Establishment of the experimental procedure for prediction of conjugation capacity in mutant UGT1A1


Autoři: Yutaka Takaoka aff001;  Atsuko Takeuchi aff002;  Aki Sugano aff001;  Kenji Miura aff001;  Mika Ohta aff001;  Takashi Suzuki aff001;  Daisuke Kobayashi aff003;  Takuji Kimura aff004;  Juichi Sato aff004;  Nobutaro Ban aff004;  Hisahide Nishio aff006;  Toshiyuki Sakaeda aff007
Působiště autorů: Division of Medical Informatics and Bioinformatics, Kobe University Hospital, Kobe, Japan aff001;  Division of Analytical Laboratory, Kobe Pharmaceutical University, Kobe, Japan aff002;  Division of Medical and Healthcare Systems, Healthcare Economics and Hospital Administration, Kobe University Graduate School of Medicine, Kobe, Japan aff003;  Department of General Medicine/Family and Community Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan aff004;  Medical Education Center, Aichi Medical University School of Medicine, Nagakute, Aichi, Japan aff005;  Department of Community Medicine and Social Healthcare Science, Kobe University Graduate School of Medicine, Kobe, Japan aff006;  Department of Pharmacokinetics, Kyoto Pharmaceutical University, Kyoto, Japan aff007
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225244

Souhrn

UDP-glucuronosyltransferase 1A1 (UGT1A1) is an enzyme that is found in the endoplasmic reticulum membrane and can reportedly have a large number of amino acid substitutions that result in the reduction of glucuronidation capacity. For example, adverse drug reactions when patients receive CPT-11 (irinotecan) such as in cancer chemotherapy are caused by amino acid substitutions in UGT1A1. We previously found that the extent of the docking when the hydroxyl residue of bilirubin was oriented toward UDP-glucuronic acid correlated with in vitro conjugation capacity. In this study, we analyzed the conformation of mutant UGT1A1s by means of structural optimization with water and lipid bilayers instead of the optimization in vacuo that we used in our previous study. We then derived a mathematical model that can predict the conjugation capacities of mutant UGT1A1s by using results of substrate docking in silico and results of in vitro analysis of glucuronidation of acetaminophen and 17β-estradiol by UGT1A1s. This experimental procedure showed that the in silico conjugation capacities of other mutant UGT1A1s with bilirubin or SN-38 were similar to reported in vitro conjugation capacities. Our results suggest that this experimental procedure described herein can correctly predict the conjugation capacities of mutant UGT1A1s and any substrate.

Klíčová slova:

Amino acid analysis – bilirubin – Drug metabolism – Enzyme metabolism – Mathematical models – Simulation and modeling – Substitution mutation – Coenzymes


Zdroje

1. Levesque E, Girard H, Journault K, Lepine J, Guillemette C. Regulation of the UGT1A1 bilirubin-conjugating pathway: role of a new splicing event at the UGT1A locus. Hepatology (Baltimore, Md). 2007;45(1):128–138. Epub 2006/12/26. doi: 10.1002/hep.21464 17187418

2. Kiang TK, Ensom MH, Chang TK. UDP-glucuronosyltransferases and clinical drug-drug interactions. Pharmacology & therapeutics. 2005;106(1):97–132. Epub 2005/03/23. doi: 10.1016/j.pharmthera.2004.10.013 15781124

3. UGT1A1 Substrates. [March 2, 2019]. Available from: https://www.drugbank.ca/categories/DBCAT003871.

4. Locuson CW, Tracy TS. Comparative modelling of the human UDP-glucuronosyltransferases: insights into structure and mechanism. Xenobiotica, the fate of foreign compounds in biological systems. 2007;37(2):155–168. Epub 2007/05/09. doi: 10.1080/00498250601129109 17484518

5. Takaoka Y, Ohta M, Takeuchi A, Miura K, Matsuo M, Sakaeda T, et al. Ligand orientation governs conjugation capacity of UDP-glucuronosyltransferase 1A1. Journal of biochemistry. 2010;148(1):25–28. Epub 2010/05/04. doi: 10.1093/jb/mvq048 20435641

