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    题名: 電腦輔助藥物設計 : 抗癌藥物之結構優化與虛擬接合
    其它题名: Computer-assisted drug design : geometry optimization and virtual docking of anti-cancer agents
    作者: 張詠昇;Chang, Yeong-sheng
    贡献者: 淡江大學化學學系博士班
    王伯昌;Wang, Bo-cheng
    关键词: 定量構效關係;藥效團分析;分子對接模擬;酪胺酸激酶抑制劑;Quantitative structure–activity relationship;pharmacophore model;Docking;quinazoline
    日期: 2010
    上传时间: 2010-09-23 16:12:21 (UTC+8)
    摘要: 電腦模擬技術與藥物化學學科的結合,產生了電腦輔助藥物設計的新學門,其主要目的在於縮短藥物研發時間,最終目標則在於解決人類的疾病問題。定量構效分析屬於為其中受到研究者青睞的設計方法之一。
    本研究由藥物設計的策略與方向進行說明,並將電腦輔助藥物設計依據其不同的理論基礎分為兩種,一為間接藥物設計方法,另一為直接藥物設計方法;文中內容將不同的軟體所提供的訊息與結果作一說明,由藥效團分析及分子對接模擬,進以闡釋藥物分子與藥物作用標靶的結合情形。
    論文的研究與討論則以兩種抗癌藥物的設計,第一部分針對類黃酮分子之於人類結腸直腸癌之細胞株(HT-29)的抑制能力,以間接藥物設計方法(CoMFA)進行深入的計算與嘗試提出三維構效方程式;第二部份則對於酪胺酸激酶的抑制劑(quinazoline type)進行計算模擬,透過直接藥物設計與間接藥物設計方法的結合,模擬藥物分子實際之結合情形,並於最後提出活性更佳的潛力藥物分子。
    Quantitative structure–activity relationship (QSAR) methods, particularly three dimensional QSAR, have been demonstrated as an effective tool in discovering novel lead compounds. And pharmacophore modeling method is one of the best 3D-QSAR methods, which has been successfully applied to the drug discovery.
    In an effort to establish a pharmacophore model for the inhibition of Tyrosine Kinase that could serve as a guide for the rational design of further potent and selective inhibitors. We have developed a quantitatively predictive chemical function-based pharmacophore model by using the HypoGen algorithm implemented in the Discovery Studio 2.1 software. The most optimal hypothesis consists of four features: three hydrophobic (HYD), and one hydrogen bond donor (HBD) function. To further validate our design rationale, protein-ligand docking software was used to elucidated the intra-molecular interaction.
    By comparing molecular surfaces with POX1 and quinazoline type inhibitors, the ligand position relative to the adjacent residues was further constructed. Therefore, the built pharmacophore model could help us to better understand how the substituents influence the activity and afford important information for both ligand-based and structure-based drug design.
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