Quantitative Structure-Activity Relationship of Flavonoid Antioxidants

碩士 === 淡江大學 === 化學學系碩士班 === 93 === Because of the large cost of people, materials, and money in the drug design process, a new investigation – Quantitative Structure-Activity Relationship ( QSAR ) , was used in this study. Recently, computer-aided drug design has emerged as a powerful technique in d...

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Bibliographic Details
Main Authors: Yeong-Sheng Chang, 張詠昇
Other Authors: 王伯昌
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/15526659025148038238
Description
Summary:碩士 === 淡江大學 === 化學學系碩士班 === 93 === Because of the large cost of people, materials, and money in the drug design process, a new investigation – Quantitative Structure-Activity Relationship ( QSAR ) , was used in this study. Recently, computer-aided drug design has emerged as a powerful technique in drug discovery process. Modern QSAR analysis developed using molecular structure descriptors and regression analysis techniques have found wide utility and acceptance. It was our aim to reduce the time of discovering process as well as help us to design better structures of flavonoids and more efficient antioxidants. A series of 118 flavonoid molecules were employed in all the calculations. All molecular structures were optimized at semi-empirical ( PM3 ) level. By use of structural , electronic energy, electrostatic energy, and bond energy as descriptors, the regression analysis was performed using. As the result, we suggested that the substituent position of the hydroxy group on the position 5 and 8 of the A ring could make an important role in the antioxidant property. Another key point might be the hydroxy group on the position 3 and 4 of the C ring. Besides, it had been shown good correlation between bond energy and antioxidant property. All the three energies ( electronic energy, electrostatic energy, and bond energy ) also affected the activity and helped us to construct the final QSAR model. It was clear from our QSAR analysis that all the descriptors involved encode very specific information about what factors affect the antioxidant properties of the flavonoids. Thus we could design more efficient antioxidants by using this model.