| Summary: | 博士 === 國立臺灣大學 === 農業化學系 === 85 === Physical and chemical properties of chemical compounds as well
as their bioactivities alter due to the changes in their
chemical structures. Therefore, the quantitative structure
parameters can be used to describe the physical and chemical
properties of different compounds and their bioactivities.In the
present study, hydrogen bond acidity index (HAI), hydrogen bond
basicity index (HBI), molecular weight (MW) and molecular
connectivity indices are selected as quantitative structure
parameters. The capacity factors (k'') of 19 carbamate
pesticides are determined on the reversed-phase column with
mobile phases of methanol/water or acetonitrile/water in various
ratios. By the use of multiple regression analysis, the ln k''
values are screened against the quantitative structure
parameters for all possible two-, three- and four-variable
combinations. With different mobile phase systems, the best
relationships are obtained to the 4-variable, the multiple
correlation coefficients are between 0.898-0.934. The
independent variable HBI in all regression equations means that
HBI is an effective parameter in retention of carbamate
pesticides in reversed-phase high-performance liquid
chromatographic(RP-HPLC).The inhibition of acetylcholinesterase
by carbamate pesticides can be explained with affinity constant
(Ka) and carbamylation constant (kc), in the other word, in
explanation of inhibition constant (Ki). The natural logarithm
value of these three constants can be described by the
quantitative structure parameters. The best relationships are
obtained to the 4-variable, the multiple correlation
coefficients are between 0.911-0.946. Through the further
study, (1／0XN)2 and (R1 3XcV) are effective parameters to
explain the inhibition of carbamate pesticides on
acetylcholinesterase. The natural logarithm values of median
lethal concentration (LC50) of carbamate pesticides to Daphnia
pulex can also be described by the quantitative structure
parameters, the best relationship is obtained to the 4-variable,
the multiple correlation coefficient is 0.888.The above
mentioned regression equations are tested by random effect and
F-test. The regression coefficients are also tested by t-test.
All of the statistic results are significant. The values of
these quantitative structure parameters are sure to reveal
certain relationship among ln k'', ln Ka, ln Ki, ln kc and ln
(LC50).
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