Understanding the Protox Inhibition Activity of Novel 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene Derivatives Using Holographic Quantitative Structure-Activity Relationship (HQSAR) Methodology

홀로그램(H) QSAR 방법에 따른 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene 유도체들의 Protox 저해 활성에 관한 이해

  • Song, Jong-Hwan (Cytosine Laboratory, Korea Research Institute of Chemical Technology) ;
  • Park, Kyeng-Yong (Division of Applied Biologies and Chemistry, College of Agriculture and Life Science, Chungnam National University) ;
  • Sung, Nack-Do (Division of Applied Biologies and Chemistry, College of Agriculture and Life Science, Chungnam National University)
  • 송종환 (한국화학연구원 세포화학 연구팀) ;
  • 박경용 (충남대학교 농업생명과학대학 응용생물화학부) ;
  • 성낙도 (충남대학교 농업생명과학대학 응용생물화학부)
  • Published : 2004.09.30

Abstract

Holographic quantitative structure activity relationships (HQSAR) as 2D QSAR between the herbicidal activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli), and structures of A=3,4,5,6-tetra-hydrophthalimino, B = 3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C = 3,4-dimethylmaleimino substituents in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene derivatives were studied and discussed. The statistical results of four HQSAR models for the herbicidal activities against root and shoot of the two plants showed the best predictability of the herbicidal activities based on the cross-validated $r^2\;_{cv}\;(q^2=\;0.760{\sim}0.924)$, non cross-validated conventional coefficient $(r^2\;_{ncv}\;=\;0.868{\sim}0.970)$ and PRESS values $(0.123{\sim}0.261)$. The results indicated that the qualities of HQSAR models for barnyardgrass were slightly higher than that of rice plant. And also, the predictability of HQSAR models were higher $(q^2\;=\;HQSAR\;>\;CoMFA)$ than CoMFA but the conventional coefficients of HQSAR models lower $(r^2\;=\;HQSAR\;<\;CoMFA)$ than CoMFA. Moreover, from the contribution maps, it was founded that the selectivity between the two plants depends upon the 2-fluoro-4-chloro-5-alkoxyanilino and $R_3$ substituent on the C-phenyl ring. These features suggest where to modify a molecular structure in order to improve its selective of herbicidal activities against barnyardgrass.

HQSAR 방법으로 일련의 새로운 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene 유도체들중 A = 3,4,5,6-tetrahydrophthalimino, B = 3-chloro-4,5,6,7-tetrahydro-2H-indazolyl 및 C = 3,4-dimethylmaleimino 치환체들의 구조 변화에 따른 벼(Orysa sativa L.)와 논피(Echinochloa crus-galli) 뿌리와 줄기부위 사이의 살초활성 관계를 연구하였다. 두 가지 초종의 뿌리와 줄기의 살초활성에 대하여 유도된 4개의 HQSAR 모델들은 예측성, cross-validated $r^2\;_{cv.}$$(q^2\;=\;0.760{\sim}0.924)$, non-cross-validated 상관계수$(r^2\;_{cv.}\;=\;0.868{\sim}0.970)$ 및 PRESS 값$(0.123{\sim}0.261)$에 근거하여 매우 양호한 통계값들을 나타내었다. 유도된 HQSAR 모델들은 벼 보다는 논피에 대하여 양호한 경향을 나타내었으며 CoMFA 모델에 비하여 예측성은 좋았으나$(q^2\;=\;HQSAR\;>\;CoMFA)$ 저해활성과의 상관성은 약간 낮은$(r^2\;=\;HQSAR\;<\;CoMFA)$ 경향이었다. 또한, HQSAR 기여도로부터 논피에 대한 선택적인 살초활성은 2-fluoro-4-chloro-5-alkoxy anilino 및 C-phenyl 고리상 $R_3-$치환기에 의존적임을 알았다.

