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Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors

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Abstract

Using a self-organizing map (SOM) and support vector machine, two classification models were built to predict whether a compound is a selective inhibitor toward the two Acyl-coenzyme A: cholesterol acyltransferase (ACAT) isozymes, ACAT-1 and ACAT-2. A dataset of 97 ACAT inhibitors was collected. For each molecule, the global descriptors, 2D and 3D property autocorrelation descriptors and autocorrelation of surface properties were calculated from the program ADRIANA.Code. The prediction accuracies of the models (based on the training/ test set splitting by SOM method) for the test sets are 88.9 % for SOM1, 92.6 % for SVM1 model. In addition, the extended connectivity fingerprints (ECFP_4) for all the molecules were calculated and the structure–activity relationship of selective ACAT inhibitors was summarized, which may help find important structural features of inhibitors relating to the selectivity of ACAT isozymes.

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References

  1. Pols TW, Bonta PI, Pires NM, Otermin I, Vos M, de Vries MR, van Eijk M, Roelofsen J, Havekes LM, Quax PH, Kuilenburg AB, de Waard V, Pannekoek H, de Vries CJ (2010) 6-mercaptopurine inhibits atherosclerosis in apolipoprotein e*3-Leiden transgenic mice through atheroprotective actions on monocytes and macrophages. Arterioscler Thromb Vasc Biol 30: 1591–1597. doi:10.1161/ATVBAHA.110.205674

    Article  PubMed  CAS  Google Scholar 

  2. Ikenoya M, Yoshinaka Y, Kobayashi H, Kawamine K, Shibuya K, Sato F, Sawanobori K, Watanabe T, Miyazaki A (2007) A selective ACAT-1 inhibitor, K-604, suppresses fatty streak lesions in fat-fed hamsters without affecting plasma cholesterol levels. Atherosclerosis 191: 290–297. doi:10.1016/j.atherosclerosis.2006.05.048

    Article  PubMed  CAS  Google Scholar 

  3. Libby P (2005) The forgotten majority: unfinished business in cardiovascular risk reduction. J Am Coll Cardiol 46: 1225–1228. doi:10.1016/j.jacc.2005.07.006

    Article  PubMed  Google Scholar 

  4. Miyazaki A, Kanome T, Watanabe T (2005) Inhibitors of acyl-coenzyme A: cholesterol acyltransferase. Curr Drug Targets Cardiovasc Haematol Disord 5: 463–469

    Article  PubMed  CAS  Google Scholar 

  5. Lada AT, Davis M, Kent C, Chapman J, Tomoda H, Omura S, Rudel LL (2004) Identification of ACAT1- and ACAT2-specific inhibitors using a novel, cell-based fluorescence assay: individual ACAT uniqueness. J Lipid Res 45: 378–386. doi:10.1194/jlr.D300037-JLR200

    Article  PubMed  CAS  Google Scholar 

  6. Sliskovic DR, Picard JA, Krause BR (2002) ACAT inhibitors: the search for a novel and effective treatment of hypercholesterolemia and atherosclerosis. Prog Med Chem 39: 121–171

    Article  PubMed  CAS  Google Scholar 

  7. Alegret M, Llaverias G, Silvestre JS (2004) Acyl coenzyme A:cholesterol acyltransferase inhibitors as hypolipidemic and antiatherosclerotic drugs. Methods Find Exp Clin Pharmacol 26: 563–586. doi:10.1358/mf.2004.26.7.863738

    Article  PubMed  CAS  Google Scholar 

  8. Meuwese MC, Franssen R, Stroes ES, Kastelein JJ (2006) And then there were acyl coenzyme A:cholesterol acyl transferase inhibitors. Curr Opin Lipidol 17: 426–430. doi:10.1097/01.mol.0000236369.50378.6e

    Article  PubMed  CAS  Google Scholar 

  9. Chang TY, Li BL, Chang CC, Urano Y (2009) Acyl-coenzyme A:cholesterol acyltransferases. Am J Physiol Endocrinol Metab 297: E1–9. doi:10.1152/ajpendo.90926.2008

