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Investigating the impact of missense mutations in hCES1 by in silico structure-based approaches

  • Grace Shema Nzabonimpa , Henrik Berg Rasmussen , Søren Brunak , Olivier Taboureau EMAIL logo and for the INDICES Consortium
Published/Copyright: February 19, 2016

Abstract

Genetic variations in drug-metabolizing enzymes have been reported to influence pharmacokinetics, drug dosage and other aspects that affect therapeutic outcomes. Most particularly, non-synonymous single-nucleotide polymorphisms (nsSNPs) resulting in amino acid changes disrupt potential functional sites responsible for protein activity, structure, or stability, which can account for individual susceptibility to disease and drug response. Investigating the impact of nsSNPs at a protein’s structural level is a key step in understanding the relationship between genetic variants and the resulting phenotypic changes. For this purpose, in silico structure-based approaches have proven their relevance in providing an atomic-level description of the underlying mechanisms. The present review focuses on nsSNPs in human carboxylesterase 1 (hCES1), an enzyme involved in drug metabolism. We highlight how prioritization of functional nsSNPs through computational prediction techniques in combination with structure-based approaches, namely molecular docking and molecular dynamics simulations, is a powerful tool in providing insight into the underlying molecular mechanisms of nsSNPs phenotypic effects at microscopic level. Examples of in silico studies of carboxylesterases (CESs) are discussed, ranging from exploring the effect of mutations on enzyme activity to predicting the metabolism of new hCES1 substrates as well as to guiding rational design of CES-selective inhibitors.


Corresponding author: Olivier Taboureau, INSERM, UMRS 973, MTi, Université Paris Diderot, 75205 Paris Cedex 13, France, Phone: +33 1 57 27 82 79, E-mail: ; and Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark

References

1. Tatonetti NP, Liu T, Altman RB. Predicting drug side-effects by chemical systems biology. Genome Biol 2009;10:238.10.1186/gb-2009-10-9-238Search in Google Scholar

2. Tomalik-Scharte D, Lazar A, Fuhr U, Kirchheiner J. The clinical role of genetic polymorphisms in drug-metabolizing enzymes. Pharmacogenomics J 2008;8:4–15.10.1038/sj.tpj.6500462Search in Google Scholar

3. Li J, Zhang L, Zhou H, Stoneking M, Tang K. Global patterns of genetic diversity and signals of natural selection for human ADME genes. Hum Mol Genet 2011;20:528–40.10.1093/hmg/ddq498Search in Google Scholar

4. Zhou S-F, Liu J-P, Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug Metab Rev 2009;41:89–295.10.1080/03602530902843483Search in Google Scholar

5. Sim SC, Kacevska M, Ingelman-Sundberg M. Pharmacogenomics of drug-metabolizing enzymes: a recent update on clinical implications and endogenous effects. Pharmacogenomics J 2013;13:1–11.10.1038/tpj.2012.45Search in Google Scholar

6. Redinbo MR, Potter PM. Mammalian carboxylesterases: from drug targets to protein therapeutics. Drug Discov Today 2005;10:313–25.10.1016/S1359-6446(05)03383-0Search in Google Scholar

7. Satoh T, Hosokawa M. The mammalian carboxylesterases: from molecules to functions. Annu Rev Pharmacol Toxicol 1998;38:257–88.10.1146/annurev.pharmtox.38.1.257Search in Google Scholar PubMed

8. Hosokawa M. Structure and catalytic properties of carboxylesterase isozymes involved in metabolic activation of prodrugs. Molecules 2008;13:412–31.10.3390/molecules13020412Search in Google Scholar PubMed PubMed Central

9. Sun Z, Murry DJ, Sanghani SP, Davis WI, Kedishvili NY, Zou Q, et al. Methylphenidate is stereoselectively hydrolyzed by human carboxylesterase CES1A1. J Pharmacol Exp Ther 2004;310: 469–76.10.1124/jpet.104.067116Search in Google Scholar PubMed

