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  • 學位論文

利用電腦輔助藥物設計開發新穎的神經異常症藥物:以阿茲海默症、運甲腺素蛋白類澱粉沉積症與憂鬱症為例

Computer-aided drug discovery of novel drugs for neuropsychiatric disorders: Alzheimer’s disease, transthyretin amyloidosis and depression

指導教授 : 劉宣良

摘要


神經異常症為大腦內的神經細胞漸進性的喪失或神經傳導物質不足,導致多種精神病症狀的產生。常見的神經異常症包含了阿茲海默症、運甲腺素蛋白類澱粉沉積症與憂鬱症。為了開發新型的阿茲海默症、運甲腺素蛋白類澱粉沉積症與憂鬱症藥物,本研究將結合多種電腦輔助藥物設計元件並設計出一個有效的篩選方法自化學分子資料庫中篩選出新穎的前導化合物。針對各個疾病,我們分別依據各個目標蛋白與抑制劑的複合體結構來建立以結構為基礎的藥效基團模型,此模型描述抑制劑結合在目標蛋白中所必須的重要官能基特徵。各個驗證後的藥效基團模型將套用至虛擬篩選,並自化學分子資料庫中篩選出對目標蛋白具抑制活性的化合物。所篩選出來的化合物與目標蛋白的結合親和力與穩定度將分別利用分子嵌合與分子動態模擬進行評估。根據本實驗的篩選結果,各個目標蛋白都篩選出比參考抑制劑具有更好結合親和力與穩定度的化合物。因此,本研究所篩選出的化合物將可作為開發新穎的神經異常症藥物的新型骨幹結構。

並列摘要


Neuropsychiatric disorders are characterized by progressive loss of neuronal cells or lack of neurotransmitters in the brain, resulting in various psychotic symptoms. The common neuropsychiatric disorders include Alzheimer’s disease (AD), transthyretin (TTR) amyloidosis and depression. To discover new drugs against AD, TTR amyloidosis and depression, a useful guide combining several computer-aided drug design (CADD) approaches was designed in this study to identify novel lead compounds from chemical databases. For each disease, a structure-based pharmacophore model (SBPM) that describes the critical features necessary for the inhibitor binding to the target protein was generated from each target protein-inhibitor complex. Each well-validated SBPM was then applied in virtual screening to identify potential compounds with inhibitory activity toward the target protein from chemical databases. The binding affinity and stability between the target protein and the selected compounds were evaluated using molecular docking and molecular dynamics (MD) simulations, respectively. Based on our search method, serveral potenial hits that exhibited higher binding affinity and stability in comparison to the reference inhibitor were finally identified for each target protein. Thus, the obtaine hits could be used as new scaffold in the development of novel neuropsychiatric disorders drugs.

參考文獻


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