 0.3271 4.0605 YES

151.

Training CCC(=O)N(C1CCN(CC1)CCc1ccccc1)c1ccccc1

-0.2550 -0.3017 0.0206 YES

152.

Validation CC(C)(C(O)=O)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

-1.3620 -0.9033 0.0627 YES

153.


-1.3620 -0.8847 0.0604 YES

154.

Calibration FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@H]1CCCCN1

-0.5920 -0.6056 0.0844 YES

155.

Training FC(F)(F)COc1ccc(OCC(F)(F)F)c(c1)C(=O)NC[C@@H]1CCCCN1

-0.5920 -0.5870 0.0820 YES

156.


2.0000 1.9990 13.0361 No

157.

Validation CNCC[C@@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.4346 1.0546 YES

158.

Training CNCC[C@H](Oc1ccc(cc1)C(F)(F)F)c1ccccc1

-0.1760 -0.4532 1.0570 YES

159.


-0.3690 0.1325 0.0507 YES

160.


-0.5800 -0.5751 15.0329 No

161.

Training COc1c(N2CCN[C@@H](C)C2)c(F)cc2c1n(cc(C(O

-2.1140 -2.1658 1.0766 YES

)=O)c2=O)C1CC1 162.


-2.1140 -2.1844 1.0789 YES

163.


-0.0000 0.1432 0.0375 YES

164.

Training COc1ccc(Cl)cc1C(=O)NCCc1ccc(cc1)S(=O)(=O)NC(=O)NC1CCCCC1

-1.8740 -1.8350 0.0508 YES

165.


1.0000 1.0128 1.0401 YES

166.

Training CCCCCCCCC(=O)NCc1ccc(C[C@@H](O)CO)c(OC)c1

1.0000 1.0313 1.0378 YES

167.


-1.6990 -1.8125 0.0721 YES

168.

Calibration C[C@@H]1CN(CCN1)c1cc2n(cc(C(O)=O)c(=O)c2c(C)c1F)C1CC1

-1.6990 -1.7939 0.0697 YES

169.

Validation CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.4091 3.1093 YES

170.

Training CC(C)COC(=O)N1C[C@H]2C[C@H](CN(C[C@@H](O)COc3ccc(cc3)CCalibrationN)C2)C1

1.3980 1.4277 3.1069 YES

171.


-1.1000 -1.0986 5.1111 YES

172.


1.3980 1.6017 1.0663 YES

173.


1.3980 1.5831 1.0687 YES

174.

Training OC1(CCN(CCCC(=O)c2ccc(F)cc2)CC1)c1ccc(Cl)cc1

1.5230 1.4269 0.0452 YES

175.


-2.4610 -2.1729 1.0536 YES

176.


-0.9640 -1.2509 1.0610 YES

177.


1.6990 1.4168 0.0667 YES

178.

Calibration CCCCCCCN(CC)CCC[C@H](O)c1ccc(NS(C)

1.6990 1.3982 0.0691 YES

(=O)=O)cc1 179.

Training CN(C)CCCN1c2ccccc2CCc2ccccc12

-0.5310 -0.3119 0.0215 YES

180.


-2.2860 -2.2802 11.0506 No

181.


-1.0000 -0.9981 5.0334 YES

182.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationC)c1

-0.1490 -0.3588 0.0794 YES

183.


-0.6880 -0.6764 2.1047 YES

184.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNC(=O)Oc2ccccc2)c1

-0.4390 -0.1524 2.0926 YES

185.


-0.8980 -1.2499 2.0918 YES

186.


-0.2550 -0.2558 0.1061 YES

187.

Calibration COCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12

-0.7150 -0.7598 0.1080 YES

188.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCCOc2ccccc2)c1

0.3470 0.1168 0.0883 YES

189.


0.1020 0.1644 0.0960 YES

190.

Calibration CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccc(Cl)c2)c1

-0.4130 -0.3400 0.0990 YES

191.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(Cl)cc2)c1

-0.5550 -0.6653 0.0990 YES

192.


-0.3980 0.0596 0.0929 YES

193.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2cccnc2)c1

-0.5300 -1.1328 0.0918 YES

194.


-0.6810 -0.2545 0.0874 YES

195.

Training CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCNc2ccccc2)c1

-0.2430 -0.3503 1.0868 YES

196.


-0.8730 -0.0453 1.0907 YES

197.