    Article  PubMed  CAS  Google Scholar 

  10. Chang CC, Huh HY, Cadigan KM, Chang TY (1993) Molecular cloning and functional expression of human acyl-coenzyme A:cholesterol acyltransferase cDNA in mutant Chinese hamster ovary cells. J Biol Chem 268: 20747–20755

    PubMed  CAS  Google Scholar 

  11. Anderson RA, Joyce C, Davis M, Reagan JW, Clark M, Shelness GS, Rudel LL (1998) Identification of a form of acyl-CoA:cholesterol acyltransferase specific to liver and intestine in nonhuman primates. J Biol Chem 273: 26747–26754. doi:10.1074/jbc.273.41.26747

    Article  PubMed  CAS  Google Scholar 

  12. Parini P, Davis M, Lada AT, Erickson SK, Wright TL, Gustafsson U, Sahlin S, Einarsson C, Eriksson M, Angelin B, Tomoda H, Omura S, Willingham MC, Rudel LL (2004) ACAT2 is localized to hepatocytes and is the major cholesterol-esterifying enzyme in human liver. Circulation 110: 2017–2023. doi:10.1161/01.CIR.0000143163.76212.0B

    Article  PubMed  CAS  Google Scholar 

  13. Ohshiro T, Tomoda H (2011) Isoform-specific inhibitors of ACATs: recent advances and promising developments. Future Med Chem 3: 2039–2061. doi:10.4155/fmc.11.158

    Article  PubMed  CAS  Google Scholar 

  14. Tardif JC, Gregoire J, L’Allier PL, Anderson TJ, Bertrand O, Reeves F, Title LM, Alfonso F, Schampaert E, Hassan A, McLain R, Pressler ML, Ibrahim R, Lesperance J, Blue J, Heinonen T, Rodes-Cabau J (2004) Effects of the acyl coenzyme A:cholesterol acyltransferase inhibitor avasimibe on human atherosclerotic lesions. Circulation 110: 3372–3377. doi:10.1161/01.CIR.0000147777.12010.EF

    Article  PubMed  CAS  Google Scholar 

  15. Nissen SE, Tuzcu EM, Brewer HB, Sipahi I, Nicholls SJ, Ganz P, Schoenhagen P, Waters DD, Pepine CJ, Crowe TD, Davidson MH, Deanfield JE, Wisniewski LM, Hanyok JJ, Kassalow LM (2006) Effect of ACAT inhibition on the progression of coronary atherosclerosis. N Engl J Med 354: 1253–1263. doi:10.1056/NEJMoa054699

    Article  PubMed  CAS  Google Scholar 

  16. Meuwese MC, de Groot E, Duivenvoorden R, Trip MD, Ose L, Maritz FJ, Basart DC, Kastelein JJ, Habib R, Davidson MH, Zwinderman AH, Schwocho LR, Stein EA (2009) ACAT inhibition and progression of carotid atherosclerosis in patients with familial hypercholesterolemia: the CAPTIVATE randomized trial. JAMA 301: 1131–1139. doi:10.1001/jama.301.11.1131

    Article  PubMed  CAS  Google Scholar 

  17. Cho KH, An S, Lee WS, Paik YK, Kim YK, Jeong TS (2003) Mass-production of human ACAT-1 and ACAT-2 to screen isoform-specific inhibitor: a different substrate specificity and inhibitory regulation. Biochem Biophys Res Commun 309: 864–872. doi:S0006291X03016796

    Article  PubMed  CAS  Google Scholar 

  18. Ohshiro T, Matsuda D, Sakai K, Degirolamo C, Yagyu H, Rudel LL, Omura S, Ishibashi S, Tomoda H (2011) Pyripyropene A, an acyl-coenzyme A:cholesterol acyltransferase 2-selective inhibitor, attenuates hypercholesterolemia and atherosclerosis in murine models of hyperlipidemia. Arterioscler Thromb Vasc Biol 31: 1108–1115. doi:10.1161/ATVBAHA.111.223552

    Article  PubMed  CAS  Google Scholar 

  19. Alger HM, Brown JM, Sawyer JK, Kelley KL, Shah R, Wilson MD, Willingham MC, Rudel LL (2010) Inhibition of acyl-coenzyme A:cholesterol acyltransferase 2 (ACAT2) prevents dietary cholesterol-associated steatosis by enhancing hepatic triglyceride mobilization. J Biol Chem 285: 14267–14274. doi:10.1074/jbc.M110.118422