6. Canu G, Minucci A, Zuppi C, Capoluongo E. Gilbert and Crigler Najjar syndromes: an update of the UDP-glucuronosyltransferase 1A1 (UGT1A1) gene mutation database. Blood cells, molecules & diseases. 2013;50(4):273–280. Epub 2013/02/14. doi: 10.1016/j.bcmd.2013.01.003 23403257

7. Ando Y, Saka H, Ando M, Sawa T, Muro K, Ueoka H, et al. Polymorphisms of UDP-glucuronosyltransferase gene and irinotecan toxicity: a pharmacogenetic analysis. Cancer research. 2000;60(24):6921–6926. Epub 2001/01/13. 11156391

8. Yamamoto K, Sato H, Fujiyama Y, Doida Y, Bamba T. Contribution of two missense mutations (G71R and Y486D) of the bilirubin UDP glycosyltransferase (UGT1A1) gene to phenotypes of Gilbert's syndrome and Crigler-Najjar syndrome type II. Biochimica et biophysica acta. 1998;1406(3):267–273. Epub 1998/06/19. doi: 10.1016/s0925-4439(98)00013-1 9630669

9. Bosma PJ, Chowdhury JR, Bakker C, Gantla S, de Boer A, Oostra BA, et al. The genetic basis of the reduced expression of bilirubin UDP-glucuronosyltransferase 1 in Gilbert's syndrome. The New England journal of medicine. 1995;333(18):1171–1175. Epub 1995/11/02. doi: 10.1056/NEJM199511023331802 7565971

10. Trdan Lusin T, Roskar R, Mrhar A. Evaluation of bisphenol A glucuronidation according to UGT1A1*28 polymorphism by a new LC-MS/MS assay. Toxicology. 2012;292(1):33–41. Epub 2011/12/14. doi: 10.1016/j.tox.2011.11.015 22154984

11. Iyer L, King CD, Whitington PF, Green MD, Roy SK, Tephly TR, et al. Genetic predisposition to the metabolism of irinotecan (CPT-11). Role of uridine diphosphate glucuronosyltransferase isoform 1A1 in the glucuronidation of its active metabolite (SN-38) in human liver microsomes. The journal of clinical investigation. 1998;101(4):847–854. Epub 1998/03/21. doi: 10.1172/JCI915 9466980

12. Hasegawa Y, Ando M, Shimokata K. Screening for adverse reactions to irinotecan treatment using the Invader UGT1A1 Molecular Assay. Expert review of molecular diagnostics. 2006;6(4):527–533. doi: 10.1586/14737159.6.4.527 16824027

13. Nagai H, Takaoka Y, Sugano A, Nakamachi Y, Kawano S, Nishigori C. Identification of a heterozygous p.Gly568Val missense mutation in the TRPV3 gene in a Japanese patient with Olmsted syndrome: in silico analysis of TRPV3. The journal of dermatology. 2017;44(9):1059–1062. Epub 2017/04/10. doi: 10.1111/1346-8138.13844 28391651

14. Nakamura Y, Sugano A, Ohta M, Takaoka Y. Docking analysis and the possibility of prediction efficacy for an anti-IL-13 biopharmaceutical treatment with tralokinumab and lebrikizumab for bronchial asthma. PloS one. 2017;12(11):e0188407. Epub 2017/11/21. doi: 10.1371/journal.pone.0188407 29155876

15. Ogasawara M, Nakamura Y, Morikawa N, Nitanai H, Moriguchi S, Chiba R, et al. Analysis of a single-codon E746 deletion in exon 19 of the epidermal growth factor receptor. Cancer chemotherapy and pharmacology. 2016;77(5):1019–1029. Epub 2016/04/05. doi: 10.1007/s00280-016-3021-y 27042857

16. Ohta M, Sugano A, Hatano N, Sato H, Shimada H, Niwa H, et al. Co-precipitation molecules hemopexin and transferrin may be key molecules for fibrillogenesis in TTR V30M amyloidogenesis. Transgenic research. 2018;27(1):15–23. Epub 2017/12/31. doi: 10.1007/s11248-017-0054-x 29288430

