3D-QSAR Analyses on the Inhibition Activity of 4-($R_1$)-Benzyl Alcohol and 4-($R_2$)-Phenol Analogues Against Tyrosinase

4-($R_1$)-Benzyl alcohol 및 4-($R_2$)-Phenol 유도체들의 Tyrosinase 활성 저해에 대한 3D-QSAR 분석

  • Kim, Sang-Jin (Department of Cosmetic Science, Daejeon Health Sciences College) ;
  • Lee, Myoung-Hee (Department of Cosmetic Science, Daejeon Health Sciences College)
  • 김상진 (대전보건대학 화장품과학과) ;
  • 이명희 (대전보건대학 화장품과학과)
  • Published : 2009.12.30

Abstract

The 3-dimensional quantitative structure-activity relationships (3D-QSARs) models between the substituents with changing groups ($R_1$ & $R_2$) of 4-($R_1$)-benzyl alcohol and 4-($R_2$)-phenol derivatives as substrate molecule and their inhibitory activities against tyrosinase were derived and discussed quantitatively. The optimized CoMSIA 2 model have best predictability and fitness ($r^2\;=\;0.858$ & $q^2\;=\;0.951$). The contour maps of optimized CoMSIA 2 model showed that, the inhibitory activities of the analogues against tyrosinase were expected to increase when hydrophobic favor, negative charge favor, steric disfavor and hydrogen bond donor disfavor groups were substituted at the $R^2$ position. When the positive charge and the hydrogen bond donor favor groups were substituted at the $R_1$ position, it is predicted that the substituents will be able to increase the inhibitory activity. However, hydrogen bond acceptor did not affect inhibitory activities of tyrosinase.

기질 화합물로써 일련의 4-($R_1$)-benzyl alcohol 및 4-($R_2$)-phenol 유도체들의 치환기($R_1$$R_2$)가 변화함에 따른 tyrosinase 활성저해에 관한 3차원적인 구조-활성 상관 (3D-QSARs) 모델을 유도하고 정량적으로 검토하였다. 그 결과, 입체장, 정전기장, 소수성장 및 수소결합 주게장의 조합조건에서 통계적으로 양호한 CoMSIA 2 모델(상관성; $r^2\;=\;0.858$ 및 예측성; $q^2\;=\;0.951$)을 유도하였다. 등고도 분석결과, 기질분자의 $R_2$-치환기는 입체적으로 작고 음전하를 띄며, 소수성이면서 수소결합 주게장을 선호하지 않는 치환기가, 그리고 $R_1$-치환기는 양전하를 띄며 수소결합 주게장을 선호하는 치환기가 tyrosinase의 저해활성이 증가 될 것으로 예상되었으며, 수소결합 받게장은 전혀 영향을 미치지 않았다.

Keywords

References

  1. V. Marmol and F. Beermann, Tyrosinase and related protein in mammalian pigmentation. FEBS Letters, 381, 165 (1996) https://doi.org/10.1016/0014-5793(96)00109-3
  2. J. Cabanes, S. Chazarra, and F. Garcia-Carmona, Kojic acid, a cosmetic skin whitening agent, is a slow-binding inhibitor of catecholase activity of tyrosinase. J. Pharm. Pharmacol., 46, 982 (1994) https://doi.org/10.1111/j.2042-7158.1994.tb03253.x
  3. G. Battaini, E. Monzani, L. Casella, L. Santagostini, and R. Pagliarin. Inhibition of the catecholase activity of biomimetic dinuclear copper complexes by kojic acid. J. Biol. Inorg. Chem., 5, 262 (2000) https://doi.org/10.1007/s007750050370
  4. K. Maeda and M. Fukuda, Arbutin: mechanism of its depigmenting action in human melanocyte culture. J. Pharmacol. Exp. Ther., 276, 765 (1996)
  5. H. Z. Hill, W. Li, P. Xin, and D. L. Mitchell, Melanin: A two edged sword? Pigment Cell Res., 10, 158 (1997) https://doi.org/10.1111/j.1600-0749.1997.tb00478.x
  6. M. Seiberg, Kerationcyte-melanocyte interaction during melanosome transfer. Piment Cell Res., 14, 236 (2001) https://doi.org/10.1034/j.1600-0749.2001.140402.x
  7. N. D. Sung, H. S. Jung, and S. J. Kim, Hydrolytic Reactivity and Holographic Quantitative Structure-Activity Relationship Analysis on the Melanogenesis Inhibitory Activities of Alkyl-3,4-dihydroxybenzoate and N-Alkyl-3,4-ihydroxybenzamide Derivatives, J. Soc. Cosmet. Scientists Korea, 30, 4 (2004)
  8. N. W. Boaz and S. K. Clendennen, A Green, Solvent-free Biocatalytic Method to Produce Cosmetic Esters. Cosmetics & Toiletries, 124, 7 (2009)
  9. Tripos Sybyl, Molecular modeling and QSAR software on CD-Rom (Ver. 8.0), Tripos Associates, Inc. (2001)
  10. W. P. Purcell and J. A. Singer, A brief review and table of semiempirical parameters used in the Huckel molecular orbital method, J. Chem. Eng. Data., 122, 235 (1967) https://doi.org/10.1021/je60033a020
  11. G. R. Marshall, C. D. Barry, H. E. Bosshard, R. A. Dammkoehler, and D. A. Dunn, In computer- assisted drug design: The conformational parameter in drug design; active analog approach, Am. Chem. Soc., 205 (1979)
  12. M. Clark, R. D. Cramer III, D. M. Jones, D. E. Patterson, and P. E. Simeroth, Comparative molecular field analysis (CoMFA). Toward its use with 3D-structural databases. Tetrahedron Comput. Methodol., 3, 47 (1990) https://doi.org/10.1016/0898-5529(90)90120-W
  13. G. E. Kellogg, S. F. Semus, and D. J. Abraham, HINT: A new method of empirical hydophobic field calculation for CoMFA. J. Comput.-Aided Mol. Des., 5, 545 (1991) https://doi.org/10.1007/BF00135313
  14. R. D. Cramer, J. D. Bunce, and D. E. Patterson, Cross validation, Bootstrapping, and partial least squares compared with multiple regression in conventional QSAR studies. Quant. Struct. Act. Relat., 7, 18 (1988) https://doi.org/10.1002/qsar.19880070105
  15. D. C. Robert and C. F. Peter, Statistical variation in progressive scrambling. J. Comp.-Aided Mol. Des., 18, 563 (2004) https://doi.org/10.1007/s10822-004-4077-z
  16. G. Schneider and K. H. Baringhaus. Molecular Design; Concepts and Application. WILEY-VCH. Weinheim, 64 (2008)