Validation CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.2410 -0.1303 0.0841 YES

198.


-0.7690 -0.3210 0.0878 YES

199.


1.0970 0.5379 0.0836 YES

200.

Training CN1CCC(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.3220 -0.0730 0.0844 YES

201.


-0.7290 -0.7159 2.0933 YES

202.


-0.2360 -0.9839 1.0886 YES

203.

Validation CN1CCN(CC1)Cc1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccccc2)c1

-0.0450 -0.2071 0.0880 YES

204.


-0.1550 -0.1182 2.0792 YES

205.

Validation CN1CCN(CC1)c1ccc-2c(Cc3c(n[nH]c-23)-c2csc(c2)CCalibrationCCOc2ccc(CN3CCOCC3)cc2)c1

-0.4080 -0.3304 0.1066 YES

206.


-0.9630 -1.0104 1.0726 YES

207.


0.0220 -0.3735 0.0519 YES

208.

Validation CN(C)[C@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.2220 0.6564 0.0741 YES

209.


0.3770 -0.0470 0.0754 YES

210.

Training CN(C)CC1CCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.2230 0.5228 0.0545 YES

211.


-0.2700 -0.0383 0.0791 YES

212.

Training CN(C)C[C@@H]1CCN(C1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

-0.0040 -0.0197 0.0767 YES

213.

Calibration CN(C)CCC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.1870 0.0366 0.0480 YES

214.


-0.3580 -0.3512 9.0740 No

215.


-0.6200 -0.3162 0.0523 YES

216.

Training CN1CCCN(CC1)CC(=O)Nc1cc(nc(n1)-c1ccc(C)o1)-n1nc(C)cc1C

0.5380 -0.0497 0.0522 YES

217.


-1.1020 -1.1069 9.1847 No

218.


-0.0000 0.1394 0.0579 YES

219.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@](Cn3ccnc3)

-0.2790 -0.2744 8.0853 No

(O2)c2ccc(Cl)cc2Cl)cc1 220.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.2558 8.0829 No

221.

Validation CC(=O)N1CCN(CC1)c1ccc(OC[C@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.3783 9.0807 No

222.

Training CC(=O)N1CCN(CC1)c1ccc(OC[C@@H]2CO[C@@](Cn3ccnc3)(O2)c2ccc(Cl)cc2Cl)cc1

-0.2790 -0.3597 9.0784 No

223.

Validation CN1C(=O)[C@H](NC(=O)Nc2cccc(C)c2)N=C(c2ccccc2)c2ccccc12

-0.6990 -0.7063 7.0447 No

224.

Training CN1C(=O)[C@@H](NC(=O)Nc2cccc(C)c2)N=C(c2ccccc2)c2ccccc12

-0.6990 -0.6878 7.0423 No

225.


2.0000 1.9987 18.0577 No

226.


2.0000 1.7682 0.0936 YES

227.

Training FC(F)(F)CN1C(=O)[C@H](NC(=O)Cc2ccc(cc2C(F)(F)F)C(F)(F)F)N=C(c2ccccc2)c2ccccc12

-0.7780 -0.8021 6.1118 No

228.


-0.7780 -0.7835 6.1094 No

229.


1.5230 1.5431 14.0259 No

230.

Calibration C[C@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-2.9610 -3.2181 0.1222 YES

231.

Validation C[C@@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-2.9610 -3.1995 0.1198 YES

232.


1.6990 1.5580 0.0507 YES

Calibration CCN(CC)CC(=O)Nc1c(C)c -2.4200 -2.6104 0.0142 YES

233. ccc1C 234.


-0.6990 -0.7174 25.0204 No

235.


-3.3800 -3.3954 0.0932 YES

236.

Calibration CCn1cc(C(O)=O)c(=O)c2cc(F)c(N3CCN[C@@H](C)C3)c(F)c12

-3.3800 -3.3768 0.0908 YES

237.


-0.6020 -0.5575 14.0401 No

238.

Validation CCCCN(CCCC)C[C@@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.9100 -0.8238 16.0595 No

239.

Validation CCCCN(CCCC)C[C@H](O)c1cc(Cl)cc2c1-c1ccc(Cl)cc1\C2=C/c1ccc(Cl)cc1

-0.9100 -0.8424 16.0619 No

240.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.0522 0.1156 YES

241.

Calibration CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@@H](O)c2c1

0.9210 1.0707 0.1132 YES

242.

