藉由一組有不同活性的化合物 (活性範圍1.2 nM ~ 6000 nM)，利用CATALYSY定量化合物結構與活性的關係，我們建立了一個藥效基團模型 (pharmacophore model)，此模型保留了微管蛋白抑制劑 (tubulin inhibitor) 最重要的化學性質（疏水性區域），並加入兩個氫鍵的特徵，對於預測化合物活性的能力，經由訓練組和測試組的驗證後，相關係數分別達到 0.96 和 0.89，我們並且利用cost analysis 和統計方法去證實這是個可信的模型後，之後使用此模型進行電腦虛擬藥物篩選 (virtual screening)。從十三萬筆的資料中，挑選前一千名分數最好的化合物，然後參考微管蛋白的結構，剔除有可能會與它發生碰撞化合物， 並考量化合物結構的多樣化，最後篩選出142個去作生物實驗，而結果當中有4個具有抑制細胞生長活性，其中化合43對多種癌症細胞都具有抑制生長的活性，尤其對MCF-7細胞株具有相當好的抑制效果，IC50 = 25 nM。進一步的實驗顯示，化合物43能有效的抑制微管蛋白的聚合，且能使細胞週期停留在G2-M 時期，也發現有許多細胞都進行了細胞凋零(apoptosis)，而與秋水仙素(colchicine) 的競爭性抑制實驗，發現化合物43於微管蛋白的結合位，可能並不是完全和秋水仙素一樣，這需要再進一步的研究。化合物43是現在由電腦輔助設計所篩選到最有活性的微管蛋白抑制劑，而化合物43全新的化學結構和抑制癌細胞的活性，將會是有潛力進行前導化合物最佳化的藥物(lead optimization)。

A pharmacophore model, Hypo1, was built based on 21 training-set indole compounds with varying levels of antiproliferative activity. Hypo1 possessed important chemical features required for the inhibitors and demonstrated good predictive ability for biological activity with high correlation coefficient of 0.96 and 0.89 for the training-set and test-set compounds, respectively. Further utilization of Hypo1 pharmacophore model to screen chemical database in silico led to the identification of four compounds with antiproliferative activity. Among these four compounds, 43 showed potent antiproliferative activity against various cancer cell lines with the strongest inhibition on the proliferation of MCF-7 cells (IC50 ＝ 25 nM). Further biological characterization revealed that 43 effectively inhibited tubulin polymerization and significantly induced cell cycle arrest in G2-M phase. To our knowledge, 43 is the most potent antiproliferative compound with antitubulin activity discovered by computer-aided drug design. The chemical novelty of 43 and its anticancer activities made this compound as an interesting hit worthy of further lead optimization.

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