10. Takai S, Matsuda A, Usami Y, Adachi T, Sugiyama T, Katagiri Y, et al. Hydrolytic profile for ester- or amide-linkage by carboxylesterases pI 5.3 and 4.5 from human liver. Biol Pharm Bull 1997;20:869–73.10.1248/bpb.20.869Search in Google Scholar PubMed

11. Humerickhouse R, Lohrbach K, Li L, Bosron WF, Dolan ME. Characterization of CPT-11 hydrolysis by human liver carboxylesterase isoforms hCE-1 and hCE-2. Cancer Res 2000;60: 1189–92.Search in Google Scholar

12. Tabata T, Katoh M, Tokudome S, Nakajima M, Yokoi T. Identification of the cytosolic carboxylesterase catalyzing the 5′-deoxy-5-fluorocytidine formation from capecitabine in human liver. Drug Metab Dispos 2004;32:1103–10.10.1124/dmd.104.000554Search in Google Scholar

13. Pindel EV, Kedishvili NY, Abraham TL, Brzezinski MR, Zhang J, Dean RA, et al. Purification and cloning of a broad substrate specificity human liver carboxylesterase that catalyzes the hydrolysis of cocaine and heroin. J Biol Chem 1997;272: 14769–75.10.1074/jbc.272.23.14769Search in Google Scholar

14. Zhang J, Burnell JC, Dumaual N, Bosron WF. Binding and hydrolysis of meperidine by human liver carboxylesterase hCE-1. J Pharmacol Exp Ther 1999;290:314–8.10.1016/S0022-3565(24)34901-8Search in Google Scholar

15. Collins FS, Brooks LD, Chakravarti A. A DNA polymorphism discovery resource for research on human genetic variation. Genome Res 1998;8:1229–31.10.1101/gr.8.12.1229Search in Google Scholar

16. Joerger AC, Ang HC, Fersht AR. Structural basis for understanding oncogenic p53 mutations and designing rescue drugs. Proc Natl Acad Sci USA 2006;103:15056–61.10.1073/pnas.0607286103Search in Google Scholar

17. Bohl CE, Wu Z, Miller DD, Bell CE, Dalton JT. Crystal structure of the T877A human androgen receptor ligand-binding domain complexed to cyproterone acetate provides insight for ligand-induced conformational changes and structure-based drug design. J Biol Chem 2007;282:13648–55.10.1074/jbc.M611711200Search in Google Scholar

18. Sherry ST, Ward M, Sirotkin K. dbSNP-database for single nucleotide polymorphisms and other classes of minor genetic variation. Genome Res 1999;9:677–9.10.1101/gr.9.8.677Search in Google Scholar

19. Hamosh A, Scott AF, Amberger J, Valle D, McKusick VA. Online Mendelian Inheritance in Man (OMIM). Hum Mutat 2000;15: 57–61.10.1002/(SICI)1098-1004(200001)15:1<57::AID-HUMU12>3.0.CO;2-GSearch in Google Scholar

20. Stenson PD, Ball EV, Mort M, Phillips AD, Shiel JA, Thomas NS, et al. Human Gene Mutation Database (HGMD®): 2003 update. Hum Mutat 2003;21:577–81.10.1002/humu.10212Search in Google Scholar

21. Mottaz A, David FP, Veuthey AL, Yip YL. Easy retrieval of single amino-acid polymorphisms and phenotype information using SwissVar. Bioinformatics 2010;26:851–2.10.1093/bioinformatics/btq028Search in Google Scholar

22. Wu J, Jiang R. Prediction of deleterious nonsynonymous single-nucleotide polymorphism for human diseases. Sci World J 2013;2013:675851.10.1155/2013/675851Search in Google Scholar