Training CS(=O)(=O)Nc1ccc2OC3(CCN(CC3)[C@H]3CCc4cc(ccc4C3)CCalibrationN)C[C@H](O)c2c1

0.9210 1.0336 0.1180 YES

243.


0.9210 1.0522 0.1156 YES

244.


-0.7160 -0.7117 6.0593 No

245.

Validation O[C@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3809 0.1002 YES

Calibration O[C@H] -0.4220 -0.3623 0.0979 YES

246. ([C@@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

247.

Training O[C@@H]([C@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3623 0.0979 YES

248.

Training O[C@@H]([C@@H]1CCCCN1)c1cc(nc2c(cccc12)C(F)(F)F)C(F)(F)F

-0.4220 -0.3437 0.0955 YES

249.


-1.8750 -1.2909 0.0157 YES

250.


-2.1940 -2.0937 0.0400 YES

251.

Training CN1CCCC[C@H]1C(=O)Nc1c(C)cccc1C

-2.1940 -2.1123 0.0424 YES

252.

Calibration CN1CCCC[C@H]1CCN1c2ccccc2Sc2ccc(cc12)S(C)=O

0.4950 0.4558 0.0763 YES

253.

Training CN1CCCC[C@@H]1CCN1c2ccccc2Sc2ccc(cc12)S(C)=O

0.4950 0.4743 0.0740 YES

254.

Calibration CCC(=O)C(C[C@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -0.9913 0.0459 YES

255.

Training CCC(=O)C(C[C@@H](C)N(C)C)(c1ccccc1)c1ccccc1

-0.9910 -0.9727 0.0435 YES

256.


-0.7320 -1.4444 0.0245 YES

257.

Training CC(C)NC[C@H](O)COc1ccc(CCO)cc1

-2.1610 -2.2874 0.0332 YES

258.

Training CC(C)NC[C@@H](O)COc1ccc(CCO)cc1

-2.1610 -2.2688 0.0308 YES

259.

Calibration COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@H]1C(C)C

-0.1550 -0.1908 0.1101 YES

260.

Training COCC(=O)O[C@@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.1722 0.1077 YES

261.


-0.1550 -0.1534 0.1096 YES

262.

Training COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2cc(F)ccc2[C@@H]1C(C)C

-0.1550 -0.1348 0.1072 YES

Training Clc1ccc(CO[C@@H] -0.3220 -0.3863 0.0505 YES

263. (Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

264.

Calibration Clc1ccc(CO[C@H](Cn2ccnc2)c2ccc(Cl)cc2Cl)c(Cl)c1

-0.3220 -0.4049 0.0529 YES

265.


-2.0470 -2.0720 4.0298 YES

266.

Validation CCOc1cc(N)c(Cl)cc1C(=O)NC[C@H]1CN(CCO1)Cc1ccc(F)cc1

-0.6020 -0.6249 1.0699 YES

267.

Training CCOc1cc(N)c(Cl)cc1C(=O)NC[C@@H]1CN(CCO1)Cc1ccc(F)cc1

-0.6020 -0.6063 1.0675 YES

268.


-0.5560 -0.5389 6.0217 No

269.

Training NC[C@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.7620 -0.7688 0.0365 YES

270.

Training NC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.7620 -0.7502 0.0341 YES

271.

Validation CCCCNCC[C@@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.7753 1.0641 YES

272.

Training CCCCNCC[C@H](O)c1cc2c(Cl)cc(Cl)cc2c2cc(ccc12)C(F)(F)F

1.1550 0.7567 1.0664 YES

273.


-0.6520 -0.6135 8.0425 No

274.


-1.1520 -1.1499 9.0381 No

275.

Training CCCCCCCC[N+](CC)(CC)CC

-0.9240 -1.1865 6.0212 No

276.

Training CCCCCCCC[N+](C)(C)C -2.5020 -1.9981 6.0215 No

277.

Calibration Oc1ccc(cc1)[C@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -1.9899 0.0527 YES

278.

Training Oc1ccc(cc1)[C@@H]1CC(=O)c2c(O)cc(O)cc2O1

-1.5620 -1.9713 0.0503 YES

279.


-2.3890 -2.3973 2.0359 YES

280.

Validation CN1CCC[C@@H]1c1cccnc1

-2.3890 -2.3787 2.0335 YES

281.


