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Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach

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Abstract

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme that plays a vital role in obesity-induced type 2 diabetes and fatty acid metabolism. To identify dual inhibitors of Acetyl-CoA carboxylase1 and Acetyl-CoA carboxylase2, a pharmacophore modelling approach has been employed. The best HypoGen pharmacophore model for ACC2 inhibitors (Hypo1_ACC2) consists of one hydrogen bond acceptor, one hydrophobic aliphatic and one hydrophobic aromatic feature, whereas the best pharmacophore (Hypo1_ACC1) for ACC1 consists of one additional hydrogen-bond donor (HBD) features. The best pharmacophore hypotheses were validated by various methods such as test set, decoy set and Cat-Scramble methodology. The validated pharmacophore models were used to screen several small-molecule databases, including Specs, NCI, ChemDiv and Natural product databases to identify the potential dual ACC inhibitors. The virtual hits were then subjected to several filters such as estimated \(\text{ IC}_{50}\) value, quantitative estimation of drug-likeness and molecular docking analysis. Finally, three novel compounds with diverse scaffolds were selected as potential starting points for the design of novel dual ACC inhibitors.

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References

  1. Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, Marks JS (2003) Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. J Am Med Assoc 289:76–79. doi:10.1001/jama.289.1.76

    Article  Google Scholar 

  2. Bengtsson C, Blaho S, Saitton DB, Brickmann K, Broddefalk J, Davidsson Ö, Drmota T, Folmer R, Hallberg K, Hallén S (2011) Design of small molecule inhibitors of acetyl-CoA carboxylase 1 and 2 showing reduction of hepatic malonyl-CoA levels in vivo in obese Zucker rats. Bioorg Med Chem 19:3039–3053. doi:10.1016/j.bmc.2011.04.014

  3. http://www.who.int/diabetes/en/. Accessed Sept 2010

  4. Hulver MW, Berggren JR, Cortright RN, Dudek RW, Thompson RP, Pories WJ, MacDonald KG, Cline GW, Shulman GI, Dohm GL (2003) Skeletal muscle lipid metabolism with obesity. Am J Physiol Endocrinol Metab 284:E741–E747. doi:10.1152/ajpendo.00514.2002

    PubMed  CAS  Google Scholar 

  5. Sinha R, Dufour S, Petersen KF, LeBon V, Enoksson S, Ma YZ, Savoye M, Rothman DL, Shulman GI, Caprio S (2002) Assessment of skeletal muscle triglyceride content by 1H nuclear magnetic resonance spectroscopy in lean and obese adolescents. Diabetes 51:1022–1027. doi:10.2337/diabetes.51.4.1022

    Article  PubMed  CAS  Google Scholar 

  6. Kusunoki J, Kanatani A, Moller DE (2006) Modulation of fatty acid metabolism as a potential approach to the treatment of obesity and the metabolic syndrome. Endocrine 29:91–100. doi:10.1385/ENDO:29:1:91

    Google Scholar 

  7. Singh U, Gangwal RP, Dhoke GV, Prajapati R, Damre M, Sangamwar AT (2012) 3D-QSAR and molecular docking analysis of (4-piperidinyl)-piperazines as acetyl-CoA carboxylases inhibitors. Arabian J Chem. doi:10.1016/j.arabjc.2012.10.023

  8. McGarry JD, Foster DW (1980) Regulation of hepatic fatty acid oxidation and ketone body production. Annu Rev Biochem 49: 395–420. doi:10.1146/annurev.bi.49.070180.002143

    Google Scholar 

  9. Harwood HJ, Petras SF, Shelly LD, Zaccaro LM, Perry DA, Makowski MR, Hargrove DM, Martin KA, Tracey WR, Chapman JG (2003) Isozyme-nonselective N-substituted bipiperidylcarboxamide acetyl-CoA carboxylase inhibitors reduce tissue malonyl-CoA concentrations, inhibit fatty acid synthesis, and increase fatty acid oxidation in cultured cells and in experimental animals. J Biol Chem 278:37099–37111. doi:10.1074/jbc.M304481200

    Article  PubMed  CAS  Google Scholar 

  10. Harwood J, James H (2005) Treating the metabolic syndrome: acetyl-CoA carboxylase inhibition. Expert Opin Ther Targets 9:267–281. doi:10.1517/14728222.9.2.267

    Article  PubMed  CAS  Google Scholar 

  11. Corbett JW (2009) Review of recent acetyl-CoA carboxylase inhibitor patents: mid-2007–2008. Expert Opin Ther Pat 19: 943–956. doi:10.1517/13543770902862180

    Google Scholar 

  12. Mao J, Chirala SS, Wakil SJ (2003) Human acetyl-CoA carboxylase 1 gene: presence of three promoters and heterogeneity at the 5\(^{{\prime }{2}}\)-untranslated mRNA region. Proc Natl Acad Sci USA 100:7515–7520. doi: 10.1073/pnas.1332670100