17. Sakaeda T, Kobuchi S, Yoshioka R, Haruna M, Takahata N, Ito Y, et al. Susceptibility to serious skin and subcutaneous tissue disorders and skin tissue distribution of sodium-dependent glucose co-transporter type 2 (SGLT2) inhibitors. International journal of medical sciences. 2018;15(9):937–943. Epub 2018/07/17. doi: 10.7150/ijms.22224 30008607

18. Sugawara K, Nomura K, Okada Y, Sugano A, Matsumoto M, Takarada T, et al. In silico and in vitro analyses of the pathological relevance of the R258H mutation of hepatocyte nuclear factor 4alpha identified in maturity-onset diabetes of the young type 1. Journal of diabetes investigation. 2019;10(3):680–684. Epub 2018/10/17. doi: 10.1111/jdi.12960 30325586

19. Nishimuta H, Sato K, Yabuki M, Komuro S. Prediction of the intestinal first-pass metabolism of CYP3A and UGT substrates in humans from in vitro data. Drug metabolism and pharmacokinetics 2011;26(6):592–601. Epub 2011/09/01. doi: 10.2133/dmpk.DMPK-11-RG-034 21878741

20. Tanaka Y, Kitamura Y, Maeda K, Sugiyama Y. Explication of definitional description and empirical use of fraction of orally administered drugs absorbed from the intestine (Fa) and intestinal availability (Fg): effect of P-glycoprotein and CYP3A on Fa and Fg. Journal of pharmaceutical sciences. 2016;105(2):431–442. doi: 10.1016/j.xphs.2015.11.005 26869410

21. Pieper U, Webb BM, Dong GQ, Schneidman-Duhovny D, Fan H, Kim SJ, et al. ModBase, a database of annotated comparative protein structure models and associated resources. Nucleic acids research. 2014;42(Database issue):D336–346. Epub 2013/11/26. doi: 10.1093/nar/gkt1144 24271400

22. Schrödinger LLC. The PyMOL Molecular Graphics System. 2.0 ed, 2017.

23. Castrignano T, De Meo PD, Cozzetto D, Talamo IG, Tramontano A. The PMDB Protein Model Database. Nucleic acids research. 2006;34(Database issue):D306–309. Epub 2005/12/31. doi: 10.1093/nar/gkj105 16381873

24. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. Journal of molecular graphics. 1996;14(1):33–38, 27–38. Epub 1996/02/01. doi: 10.1016/0263-7855(96)00018-5 8744570

25. Laakkonen L, Finel M. A molecular model of the human UDP-glucuronosyltransferase 1A1, its membrane orientation, and the interactions between different parts of the enzyme. Molecular pharmacology. 2010;77(6):931–939. Epub 2010/03/11. doi: 10.1124/mol.109.063289 20215562

26. Jorgensen W, Chandrasekhar J, Madura J, Impey R, Klein M. Comparison of simple potential functions for simulating liquid water. The journal of chemical physics. 1983;79:926–935. doi: 10.1063/1.445869

27. Ohtsubo H, Okada T, Nozu K, Takaoka Y, Shono A, Asanuma K, et al. Identification of mutations in FN1 leading to glomerulopathy with fibronectin deposits. Pediatric nephrology (Berlin, Germany). 2016;31(9):1459–1467. Epub 2016/04/09. doi: 10.1007/s00467-016-3368-7 27056061

28. Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, et al. Scalable molecular dynamics with NAMD. Journal of computational chemistry. 2005;26(16):1781–1802. Epub 2005/10/14. doi: 10.1002/jcc.20289 16222654

29. Berendsen HJC, Postma JPM, Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. The journal of chemical physics. 1984;81:3684–3690. doi: 10.1063/1.448118

30. Ryckaert JP, Ciccotti G, Berendsen HJC. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. Journal of computational physics. 1977;23(3):327–341. doi: 10.1016/0021-9991(77)90098-5

31. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. Journal of applied crystallography. 1993;26:283–291. doi: 10.1107/S0021889892009944

