Quantum chemical approach to the mechanism on discrimination on odor molecules
Project/Area Number |
14580776
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Neuroscience in general
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Research Institution | Toho University |
Principal Investigator |
KISHI Kiyoshi Toho University, School of Medicine, Dept., Anat., Professor, 医学部, 教授 (00014118)
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Project Period (FY) |
2002 – 2004
|
Project Status |
Completed (Fiscal Year 2004)
|
Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2004: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2003: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2002: ¥2,400,000 (Direct Cost: ¥2,400,000)
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Keywords | odor molecules / raspberry odor / musk odor / electrophilic frontier density / computer aided chemistry / perfumers / discriminant function analysis / multiple regression analysis / 反応特性 / 量子化学 / 電子供与性フロンティア電子密度 / ニオイ強度 / ニオイの性質 / CAChe Work Program / 電子供与性フロシティア電子密度 / CAChe Work System / 統計的解析 |
Research Abstract |
This study was performed to characterize the response properties of odor molecules, which are indispensable for understanding the specificity of odor-receptor interactions underlying odor discrimination. First,28 raspberry related molecules including 8 raspberry odorous and 19 odorless molecules reported by Winter (1961) were analyzed. We used electrophilic frontier density(EFD) (Fukui et al.,1954) to evaluate the reactivity based on the localization of reactive electrons of these molecules. The EFD was computed for all of the atoms of each raspberry related molecules using Computer Aided Chemistry (CAChe, version 3.8,Oxford) program with chemical parameter of PM3. The relationship between reactivity of molecules, i.e., EFD values on appointed positions of the molecules, and raspberry odor intensities judged by perfumers was studied by discriminant function analysis and multiple regression analysis. The results are as follows : 1)Two reactive EFD on appointed position of molecules disc
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riminated 8 raspberry odorous and 19 odorless molecules with error discriminated probability of 0%. Bond distance ot two reactive EFD was 1.390±0.012Å (Mean±SEM). 2)The same EFD values correlated with levels of raspberry odor intensities judged by perfumers using multiple regression analysis (r<0.994,p<0.01). 3)We found bond distance between two reactive EFD of raspberry related molecules was significantly similar to that of 203 musk related molecules in our previous study (p<0.01). Therefore, we analyzed statistically whether these EFD values can effectively discriminate among three groups, group A of 8 raspberry odorous molecules, group B of 83 odorless molecules including 19 raspberry odorless and 64 musk odorless molecules, and group C of 139 musk odorous molecules. Two EFD values were able to discriminate all 8 raspberry odorous molecules, 79 out of 83 odorless molecules, and 122 out of 139 musk odorous molecules. Correct discrimination indicated 90.9% (p<0.01). In addition, we also analyzed several other odor molecules using the same method, and neural network that play important role for odor discrimination. Less
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Report
(4 results)
Research Products
(15 results)