3D Pharmacophore Models for Thromboxane A2 Receptor Antagonists

Jing Wei·Yixi Liu·Songqing Wang[(]

Tianjin Key Laboratory for Modern Drug Delivery & High-Efficiency, School of Pharmaceutical Science and Technology, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, P.R. China

Supplement

Fig. S1 Structures of compounds 33~62 in the HypoGenRefine test set

Fig. S2 Structures of compounds 63~74 in the HipHop test set

Fig. S3 The best quantitative model Hypo-1. Pharmacophore features are color-code with green for hydrogen bond acceptor (HBA), cyan for hydrophobic (H), orange for aromatic ring (RA), and black for excluded volumes (EV)

Fig. S4 Plot of predicted activities against experimental values (Ki in nM) of the HypoGen training and test sets

Fig. S5 The mapping of 5 (pink) and 6 (green) with models. a: Hypo-1 model; b: Hypo-1 model without EV1 and EV2 . Color coding of pharmacophore features is as described for Fig. S3

Fig. S6 The best qualitative model Hypo-2. Color coding of pharmacophore features is as described for Fig. S3

Fig. S7 Hypo-2 model mapped with some of compound 27-purple and 68-green. Color coding of pharmacophore features is as described for Fig. S3

Fig. S8 Hypo-2 model mapped with some of compound 70 (purple) and 71 (green). Color coding of pharmacophore features is as described for Fig. S3

Fig. S9 Hypo-2 model mapped with some of compound 28 (light blue) and 72 (purple). Color coding of pharmacophore features is as described for Fig. S3

Fig. S10 Hypo-2 model mapped with some of compound 73 (green) and 74 (purple). Color coding of pharmacophore features is as described for Fig. S3


Table S1 Experimental biological data and estimated Ki of HypoGen test set molecules based on Hypo-1 model

No. / Ref / Act Ki
[nM] / Est Ki
[nM] / Error / Act Ki scalea / Est Ki
scalea
42 / 11 / 1.8 / 0.75 / -2.4 / +++ / +++
43 / 11 / 2.7 / 0.79 / -3.4 / +++ / +++
44 / 11 / 3.2 / 1.7 / -1.9 / +++ / +++
45 / 11 / 3.4 / 1.2 / -2.8 / +++ / +++
46 / 11 / 3.6 / 9.9 / +2.8 / +++ / +++
36 / 11 / 3.7 / 2.4 / -1.5 / +++ / +++
47 / 11 / 9.6 / 5.9 / -1.6 / +++ / +++
39 / 12 / 14 / 7.3 / -1.9 / ++ / +++
48 / 11 / 15 / 4.8 / -3.1 / ++ / +++
40 / 12 / 18 / 23 / +1.3 / ++ / ++
50 / 13 / 20 / 3.2 / -6.3 / ++ / ++
35 / 11 / 37 / 12 / -3.1 / ++ / ++
38 / 14 / 40 / 23 / -1.7 / ++ / ++
51 / 13 / 40 / 38 / -1.1 / ++ / ++
52 / 13 / 40 / 29 / -1.4 / ++ / ++
49 / 11 / 46 / 25 / -1.8 / ++ / ++
33 / 11 / 63 / 15 / -4.2 / ++ / ++
53 / 13 / 70 / 20 / -3.5 / ++ / ++
54 / 13 / 70 / 20 / -3.5 / ++ / ++
37 / 12 / 77 / 25 / -3.1 / ++ / ++
55 / 13 / 80 / 24 / -3.3 / ++ / ++
34 / 15 / 120 / 360 / +3.0 / ++ / ++
60 / 13 / 170 / 240 / +1.4 / ++ / ++
56 / 13 / 170 / 35 / -4.9 / ++ / ++
41 / 15 / 490 / 410 / -1.2 / ++ / ++
61 / 13 / 530 / 340 / -2.2 / ++ / ++
62 / 13 / 14700 / 5000 / -2.9 / + / +
57 / 13 / 19700 / 2200 / -9.0 / + / +
58 / 13 / 27300 / 12000 / -2.3 / + / +
59 / 13 / 46200 / 28000 / -1.7 / + / +
a Activity scale: highly active (10 nM, +++), moderately active (10~1000 nM, ++), or inactive (>1000 nM, +)


Table S2 Best fit values (Fit) of the TXARs HipHop training and test set mapped on the best HipHop model Hypo-2