    Article  PubMed  CAS  Google Scholar 

  20. Sakai K, Ohte S, Ohshiro T, Matsuda D, Masuma R, Rudel LL, Tomoda H (2008) Selective inhibition of acyl-CoA:cholesterol acyltransferase 2 isozyme by flavasperone and sterigmatocystin from Aspergillus species. J Antibiot (Tokyo) 61: 568–572. doi:10.1038/ja.2008.76

    Article  CAS  Google Scholar 

  21. Jeong TS, Kim KS, Yu H, Kim MJ, Cho KH, Choi YK, Kim HC, Park HY, Lee WS (2005) Saucerneol B derivatives as human acyl-CoA: cholesterol acyltransferase inhibitors. Bioorg Med Chem Lett 15: 385–388. doi:10.1016/j.bmcl.2004.10.066

    Article  PubMed  CAS  Google Scholar 

  22. Liew CY, Ma XH, Liu X, Yap CW (2009) SVM model for virtual screening of Lck inhibitors. J Chem Inf Model 49: 877–885. doi:10.1021/ci800387z

    Article  PubMed  CAS  Google Scholar 

  23. Wang Z, Yan A (2011) Discriminating of HMG-CoA reductase inhibitors and decoys using self-organizing maps. Mol Divers 15: 655–663. doi:10.1007/s11030-010-9288-8

    Article  PubMed  CAS  Google Scholar 

  24. Hao M, Li Y, Wang Y, Zhang S (2011) A classification study of human beta(3)-adrenergic receptor agonists using BCUT descriptors. Mol Divers 15: 877–887. doi:10.1007/s11030-011-9321-6

    Article  PubMed  CAS  Google Scholar 

  25. Yan A, Wang M, Wang K, Yu C (2012) Classification of HCV NS5B polymerase inhibitors using support vector machine. Int J Mol Sci 13: 4033–4047. doi:10.3390/ijms13044033

    Article  PubMed  Google Scholar 

  26. Yan A, Nie X, Wang K, Wang M (2012) Classification of Aurora kinase inhibitors by self-organizing map (SOM) and support vector machine (SVM). Eur J Med Chem. http://10.1016/j.ejmech.2012.06.037

  27. Ohshiro T, Rudel LL, Omura S, Tomoda H (2007) Selectivity of microbial acyl-CoA: cholesterol acyltransferase inhibitors toward isozymes. J Antibiot (Tokyo) 60: 43–51. doi:10.1038/ja.2007.6

    Article  CAS  Google Scholar 

  28. Matsuda D, Ohte S, Ohshiro T, Jiang W, Rudel L, Hong B, Si S, Tomoda H (2008) Molecular target of piperine in the inhibition of lipid droplet accumulation in macrophages. Biol Pharm Bull 31: 1063–1066. doi:10.1248/bpb.31.1063

    Article  PubMed  CAS  Google Scholar 

  29. Ohshiro T, Ohte S, Matsuda D, Ohtawa M, Nagamitsu T, Sunazuka T, Harigaya Y, Rudel LL, Omura S, Tomoda H (2008) Selectivity of pyripyropene derivatives in inhibition toward acyl-CoA:cholesterol acyltransferase 2 isozyme. J Antibiot (Tokyo) 61: 503–508. doi:10.1038/ja.2008.67

    Article  CAS  Google Scholar 

  30. Ohshiro T, Matsuda D, Nagai K, Doi T, Sunazuka T, Takahashi T, Rudel LL, Omura S, Tomoda H (2009) The selectivity of beauveriolide derivatives in inhibition toward the two isozymes of acyl-CoA: cholesterol acyltransferase. Chem Pharm Bull (Tokyo) 57: 377–381. doi:JST.JSTAGE/cpb/57.377

    Article  CAS  Google Scholar 

  31. Yamazaki H, Omura S, Tomoda H (2009) Pentacecilides, new inhibitors of lipid droplet formation in mouse macrophages produced by Penicillium cecidicola FKI-3765-1: II. Structure elucidation. J Antibiot (Tokyo) 62: 207–211. doi:10.1038/ja.2009.19

