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  • 學位論文

以藥效基團、定量構效關係與虛擬篩選來設計新型非洲嗜睡症抑制劑

Discovery of novel kDNA inhibitors by Pharmacophore, QSAR modeling and virtual screening

指導教授 : 劉宣良
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摘要


非洲嗜睡症是由一種微小的原生動物-錐蟲所引起,寄生在動物的血液中;錐蟲會經體表進入人體血液,當發育到一定程度時會沿著人的循環系統侵入腦脊髓,使人發生昏睡而發病。然而現階段有關此類疾病的治療藥物非常少,即使是有效的藥物,開發至今也都已經超過40年,而且都具有強大的副作用。為了深入了解真正的藥效機制與研發新型不具副作用的藥物,我們使用了電腦輔助藥物設計元件中的藥效基團、比較力場分子分析、虛擬篩選、分子嵌合與分子動態模擬來進行本研究。首先,我們分別以44個與34個錐蟲體內粒線體之特殊DNA序列抑制劑分別架設藥效基團以及定量構效關係模型。在藥效基團的模型方面,我們以Hypogen法來架設模型並使用線性迴歸法以及Guner–Henry (GH) 評分方式進行驗證。結果顯示,藥效基團模型(Hypo1)有最高的線性迴歸係數(R=0.93),並有高的GH評分值(0.82),證明此模型具有良好的藥物活性預測能力,故我們以此模型進行了NCI化學資料庫的虛擬篩選,篩選出的化合物在藉由分子嵌合與分子動態模擬實驗評估其結合力強弱,最後,我們依據藥物對藥效基團的吻合度、化合物對目標DNA的氫鍵結合力強度與和分子動態模擬分析結果選出了一個能作為未來藥物開發上可能的前導藥物。在定量構效關係方面,我們使用了3D-QSAR generation模組進行模型建立並以線性迴歸法及交叉驗證法作為其驗證方式。實驗結果發現,第一組比較力場分子分析模型最具可靠的迴歸值(R2=0.95),而經由交叉驗證法所得到的值(q2 = 0.57)都証明了此模型有很高的可信度,故我們根據此比較力場分子分析模型所提供的結構資訊作為依據分別設計了8種化合物分子,並藉由分子嵌合與預測活性計算出這些化合物都具備高度的結合活性。在本研究中,我們成功的利用多種電腦輔助藥物設計元件進行了錐蟲體內粒線體之特殊DNA序列之藥物開發實驗,而實驗中搜尋與開發出的化合物分子期望在將來可以進一步的進行體外生物實驗來測試實際的藥物活性。

並列摘要


Human African trypanosomiasis (HAT) or sleeping sickness is caused by subspecies of the parasitic hemoflagellate Trypanosoma brucei. The chemotherapy of HAT currently centers on only small numbers of drugs, most of these were discovered more than forty years, and are plagued by various side effects. In quest of possible ways to understand the structural requirement for anti-trypanosomal mechanism and design novel compounds, the Hypogen 3D-QSAR pharmacophore analysis, CoMFA, virtual screening, docking and molecular dynamics can be powerful tools, which had the ability to design novel chemical entities with enhanced inhibitory potencies against Trypanosome brucei. The best pharmacophore model Hypo1 shows the highest correlation coefficient (R=0.93), and also shows a high goodness of GH score (0.82). After that, Hypo1 is used as a 3D query for virtual screening to discover potential inhibitors from NCI database. We then used CDocker and MD simulation program to analyze virtual hits. Finally, only one compound was remained which will be possible to view as a persuasive Trypanosomal inhibitor. In CoMFA studies, a good values of R2=0.95 from training set and promising predictive power from cross validation (q2=0.57) were obtained. Based on the model suggested steric and electrostatic interactions, we designed 8 novel compounds and analyzed their interaction and binding poses by CDocker consensus scoring function. Molecular modeling and CoMFA analysis were performed to obtain useful information about the structural requirements for the HAT inhibitors which could be utilized in its future design.

參考文獻


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