    Article  PubMed  CAS  Google Scholar 

  13. Abu-Elheiga L, Almarza-Ortega DB, Baldini A, Wakil SJ (1997) Human acetyl-CoA carboxylase 2 molecular cloning, characterization, chromosomal mapping, and evidence for two isoforms. J Biol Chem 272:10669–10677. doi:10.1074/jbc.272.16.10669

    Article  PubMed  CAS  Google Scholar 

  14. Abu-Elheiga L, Matzuk MM, Kordari P, Oh WK, Shaikenov T, Gu Z, Wakil SJ (2005) Mutant mice lacking acetyl-CoA carboxylase 1 are embryonically lethal. Proc Natl Acad Sci USA 102: 12011–12016. doi:10.1073/pnas.0505714102

    Google Scholar 

  15. Savage DB, Choi CS, Samuel VT, Liu Z, Zhang D, Wang A, Zhang X, Cline GW, Yu XX, Geisler JG (2006) Reversal of diet-induced hepatic steatosis and hepatic insulin resistance by antisense oligonucleotide inhibitors of acetyl-CoA carboxylases 1 and 2. J Clin Invest 116:817–824. doi:10.1172/JCI27300

    Article  PubMed  CAS  Google Scholar 

  16. Li H, Sutter J, Hoffmann R (2000) HypoGen: an automated system for generating 3D predictive pharmacophore models, vol 2. Pharmacophore Perception, Development, and Use in Drug Design. International Univ Line, La Jolla

  17. Gu YG, Weitzberg M, Clark RF, Xu X, Li Q, Lubbers NL, Yang Y, Beno DWA, Widomski DL, Zhang T (2007) N-3-[2-(4-Alkoxyphenoxy) thiazol-5-yl]-1-methylprop-2-ynyl carboxy derivatives as acetyl-CoA carboxylase inhibitors improvement of cardiovascular and neurological Liabilities via structural modifications. J Med Chem 50:1078–1082. doi:10.1021/jm070035a

    Article  PubMed  CAS  Google Scholar 

  18. Clark RF, Zhang T, Wang X, Wang R, Zhang X, Camp HS, Beutel BA, Sham HL, Gu YG (2007) Phenoxy thiazole derivatives as potent and selective acetyl-CoA carboxylase 2 inhibitors: modulation of isozyme selectivity by incorporation of phenyl ring substituents. Bioorg Med Chem Lett 17:1961–1965. doi:10.1016/j.bmcl.2007.01.022

    Article  PubMed  CAS  Google Scholar 

  19. Clark RF, Zhang T, Xin Z, Liu G, Wang Y, Hansen TM, Wang X, Wang R, Zhang X, Frevert EU (2006) Structure-activity relationships for a novel series of thiazolyl phenyl ether derivatives exhibiting potent and selective acetyl-CoA carboxylase 2 inhibitory activity. Bioorg Med Chem Lett 16:6078–6081. doi:10.1016/j.bmcl.2006.08.100

    Article  PubMed  CAS  Google Scholar 

  20. Gu YG, Weitzberg M, Clark RF, Xu X, Li Q, Zhang T, Hansen TM, Liu G, Xin Z, Wang X (2006) Synthesis and structure-activity relationships of N-3-[2-(4-alkoxyphenoxy) thiazol-5-yl]-1-methylprop-2-ynyl carboxy derivatives as selective acetyl-CoA carboxylase 2 inhibitors. J Med Chem 49:3770–3773. doi:10.1021/jm060484v

    Article  PubMed  CAS  Google Scholar 

  21. Xu X, Weitzberg M, Keyes RF, Li Q, Wang R, Wang X, Zhang X, Frevert EU, Camp HS, Beutel BA (2007) The synthesis and structure-activity relationship studies of selective acetyl-CoA carboxylase inhibitors containing 4-(thiazol-5-yl) but-3-yn-2-amino motif: polar region modifications. Bioorg Med Chem Lett 17: 1803–1807. doi:10.1016/j.bmcl.2006.12.047

    Google Scholar 

  22. Haque TS, Liang N, Golla R, Seethala R, Ma Z, Ewing WR, Cooper CB, Pelleymounter MA, Poss MA, Cheng D (2009) Potent biphenyl-and 3-phenyl pyridine-based inhibitors of acetyl-CoA carboxylase. Bioorg Med Chem Lett 19:5872–5876. doi:10.1016/j.bmcl.2009.08.077

    Article  PubMed  CAS  Google Scholar 

  23. Keil S, Müller M, Zoller G, Haschke G, Schroeter K, Glien M, Ruf S, Focken I, Herling AW, Schmoll D (2010) Identification and synthesis of novel inhibitors of acetyl-CoA carboxylase with in vitro and in vivo efficacy on fat oxidation. J Med Chem 53: 8679–8687. doi:10.1021/jm101179e