-0.8980 -0.9673 18.0380 No

282.

Validation COC(=O)C1=C(C)NC(C)=C([C@H]1c1ccccc1[N+]

-1.3620 -1.4094 21.0616 No

([O-])=O)C(=O)OCC(C)C 283.


-1.3620 -1.3908 21.0593 No

284.

Calibration CC[C@@H](OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.6854 0.0660 YES

285.

Calibration CC[C@H](OC(C)=O)C(C[C@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.7040 0.0683 YES

286.

Validation CC[C@@H](OC(C)=O)C(C[C@@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.6668 0.0636 YES

287.

Training CC[C@H](OC(C)=O)C(C[C@@H](C)NC)(c1ccccc1)c1ccccc1

-1.0790 -0.6854 0.0660 YES

288.


1.5230 1.5404 4.0402 YES

289.


-0.5600 -0.9171 0.0547 YES

290.


-0.5600 -0.8985 0.0523 YES

291.


-0.5600 -1.0210 1.0501 YES

292.


-0.5600 -1.0024 1.0477 YES

293.

Calibration Coc1ccc(CCNCCC[C@](CCalibrationN)(C(C)C)c2ccc(OC)c(OC)c2)cc1OC

-0.5800 -0.1584 0.0590 YES

294.


-0.5800 -0.2623 1.0545 YES

295.

Calibration C[C@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-3.1520 -3.2181 0.1222 YES

296.

Training C[C@@H]1COc2c(N3CCN(C)CC3)c(F)cc3c2n1cc(C(O)=O)c3=O

-3.1520 -3.1995 0.1198 YES

297.


0.6380 0.7081 12.0309 No

298.

Training Cc1nccn1C[C@@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0898 2.0538 YES

299.

Training Cc1nccn1C[C@H]1CCc2c(C1=O)c1ccccc1n2C

0.0920 0.0713 2.0562 YES

300.

Calibration CN(C)CCO[C@@H](c1ccccc1)c1ccccc1C

0.0710 0.1368 0.0288 YES

301.


0.0710 0.1182 0.0311 YES

302.


-0.8630 -0.8972 1.0337 YES

303.

Training [H]\N=C(/N)c1ccc(OCCCCCOc2ccc(cc2)C(\N)=N\[H])cc1

-2.4010 -2.4035 31.0342 No

304.

Validation C1CCC(CC1)C(C[C@H]1CCCCN1)C1CCCCC1

-0.8920 -1.5974 0.0480 YES

305.

Calibration C1CCC(CC1)C(C[C@@H]1CCCCN1)C1CCCCC1

-0.8920 -1.5788 0.0457 YES

306.


-0.0000 0.0049 4.0480 YES

307.

Training CCC1(C(=O)NC(=O)NC1=O)c1ccccc1

-3.4770 -3.5963 0.0202 YES

308.

Calibration O=C1NC(=O)C(N1)(c1ccccc1)c1ccccc1

-2.3800 -2.1258 0.0301 YES

309.


-1.3100 -1.4188 2.0234 YES

310.

Calibration Fc1ccc(cc1)C(CCCN1CCC(CC1)n1c2ccccc2[nH]c1=O)c1ccc(F)cc1

1.3010 1.0636 0.0594 YES

311.


-0.1960 -0.2019 3.0357 YES

312.


-2.1430 -1.6755 0.0140 YES

313.

Training CCCNC[C@@H](O)COc1ccccc1C(=O)CCc1ccccc1

-0.3010 0.0327 0.0354 YES

314.


-0.3010 0.0141 0.0378 YES

315.


-0.0720 -0.3378 0.0201 YES

316.

Training COCCCN1CCC(CC1)NC(=O)c1cc(Cl)c(N)c2CCOc12

-0.7560 -0.7195 0.0365 YES

317.

Validation COc1ccc(CN(CCN(C)C)c2ccccn2)cc1

-0.7780 -0.6171 1.0197 YES

318.


-0.7610 -0.8079 4.0335 YES

319.

Validation Cc1ccc(cc1C)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.6990 1.3621 0.0496 YES

320.

Validation Cc1ccc(cc1C)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.6990 1.3806 0.0472 YES

Training O[C@@H] -0.4150 -0.4379 0.0511 YES

321. (CCCN1CCC(O)(CC1)c1ccc(Cl)cc1)c1ccc(F)cc1

322.


-0.4150 -0.4565 0.0535 YES

323.