Keywords

References

  1. Duke, S. O. and Robeiz, C. A. (1994) In Porphyric pesticides, chemistry, toxicology, and pharmaceuticaal applications, Amercan Chemical Society Symposium Series, vol. 559. American Chemical Society. Washington, DC
  2. Tomlin, C. D. S. (1997) In The Oesticide Manual (Eleventh ed.), British Crop Protection Council, Surrey GU9 7PH, UK
  3. Hamper, B. C., Leschinsky, K. L., Massey, S. S., Bell, C. L., Brannigan, L. H. and Prosch, S. D. (1995) Synthesis and herbicidal activity of 3-aryl-5-(haloalkyl)-4-isoxazolecaIboxamides and thier derivatives. J. Agric. Food Chem. 43, 219-228 https://doi.org/10.1021/jf00049a040
  4. Fujita, T. (2002) In Agrochemical Discovery, Insect, Weed, and Fungal control: Similarities in bioanalogous structural transformation patterns, Baker, D. R. and Umetsu, N. K. (eds.) ACS Symposium Series No. 774., American Chemical Society, Washington, DC, Ch.15
  5. Pallett, K. E. (1997) In Herbicide target sites, recent trends and new challenges. Proceeding of Brighton Crop Protection Conference-Weeds, pp. 575-578
  6. Theodoridis, G. (1997) Structure activity relationships of herbicidal aryltriazolinones. Pestic. Sci. 50, 283-290 https://doi.org/10.1002/(SICI)1096-9063(199708)50:4<283::AID-PS600>3.0.CO;2-L
  7. Theodoridis, G., Bahr, 1. T., Hotzman, F. w., Sehgel, S. and Suarez, D. P. (2000) New geration of protox-inhibiting herbicides. Crop Prot. 19, 533-535 https://doi.org/10.1016/S0261-2194(00)00069-7
  8. Watanabe, N., Takayama, S., Yoshida, S., Isogai, A. and Che, F.S. (2002) Resistance to protoporphyrinogen oxidase-inhibiting compound S23142 from overproduction of mitochondrial protoporphyrinogen oxidase by gene amplification in photomixotrophic tabacco cells. Biosci. Biotechnol. Biochem. 66, 1799-1805 https://doi.org/10.1271/bbb.66.1799
  9. Dayan, F. E., Duke, S. 0., Reddy, K. N., Hamper, B. C. and Leschinsky, K. L. (1997) Effects of isozaole herbicides on protoporphyrinogen oxidase and porphyrin physiology. 1. Agric. Food Chem., 45, 967-975 https://doi.org/10.1021/jf9607019
  10. Sung, N. D., Song, J. H., Yang, S. Y. and Park, K. Y. (2004) Understanding the protox inhibition actlVlty of novel 1-(5methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene derivatives using CoMFA methodology. Kor. 1. Pest. Sci., 8, in press
  11. Sung, N. D., Ock, H. S., Song, J. H. and Lee Y. G. (2003) Comparative molecular field analysis (CoMFA) on the growth activity of N-phenyl-3,4,5,6-tetrahydrophthalimide and Nphenyl- 3,4-dimethylmaleimide derivatives. Kor. 1. Pest. Sci. 7, 75-82
  12. Sung, N. D., Ock, H. S., Chung, H. J. and Song, J. H. (2003) Quantitative structure activity relationship and molecular shape similarity of the herbicidal N-substituted phenyl-3,4dimethylmaleimide derivatives., Kor. 1. Pest. Sci., 7, 100-107
  13. Lowis, D. R (1997) HQSAR. A new, highly prediction QSAR technique. Tripos Technical Notes, vol. 1., No.5
  14. Tripos Associates, Inc., 1699 S. Hanley Road, Suite 303, St.Louis, MO. 63144-2913, USA, http://www.tripos.comlBookshelf/qsar/
  15. Flower, D. R (1998) On the properties of bit string-based measures of chemical similarity. Chern. Inf. Comput. Sci. 38, 379-386 https://doi.org/10.1021/ci970437z
  16. Turner, D. B., Tyrrell, S. M., Willett, P. (1997) Rapid quantification of molecular diversity for selective database acquisition. 1. Chem. Inf. Comput. Sci. 37, 18-22 https://doi.org/10.1021/ci960463h
  17. Heritage, T. W and Lowis, D. R (1999) In Rational drug design; Novel Methodology and Practical Applications: Molecular hologram QSAR. Ch. 4., Parrill, A. L. and Reddy,M. R (cds.) ACS Symposium Series 719, American Chemical Society. Washington, DC
  18. Tong, W D., Lowis, R, Perkins, R, Chen, Y., Welsh, W J., Goddette, D. W, Heritage, T. W and Sheehan, D. M. (1998) Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor. 1. Chern. Inf. Comput. Sci. 38, 669-677 https://doi.org/10.1021/ci980008g
  19. Stahle, L. and S. Wold (1988) Multivariate data analysis and experimental design in biomedical research. Prog. Med. Chern. 25, 292-334
  20. Wold, S., Albano, C., Dunn, W.J., Edlund, u., Esbensen, K, Geladi, P., Hellberg, S., Johanasson, E., Lindberg, W and Sjostrom, M. (1984) In Chemometrics: Mathematics and Statistics in Chemistry Multivariate Data Analysis in Chemistry, Kowalski, B. R (ed.), Reidel, Dordrecht, Nethelands. pp. 1794