TXRAs training set / TXRAs test set
No. / Fita / Mapped featureb / No. / Fita / Mapped featureb
HBA1 / HBA2 / H1 / H2 / HBA1 / HBA2 / H1 / H2
36 / 3.92 / + / + / + / + / 19 / 3.69 / + / + / + / +
21 / 3.02 / + / + / + / + / 43 / 3.08 / + / + / + / +
26 / 3.73 / + / + / + / + / 63 / 3.65 / + / + / + / +
27 / 3.96 / + / + / + / + / 69 / 3.34 / + / + / + / +
29 / 3.78 / + / + / + / + / 68 / 3.96 / + / + / + / +
30 / 3.88 / + / + / + / + / 65 / 3.87 / + / + / + / +
31 / 3.05 / + / + / + / + / 64 / 3.19 / + / + / + / +
32 / 3.65 / + / + / + / + / 66 / 3.33 / + / + / + / +
28 / 3.05 / + / + / + / + / 67 / 3.53 / + / + / + / +
70 / 3.08 / + / + / + / +
71 / 3.27 / + / + / + / +
72 / 3.18 / + / + / + / +
73 / 3.28 / + / + / + / +
74 / 3.54 / + / + / + / +
a The number represents the best fit of each molecule to the hypothesis. The higher the best fit value is, the better a molecule maps the features of a hypothesis. The best fit value of 4.00 means a perfect mapping of the molecule to the hypothesis
b The “+” sign means the chemical feature of a compound maps the corresponding feature of the hypothesis


References

1. Narisada M, Ohtani M, Watanabe F et al (1988) Synthesis and in vitro activity of various derivatives of a novel thromboxane receptor antagonist, (±)-(5Z)-7-[3-endo[(phenylsulfonyl)amino]bicyclo[2.2.1]hept-2-exo-yl]heptenoic acid. J Med Chem 31:1847–1854

2. Fukumoto S, Shiraishi M, Terashita Z et al (1992) Synthesis and thromboxane A2 /prostaglandin H2 receptor antagonistic activity of phenol derivatives. J Med Chem 35:2202–2209

3. Misra RN, Brown BR, Sher PM et al (1993) Ogletree interphenylene 7-oxabicyclo[2.2.1] heptane oxazoles, highly potent, selective, and long- acting thromboxane A2 receptor antagonistst. J Med Chem 36:1401–1417

4. Cimetière B, Dubuffet T, Muller O et al (1998) Synthesis and biological evaluation of new tetrahydronaphthalene derivatives as thromboxane receptor antagonists. Bioorg Med Chem Lett 8:1375–1380

5. Alan JM, Robert G, David S et al (1992) Thromboxane receptor antagonism combined with thromboxane synthase inhibition. 2. Synthesis and biological activity of 8-(benzenesulfonamido)-7-(3-pyridinyl)octanoic acid and related compounds. J Med Chem 35:4362-4365

6. Tanaka T, Fukuta Y, Higashino R et al (1998) Antiplatelet effect of Z-335, a new orally active and long-lasting thromboxane receptor antagonist. Eur J Pharmacol 357:53–60

7. Hanson J, Dogné JM, Ghiotto J et al (2007) Design, synthesis, and SAR study of a series of N-alkyl-N´-[2-(aryloxy)-5-nitrobenzenesulfonyl]ureas and-cyanoguanidine as selective antagonists of the TPα and TPβ isoforms of the human thromboxane A2 receptor. J Med Chem 50:3928–3936

8. Ohno M, Miyamoto M, Hoshi K et al (2005) Development of dual-acting benzofurans for thromboxane A2 receptor antagonist and prostacyclin receptor agonist: synthesis, structure-activity relationship, and evaluation of benzofuran derivatives. J Med Chem 48:5279-5294

9. Ohno M, Tanaka Y, Miyamoto M et al (2006) Development of 3,4-dihydro-2H-benzo[1,4]oxazine derivatives as dual thromboxane A2 receptor antagonists and prostacyclin receptor agonists. Bioorg Med Chem 14:2005–2021

10. Michaux C, Dogné JM, Rolin S (2003) A pharmacophore model for sulphonyl-urea (-cyanoguanidine) compounds with dual action, thromboxane receptor antagonists and thromboxane synthase inhibitors. Eur J Med Chem 38:703-710

11. Ohshima E, Takami H, Sato H et al (1992) Non-prostanoid thromboxane A2 receptor antagonists with a dibenzoxepin ring system. 2. J Med Chem 35:3402–3413

12. Ohshima E, Takami H, Sato H et al (1992) Non-prostanoid thromboxane A2 receptor antagonists with a dibenzoxepin ring system. 1. J Med Chem 35:3394–3402

13. Cozzi P, Giordani A, Menichincheri M et al (1994) Agents combining thromboxane receptor antagonism with thromboxane synthase inhibition: [[[2-(1H-imidazol-1-yl)ethylidene]amino]oxy]alkanoic acids. J Med Chem 37:3588–3604

14. Ohshima E, Sato H, Obase H et al (1993) Dibenzoxepin derivatives: thromboxane A2 synthase inhibition and thromboxane A2 receptor antagonism combined in one molecule. J Med Chem 36:1613–1618

15. Ohshima E, Takami H, Harakawa H et al (1993) Dibenz[b,e]oxepin derivatives: novel antiallergic agents possessing thromboxane A2 and histamine H1 dual antagonizing activity. 1. J Med Chem 36:417–420

- 3 -

[(]Tel.: +86-022-87402196; Fax: +86-022-27892025; e-mail: .