-0.2550 0.0822 2.0799 YES

324.

Training Cc1nc2CCCCn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12

0.8240 0.8280 5.0475 YES

325.


-0.9140 -0.9119 3.1470 YES

326.

Training CCCN1CCCC[C@@H]1C(=O)Nc1c(C)cccc1C

-1.4470 -1.7228 0.0407 YES

327.


0.3770 0.0937 15.0291 No

328.

Calibration CCN(CC)CCNC(=O)c1ccc(NS(C)(=O)=O)cc1

-1.6990 -1.1250 0.0461 YES

329.


2.0000 1.7307 0.0618 YES

330.


-0.5190 -0.4789 9.0678 No

331.


-1.6560 -1.7206 15.0177 No

332.


-1.6560 -1.6632 15.0177 No

333.

Validation COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@H]1CCCO1

-1.2480 -0.7102 0.0576 YES

334.

Validation COc1cc2nc(nc(N)c2cc1OC)N1CCN(CC1)C(=O)[C@@H]1CCCO1

-1.2480 -0.6916 0.0552 YES

335.

Calibration CC(C)(C)c1ccc(cc1)[C@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 1.1132 0.0549 YES

336.

Validation CC(C)(C)c1ccc(cc1)[C@@H](O)CCCN1CCC(CC1)C(O)(c1ccccc1)c1ccccc1

1.2220 1.1318 0.0525 YES

337.

Calibration COc1ccc(cc1OC)C1CCN(CC1)CC[C@H]1CCOc2ccccc12

1.5230 1.3484 0.0503 YES

338.

Training COc1ccc(cc1OC)C1CCN(CC1)CC[C@@H]1CCOc2ccccc12

1.5230 1.3670 0.0479 YES

339.

Training C[C@@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.3285 0.0370 YES

340.

Validation C[C@H](CC(c1ccccc1)c1ccccc1)NC(C)(C)C

0.1670 -0.3471 0.0393 YES

341.

Training CSc1ccc2Sc3ccccc3N(CC[C@H]3CCCCN3C)c2c1

0.4090 0.3949 0.1019 YES

342.

Calibration CSc1ccc2Sc3ccccc3N(CC[C@@H]3CCCCN3C)c2c1

0.4090 0.4135 0.0996 YES

343.

Training COc1ccc(CNC[C@H](O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

0.0180 0.0488 1.0628 YES

344.

Validation COc1ccc(CNC[C@@H](O)COc2ccc3[nH]c(=O)ccc3c2)cc1OC

0.0180 0.0674 1.0604 YES

345.


1.6990 1.5941 1.0395 YES

346.

Training CC(C)N(CC[C@H](c1ccccc1)c1cc(C)ccc1O)C(C)C

1.6990 1.5756 1.0418 YES

347.

Training Clc1cccc(c1)N1CCN(CCCn2nc3ccccn3c2=O)CC1

-0.4620 -0.4578 5.0426 YES

348.


-0.1490 -0.1517 17.0743 No

349.

Training CCCc1nc(C)c2n1[nH]c(nc2=O)-c1cc(ccc1OCC)S(=O)(=O)N1CCN(CC)CC1

-1.1070 -1.0973 5.0719 YES

350.

Validation Coc1ccc(cc1OC)[C@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.9718 1.0563 YES

351.

Training Coc1ccc(cc1OC)[C@@](CCCN(C)CCc2ccc(O)c(OC)c2)(CCalibrationN)C(C)C

0.8540 0.8679 2.0517 YES

352.


-0.0250 -0.0694 0.0336 YES

353.

Training CC(C)CCCC(C)CCCC(C)CCC\C(C)=C\

-0.7600 -0.7510 16.0428 No

CC1=C(C)C(=O)c2ccccc2C1=O

354.


1.0460 1.0366 5.0413 YES

355.


1.0460 1.0552 5.0389 YES

356.

Training COc1ccc(NC(=O)c2ccc(cc2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

-0.2550 -0.2200 4.0391 YES

357.

Training COc1ccc(NC(=O)c2ccc(cc2F)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

-0.3220 -0.2905 7.0437 No

358.

Training COc1ccc(NC(=O)c2ccc(cc2N2CCCCC2)C(=N)N(C)C)c(c1)C(=O)Nc1ccc(Cl)cn1

0.6990 0.6749 5.0514 YES

359.


