PKA為一種蛋白質激酶，有多種功能包括糖原調節、糖類與脂類的代謝；也與許多疾病諸如肺癌、結直腸癌等有關。在本研究中，我們利用分子嵌合計算來研究PKA的抑制劑。
首先，我們對20個蛋白質資料庫的PKA抑制劑複合物進行分子嵌合計算，研究其再現性。結果發現，計算評分值與實驗IC50值具有良好的相關性。第二，我們選擇5個PKA抑制劑複合物做交叉分子嵌合，研究當PKA來自不同的結晶構型時，如何再現小分子的構型。第三，使用相同5個PKA結晶構型進行虛擬篩選，計算10個具有抑制力小分子可從資料庫下載的1000個化合物中篩選出多少個。在這些模擬計算中，我們分析/討論當我們允許可動蛋白質活性中心附近的數個胺基酸支鏈時，其對結果的影響。我們發現，當設定可動4個胺基酸支鏈時，其結果較佳。最後，我們根據以上較佳的條件選擇及設定，高速虛擬篩選24535個化合物，並討論數個具有較佳親和力化合物與PKA之間的作用及其結合模型，這些計算結果將有助於實驗學家設計與搜尋PKA抑制劑。

Protein kinase A (PKA) is a kinase protein that has several functions in cell, including regulation of glycogen, sugar, and lipid metabolism. It also plays significant role in a number of biochemical reaction networks associated with diseases, including lung cancer and colorectal cancers. In the present study, we used docking computation to aid in design and discovery of PKA inhibitors. First, we carried out docking computations for 20 PKA-inhibitor complexes from protein data bank to examine their reproducibility. The results showed that the computed fitnesses values of ligands are in good accord with the experimental IC50 values. Second, crossing docking of selected 5 complexes was carried out to investigate if and how ligand conformations can be regained when a protein structure from different complexes were used. In addition, thirdly, the protein structures from these 5 complexes were used to undergo a virtual screening to see if 10 active compounds can be screened out of 1000 compounds selected from a database. In these computations, the several side chains at active site were allowed to move to examine how this effect affects the docking results. The results showed that better results were obtained in the case of allowing 4 residues to move. Finally, a virtual screening for 24535 compounds was carried out. The interactions between top-ranked compounds and PKA were analyzed and discussed. These computed results and analysis should be of aid in design and discovery of PKA inhibitors.

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