32. Soni S, Tyagi C, Grover A, Goswami SK. Molecular modeling and molecular dynamics simulations based structural analysis of the SG2NA protein variants. BMC research Notes. 2014;7:446. Epub 2014/07/13. doi: 10.1186/1756-0500-7-446 25015106

33. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. Journal of computational chemistry. 2009;30(16):2785–2791. Epub 2009/04/29. doi: 10.1002/jcc.21256 19399780

34. Jeffrey GA. An introduction to hydrogen bonding. New York: Oxford University Press; 1997.

35. Wada K, Takeuchi A, Saiki K, Sutomo R, Van Rostenberghe H, Yusoff NM, et al. Evaluation of mutation effects on UGT1A1 activity toward 17β-estradiol using liquid chromatography-tandem mass spectrometry. Journal of chromatography B, Analytical technologies in the biomedical and life sciences. 2006;838(1):9–14. Epub 2006/03/01. doi: 10.1016/j.jchromb.2006.01.030 16504606

36. Tripathi SP, Bhadauriya A, Patil A, Sangamwar AT. Substrate selectivity of human intestinal UDP-glucuronosyltransferases (UGTs): in silico and in vitro insights. Drug metabolism reviews. 2013;45(2):231–252. Epub 2013/03/07. doi: 10.3109/03602532.2013.767345 23461702

37. Vogelauer M, Krall AS, McBrian MA, Li JY, Kurdistani SK. Stimulation of histone deacetylase activity by metabolites of intermediary metabolism. The journal of biological chemistry. 2012;287(38):32006–32016. Epub 2012/07/24. doi: 10.1074/jbc.M112.362467 22822071

38. Ciotti M, Chen F, Rubaltelli FF, Owens IS. Coding defect and a TATA box mutation at the bilirubin UDP-glucuronosyltransferase gene cause Crigler-Najjar type I disease. Biochimica et biophysica acta. 1998;1407(1):40–50. Epub 1998/06/26. doi: 10.1016/s0925-4439(98)00030-1 9639672

39. Gagne JF, Montminy V, Belanger P, Journault K, Gaucher G, Guillemette C. Common human UGT1A polymorphisms and the altered metabolism of irinotecan active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38). Molecular pharmacology. 2002;62(3):608–617. Epub 2002/08/16. doi: 10.1124/mol.62.3.608 12181437

40. Kaniwa N, Kurose K, Jinno H, Tanaka-Kagawa T, Saito Y, Saeki M, et al. Racial variability in haplotype frequencies of UGT1A1 and glucuronidation activity of a novel single nucleotide polymorphism 686C> T (P229L) found in an African-American. Drug metabolism and disposition: the biological fate of chemicals. 2005;33(3):458–465. Epub 2004/12/02. doi: 10.1124/dmd.104.001800 15572581

41. Udomuksorn W, Elliot DJ, Lewis BC, Mackenzie PI, Yoovathaworn K, Miners JO. Influence of mutations associated with Gilbert and Crigler-Najjar type II syndromes on the glucuronidation kinetics of bilirubin and other UDP-glucuronosyltransferase 1A substrates. Pharmacogenetics and genomics. 2007;17(12):1017–1029. Epub 2007/11/16. doi: 10.1097/FPC.0b013e328256b1b6 18004206

42. Meyer UA. Pharmacogenetics and adverse drug reactions. Lancet (London, England). 2000;356(9242):1667–1671. Epub 2000/11/23. doi: 10.1016/S0140-6736(00)03167-6 11089838

43. Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: somatic cancer genetics at high-resolution. Nucleic acids research. 2017;45(D1):D777–D783. Epub 2016/12/03. doi: 10.1093/nar/gkw1121 27899578

44. Evans WE, McLeod HL. Pharmacogenomics—drug disposition, drug targets, and side effects. The New England journal of medicine. 2003;348(6):538–549. Epub 2003/02/07. doi: 10.1056/NEJMra020526 12571262


Článek vyšel v časopise

PLOS One


2019 Číslo 11