23. Bencharit S, Morton CL, Xue Y, Potter PM, Redinbo MR. Structural basis of heroin and cocaine metabolism by a promiscuous human drug-processing enzyme. Nat Struct Biol 2003;10:349–56.10.1038/nsb919Search in Google Scholar

24. Bencharit S, Morton CL, Howard-Williams EL, Danks MK, Potter PM, Redinbo MR. Structural insights into CPT-11 activation by mammalian carboxylesterases. Nat Struct Biol 2002;9:337–42.10.1038/nsb790Search in Google Scholar

25. Fleming CD, Bencharit S, Edwards CC, Hyatt JL, Tsurkan L, Bai F, et al. Structural insights into drug processing by human carboxylesterase 1: tamoxifen, mevastatin, and inhibition by benzil. J Mol Biol 2005;352:165–77.10.1016/j.jmb.2005.07.016Search in Google Scholar

26. Shoichet B, McGovern S, Wei B, Irwin J. Lead discovery using molecular docking. Curr Opin Chem Biol 2002;6:439–46.10.1016/S1367-5931(02)00339-3Search in Google Scholar

27. Yu X, Sigler SC, Hossain D, Wierdl M, Gwaltney SR, Potter PM, et al. Global and local molecular dynamics of a bacterial carboxylesterase provide insight into its catalytic mechanism. J Mol Model 2012;18:2869–83.10.1007/s00894-011-1308-9Search in Google Scholar PubMed PubMed Central

28. Salsbury FR Jr, Salsbury FR. Molecular dynamics simulations of protein dynamics and their relevance to drug discovery. Curr Opin Pharmacol 2010;10:738–44.10.1016/j.coph.2010.09.016Search in Google Scholar PubMed PubMed Central

29. Marlowe AE, Singh A, Yingling YG. The effect of point mutations on structure and mechanical properties of collagen-like fibril: a molecular dynamics study. Mater Sci Eng C 2012;32:2583–8.10.1016/j.msec.2012.07.044Search in Google Scholar

30. Priya CG, Rajith B, Garwasis N, Raju P, Solomon A, Apoorva K, et al. Screening of mutations affecting protein stability and dynamics of FGFR1 – a simulation analysis. Appl Transl Genom 2012;1:37–43.10.1016/j.atg.2012.06.002Search in Google Scholar

31. Vistoli G, Pedretti A, Mazzolari A, Testa B. In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations. Bioorg Med Chem 2010;18:320–9.10.1016/j.bmc.2009.10.052Search in Google Scholar PubMed

32. Stoddard SV, Yu X, Potter PM, Wadkins RM. In silico design and evaluation of carboxylesterase inhibitors. J Pest Sci (2004) 2010;35:240–9.10.1584/jpestics.R10-06Search in Google Scholar PubMed PubMed Central

33. Hyatt JL, Moak T, Hatfield MJ, Tsurkan L, Edwards CC, Wierdl M, et al. Selective inhibition of carboxylesterases by isatins, indole-2,3-diones. J Med Chem 2007;50:1876–85.10.1021/jm061471kSearch in Google Scholar PubMed

34. Chen Q, Luan Z-J, Cheng X, Xu J-H. Molecular dynamics investigation of the substrate binding mechanism in carboxylesterase. Biochemistry 2015;54:1841–8.10.1021/bi5015612Search in Google Scholar PubMed

35. Zhu H-J, Patrick KS, Yuan H-J, Wang J-S, Donovan JL, DeVane CL, et al. Two CES1 gene mutations lead to dysfunctional carboxylesterase 1 activity in man: clinical significance and molecular basis. Am J Hum Genet 2008;82:1241–8.10.1016/j.ajhg.2008.04.015Search in Google Scholar PubMed PubMed Central

36. CLC Drug Discovery Workbench version 2.0. Aarhus, Denmark: CLC Bio-Qiagen. Available at: http://www.clcbio.com/products/clc-drug-discovery-workbench/.Search in Google Scholar