    Google Scholar 

  24. Corbett JW, Freeman-Cook KD, Elliott R, Vajdos F, Rajamohan F, Kohls D, Marr E, Zhang H, Tong L, Tu M (2010) Discovery of small molecule isozyme non-specific inhibitors of mammalian acetyl-CoA carboxylase 1 and 2. Bioorg Med Chem Lett 20: 2383–2388. doi:10.1016/j.bmcl.2009.04.091

    Google Scholar 

  25. Smellie A, Teig SL, Towbin P (1995) Poling: promoting conformational variation. J Comput Chem 16:171–187. doi:10.1002/jcc.540160205

    Article  CAS  Google Scholar 

  26. Dhoke GV, Gangwal RP, Sangamwar AT (2012) A combined ligand and structure based approach to design potent PPAR-alpha agonists. J Mol Struct 1028:22–30. doi:10.1016/j.molstruc.2012.06.032

    Article  CAS  Google Scholar 

  27. Discovery Studio, Version 2.5 (2009) Accelrys Inc, San Diego, CA

  28. Kristam R, Gillet VJ, Lewis RA, Thorner D (2005) Comparison of conformational analysis techniques to generate pharmacophore hypotheses using catalyst. J Chem Inf Model 45:461–476. doi:10.1021/ci049731z

    Google Scholar 

  29. Singh R, Balupuri A, Sobhia ME (2013) Development of 3D-pharmacophore model followed by successive virtual screening, molecular docking and ADME studies for the design of potent CCR2 antagonists for inflammation-driven diseases. Mol Simul 39:49–58. doi:10.1080/08927022.2012.701743

    Google Scholar 

  30. Gupta S, Fallarero A, Järvinen P, Karlsson D, Johnson MS, Vuorela PM, Mohan CG (2011) Discovery of dual binding site acetylcholinesterase inhibitors identified by pharmacophore modeling and sequential virtual screening techniques. Bioorg Med Chem Lett 21:1105–1112. doi:10.1016/j.bmcl.2010.12.131

  31. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49:6789–6801. doi:10.1021/jm0608356

    Article  PubMed  CAS  Google Scholar 

  32. Cereto-Massagué A, Guasch L, Valls C, Mulero M, Pujadas G, Garcia-Vallvé S (2012) DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets. Bioinformatics 28:1661–1662. doi:10.1093/bioinformatics/bts249

    Article  PubMed  Google Scholar 

  33. Singh U, Gangwal R, Prajapati R, Dhoke G, Sangamwar A (2012) 3D QSAR Pharmacophore based virtual screening and molecular docking studies to identify novel matrix metalloproteinase 12 (MMP-12) inhibitors. Mol Simul. doi:10.1080/08927022.2012.731506

  34. Gupta S, Gopi Mohan C (2011) 3D-pharmacophore model based virtual screening to identify dual-binding site and selective acetylcholinesterase inhibitors. Med Chem Res 20:1422–1430. doi:10.1007/s00044-010-9373-7

    Article  CAS  Google Scholar 

  35. Bickerton GR, Paolini GV, Besnard J, Muresan S, Hopkins AL (2012) Quantifying the chemical beauty of drugs. Nat Chem 4: 90–98. doi:10.1038/nchem.1243

    Google Scholar 

  36. Brenk R, Schipani A, James D, Krasowski A, Gilbert IH, Frearson J, Wyatt PG (2007) Lessons learnt from assembling screening libraries for drug discovery for neglected diseases. ChemMedChem 3:435–444. doi:10.1002/cmdc.200700139

    Article  Google Scholar 

  37. Glide Version, 5.5 (2009) Schrödinger. LLC, New York, NY

  38. Ambure PS, Gangwal RP, Sangamwar AT (2011) 3D-QSAR and molecular docking analysis of biphenyl amide derivatives as \(\text{ p}38\alpha \) mitogen activated protein kinase inhibitors. Mol Divers 16: 377–388. doi:10.1007/s11030-011-9353-y

    Google Scholar 

  39. Wang Y, Bolton E, Dracheva S, Karapetyan K, Shoemaker BA, Suzek TO, Wang J, Xiao J, Zhang J, Bryant SH (2010) An overview of the PubChem BioAssay resource. Nucleic Acids Res 38: D255–D266. doi:10.1093/nar/gkp965

  40. Wagner AB (2006) SciFinder Scholar 2006: an empirical analysis of research topic query processing. J Chem Inf Model 46:767–774. doi:10.1021/ci050481b

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors acknowledge financial support from Department of Science and Technology (DST), New Delhi.

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Correspondence to Abhay T. Sangamwar.

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Anuseema Bhadauriya and Gaurao V. Dhoke contributed equally to this study.

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Bhadauriya, A., Dhoke, G.V., Gangwal, R.P. et al. Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach. Mol Divers 17, 139–149 (2013). https://doi.org/10.1007/s11030-013-9425-2

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  • DOI: https://doi.org/10.1007/s11030-013-9425-2

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