    Article  CAS  Google Scholar 

  32. MOE Version 2008.10 (2012) Chemical Computing Group Inc. http://www.chemcomp.com [CP/OL]. Accessed July 2012

  33. SONNIA Software (2010) version 4. Molecular Networks GmbH: Erlangen

  34. Sadowski JGJ (1993) From atoms and bonds to three-dimensional atomic coordinates: automatic model builders. J Chem Rev 93: 2567–2581. doi:10.1021/cr00023a012

    Article  CAS  Google Scholar 

  35. ADRIANA.Code, Molecular Networks GmbH, Erlangen. http://www.molecular-networks.com

  36. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46: 3–26. doi:S0169-409X(00)00129-0

    Article  PubMed  CAS  Google Scholar 

  37. Petitjean M (1992) Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds. J Chem Inf Comput Sci 32: 331–337. doi:10.1021/ci00008a012

    Article  CAS  Google Scholar 

  38. Todeschini RCV (2000) Handbook of molecular descriptors, vol 11. Weinheim, Wiley-VCH

    Book  Google Scholar 

  39. Wagener M, Sadowski J, Gasteiger J (1995) Autocorrelation of molecular surface properties for modeling corticosteroid binding globulin and cytosolic Ah receptor activity by neural networks. J Am Chem Soc 117: 7769–7775. doi:10.1021/ja00134a023

    Article  CAS  Google Scholar 

  40. Teckentrup A, Briem H, Gasteiger J (2004) Mining high-throughput screening data of combinatorial libraries: development of a filter to distinguish hits from nonhits. J Chem Inf Comput Sci 44: 626–634. doi:10.1021/ci034223v

    Article  PubMed  CAS  Google Scholar 

  41. Rodgers JL, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42: 59–66

    Article  Google Scholar 

  42. Ivanenkov YA, Savchuk NP, Ekins S, Balakin KV (2009) Computational mapping tools for drug discovery. Drug Discov Today 14: 767–775. doi:10.1016/j.drudis.2009.05.016

    Article  PubMed  CAS  Google Scholar 

  43. Wang L, Wang Z, Yan A, Yuan Q (2011) Classification of Aurora-A kinase inhibitors using self-organizing map (SOM) and support vector machine (SVM). Mol Inform 30: 35–44. doi:10.1002/minf.201000106

    Article  Google Scholar 

  44. Hu X, Yan A (2012) In Silico models to discriminate compounds inducing and noninducing toxic myopathy. Mol Inform 31: 27–39. doi:10.1002/minf.201100067

    Article  CAS  Google Scholar 

  45. SONNIA can be obtained from Molecular Networks GmbH, Erlangen. http://www.molecular-networks.com. Accessed Juy 2012

  46. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20: 273–297

    Google Scholar 

  47. Chang CC, Lin CJ (2001) LIBSVM: a library for SVM. Software. http://www.csie.ntu.edu.tw/~cjlin/libsvm

  48. Rogers D, Hahn M (2010) Extended-connectivity fingerprints. J Chem Inf Model 50: 742–754

    Article  PubMed  CAS  Google Scholar 

  49. Bender A, Jenkins JL, Scheiber J, Sukuru SCK, Glick M, Davies JW (2009) How similar are similarity searching methods? A principal component analysis of molecular descriptor space. J Chem Inf Model 49: 108–119. doi:10.1021/ci800249s

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. School of Chemistry and Chemical Engineering, Key Laboratory for Green Process of Chemical Engineering of Xinjiang Bingtuan, Shihezi University, Xinjiang, Shihezi, 832003, China

    Ling Wang & Bin Dai

  2. State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing, 100029, China

    Maolin Wang & Aixia Yan

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  1. Ling Wang
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  2. Maolin Wang
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  3. Aixia Yan
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  4. Bin Dai
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Correspondence to Aixia Yan or Bin Dai.

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Wang, L., Wang, M., Yan, A. et al. Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors. Mol Divers 17, 85–96 (2013). https://doi.org/10.1007/s11030-012-9404-z

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