0.9590 0.8483 3.0368 YES

360.


0.3770 0.5535 6.0558 No

361.


-1.9290 -1.8582 1.0781 YES

362.

Validation Cc1nccnc1C(=O)N1CCC(CC1)[C@H](N)Cc1cc(F)c(F)cc1F

-1.7400 -0.6927 1.0773 YES

363.


-1.7710 -1.7820 1.0813 YES

364.


-1.2550 -1.2598 6.1003 No

365.


-1.1960 -1.1096 0.0364 YES

366.


-1.2150 -1.1282 0.0388 YES

367.


-0.6530 -0.6687 1.0519 YES

368.


-1.0130 -0.9991 1.0432 YES

369.

Validation CCCCN(C1CCNCC1)S(=O)(=O)c1ccc2ccccc2c1

0.1430 0.1267 0.0306 YES

370.


0.3850 0.4026 1.0507 YES

Training C1CC(CCN1)COc1ccc2cc -0.5800 -0.7689 0.0181 YES

371. ccc2c1 372.

Training Cc1ccc2ccc(OCC3CCNCC3)cc2c1

-0.5440 -0.4989 1.0260 YES

373.


-0.5440 -0.5591 1.0326 YES

374.


-1.0040 -0.7923 0.0354 YES

375.

Training Clc1ccccc1OC1CN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.5330 -0.4728 0.0565 YES

376.

Calibration Clc1cccc(OC2CN(C2)S(=O)(=O)c2ccc3CCNCCc3c2)c1

-0.5670 -0.2719 0.0712 YES

377.


-0.3200 -0.2924 0.0708 YES

378.

Training Clc1ccccc1C[C@@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.5350 -0.6458 0.0711 YES

379.

Training Clc1ccccc1C[C@H]1CCN(C1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.7190 -0.6644 0.0735 YES

380.

Calibration Clc1ccccc1OC1CCN(CC1)S(=O)(=O)c1ccc2CCNCCc2c1

-0.4620 -0.6284 0.0578 YES

381.


-2.1000 -2.0958 2.0818 YES

382.

Training F[C@H]1CN(C[C@H]1F)C(=O)[C@@H]1C[C@@H](CN1)N1CCN(CC1)c1ncccn1

-1.7320 -1.7440 3.1241 YES

383.

Calibration CC(C)(C)CNc1nc(nc(N2CCOCC2)c1N)CCalibrationN

-1.8450 -2.3539 0.0428 YES

384.


-1.7160 -1.6591 0.0366 YES

385.


1.6990 1.7856 0.0366 YES

386.

Training CCOC(=O)N1CCN(CC1)C(=O)C1(CCN(CC1)c1cc(N)ccn1)c1ccccc1

0.7700 0.4677 0.0330 YES

387.


1.3980 1.1407 1.0403 YES

388.

Training COc1ccc(CNC(=O)C2(CCN(CC2)c2cc(N)ccn2)c2cc

0.6990 0.7089 1.0376 YES

ccc2)cc1 389.


1.0970 0.6705 1.0391 YES

390.

Training COc1ccc(C(=O)NC2(CCN(CC2)c2cc(N)ccn2)c2ccccc2)c(Cl)c1

0.4690 0.5775 1.0447 YES

391.

Training Nc1ccnc(c1)N1CCC(CC1)(NC(=O)c1ccccn1)c1ccccc1

0.2600 0.0989 0.0323 YES

392.


1.5230 1.1627 0.0325 YES

393.


-0.9860 -0.1903 0.0312 YES

394.


1.6990 1.7999 1.0297 YES

395.


-0.6730 -0.7153 1.0555 YES

396.


-0.2650 -0.5188 0.0232 YES

397.


0.0600 0.1323 2.0557 YES

398.


0.0460 0.2168 0.0448 YES

399.


0.2840 0.1283 1.0424 YES

400.

Validation Nc1ccnc(c1)N1CCC(CC1)n1c2ncccc2n(CC2CC2)c1=O

0.1250 -0.9486 1.0468 YES

Documents

ars.els-cdn.com · Web view3.0822 YES 186. Training CCCCCalibrationCc1cc(cs1)-c1n[nH]c2-c3ccc(CN4CCN(C)CC4)cc3Cc12 -0.2550-0.2505 16.0581 No 187. Validation COCCCalibrationCc1cc(cs1)-c1n[nH]c2