37. Doss CG, Chakraborty C, Chen L, Zhu H. Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective. Biomed Res Int 2014;2014:895831.10.1155/2014/895831Search in Google Scholar

38. Amaro RE, Baron R, McCammon JA. An improved relaxed complex scheme for receptor flexibility in computer-aided drug design. J Comput Aided Mol Des 2008;22:693–705.10.1007/s10822-007-9159-2Search in Google Scholar PubMed PubMed Central

39. Durrant JD, Cao R, Gorfe AA, Zhu W, Li J, Sankovsky A, et al. Non-bisphosphonate inhibitors of isoprenoid biosynthesis identified via computer-aided drug design. Chem Biol Drug Des 2011;78:323–32.10.1111/j.1747-0285.2011.01164.xSearch in Google Scholar PubMed PubMed Central

40. Skovstrup S, David L, Taboureau O, Jørgensen FS. A steered molecular dynamics study of binding and translocation processes in the GABA transporter. PLoS One 2012;7:e39360.10.1371/journal.pone.0039360Search in Google Scholar PubMed PubMed Central

List of all partners in the INDICES consortiumSearch in Google Scholar

1. Henrik Berg Rasmussen, Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen University Hospital, Roskilde, Denmark.Search in Google Scholar

2. Majbritt Busk Madsen, Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen University Hospital, Roskilde, Denmark.Search in Google Scholar

3. Laura Ferrero, Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen University Hospital, Roskilde, Denmark.Search in Google Scholar

4. Kristian Linnet, Section of Forensic Chemistry, Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark.Search in Google Scholar

5. Ragnar Thomsen, Section of Forensic Chemistry, Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark.Search in Google Scholar

6. Gesche Jürgens, Department of Clinical Pharmacology, Bispebjerg University Hospital, Copenhagen, Denmark.Search in Google Scholar

7. Kim Dalhoff, Department of Clinical Pharmacology, Bispebjerg University Hospital, Copenhagen, Denmark.Search in Google Scholar

8. Claus Stage, Department of Clinical Pharmacology, Bispebjerg University Hospital, Copenhagen, Denmark.Search in Google Scholar

9. Hreinn Stefansson, CNS Division, deCODE Genetics, Reykjavik, Iceland.Search in Google Scholar

10. Thomas Hankemeier, The Leiden/Amsterdam Center for Drug Research LACDR, Leiden University, Gorlaeus Laboratories, Leiden, The Netherlands.Search in Google Scholar

11. Rima Kaddurah-Daouk, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.Search in Google Scholar

12. Søren Brunak, Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark.Search in Google Scholar

13. Olivier Taboureau, Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark.Search in Google Scholar

14. Grace Shema Nzabonimpa, Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark.Search in Google Scholar

15. Tine Houmann, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

16. Pia Jeppesen, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

17. Kristine Kaalund-Jørgensen, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

18. Peter Riis Hansen, Department of Cardiology, Copenhagen University Hospital, Hellerup, Denmark.Search in Google Scholar

19. Karl Emil Kristensen, Department of Cardiology, Copenhagen University Hospital, Hellerup, Denmark.Search in Google Scholar

20. Anne Katrine Pagsberg, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

21. Kerstin Plessen Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

22. Poul-Erik Hansen, Department of Science, Systems and Models, Roskilde University, Roskilde, Denmark.Search in Google Scholar

23. Thomas Werge, Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen University Hospital, Roskilde, Denmark.Search in Google Scholar

24. Jørgen Dyrborg, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar

25. Maj-Britt Lauritzen, Centre for Child and Adolescent Mental Health, Mental Health Services in the Capital Region of Denmark, Denmark.Search in Google Scholar


Supplemental Material

The online version of this article (DOI: 10.1515/dmpt-2015-0034) offers supplementary material, available to authorized users.


Received: 2015-9-15
Accepted: 2016-1-4
Published Online: 2016-2-19
Published in Print: 2016-6-1

©2016 by De Gruyter

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