- 學位論文
以石蒜鹼結構為架構去探討抑制表皮因子活性的藥物設計
Using the structure of lycorine as a framework to explore the drug design for inhibiting the activity of EGFR
摘要
經細胞實驗中發現石蒜鹼衍生物 (Lycorane)對HCT116、HT29、MDA231及MCF-7等癌細胞中IC50值都>100 µm，然而據文獻指出天然的石蒜鹼(lycorine)對MCF-7乳癌細胞的IC50為14.51 µm證明其具有作為乳癌細胞的標靶藥物潛力，為了促進人工合成的石蒜鹼及衍生物發展，探討抗乳腺癌活性不理想之原因，利用SwissTargetPrediction篩選出乳腺癌中的激素發現最有可能與天然石蒜鹼及石蒜鹼衍生物具有活性的蛋白質受體為EGRF並找尋文獻中用作模擬乳腺癌 EGFR 的 PDB ID: 1M17，為了更進一步的探討石蒜鹼及石蒜鹼衍生物對表皮因子EGRF的結合活性，使用的IGEMDOCK先評估石蒜鹼及石蒜鹼衍生物對表皮因子EGFR活性的評估，發現在IGEMDOOCK中石蒜鹼與石蒜鹼衍生物兩者皆具有活性，因此使用了四種網路分子對接預測程序，進行虛擬篩選找尋可能造成細胞實驗活性差異的原因，發現四種程序隨著基於不同腳本的分子對接引擎得到的結果也不相同，接著使用四種EGFR抑制劑標準品Gefitinib、Erlotinib、Afatinib、Lapatinib進行各個不同分子對接預測程序的精準度測試，以實際文獻中實驗結果作為標準，最終得到FastDRH使用MM/PB(GB)SA方法，藉由多種內建程序的結果進行分數統計作為藥理評分的依據，其與文獻中的對EGFR(1M17) 活性結果吻合: Genfitinib > Lapatinb >Afatinib > Erlotini，並且發現天然石蒜鹼在SwissDock、FastDrh中對EGRF受體具有較高的結合活性，而在CB-dock及DockThor中則是石蒜鹼衍生物具有較高的結合活性，值得探討的是CB-dock及FastDRH兩者皆基於AutoDock Vina引擎開發得到的Auto¬Dock score與及FastDRH中得到的類似於AutoDock score的分數DS兩者得分在石蒜鹼及石蒜鹼衍生物對比下皆為石蒜鹼衍生物具有更高的結合活性，而FastDrh基於MM/PB(GB)SA方法藉由多種內建程序的結果進行分數統計之藥理評分下時石蒜鹼的得分更高基於文獻到MM/PB(GB)SA是比Auto¬Dock更具有精確性的方法，因此我們將Fast¬Drh歸類為石蒜鹼得分更高的結論，而在CB-dock、FastDRH及IGEMDOCK預測對接姿勢時我們可以看到殘基的錨點大多落在700至800號附近，可以了解到石蒜鹼及石蒜鹼衍生物與EGFR蛋白質受體的活性位點在這個區域CB-dock的特殊空腔演算法可以為此推測作為例證，而在IGEMDOCK中可以觀察到在LYS721的部分皆為兩者胺基酸殘基接合的主要錨點，而在推測對接姿勢時發現其與二號位碳上的羥基有著密不可分的關係，可以看到在該位點的凡得瓦力及強氫鍵的結合能有增加，結合能整體增加了-6.2 kcal/mo，並且lycorane與lycorine的錨點分別為VAL702、LYS721、THR766、LEYU820，這些錨點可以分析出IGEMDOCK在分子對接姿勢預測時兩者間有相同的結合姿勢，在具有一、二號位碳的位置是其與EGRF蛋白質受體對接的重要點位，天然石蒜鹼在各殘基的結合能表現也比衍生物優異，為了改進石蒜鹼方向發展我們利用DeepFrag進行預測在石蒜鹼與 EGFR(1M17) 的配體改進方向，得到在碳3號位及8號位加入羥基、11號位加入烷基便能得到最佳化的分別為3號位加了羥基的石蒜鹼改進配體: T- Lycorine，碳3號及8號位加入羥基的石蒜鹼改進配體: TE- Lycorine，及碳3號及8號與11號位前兩號位加入羥基11號位加入烷基的石蒜鹼改進配體:TEE-Ly¬corine，最終僅有TEE-Lycorine擁有超過EGFR抑制劑標準品Erlotinib的預測結果，TEE-Lycorine在MM/PB(GB)SA方法的統計用得分制下得到了8分，而Erlotinib僅得到了7分，儘管與四個標準品中第三名的Afat¬inib有些許差距，但是改進後的TEE-Lycorine 仍然擁有超越市售標準EGFR藥品的潛力，因此後續藥物改進方向將以此方向進行藥物合成。
並列摘要
In cell experiments, it was found that the IC50 values of Lycorane, a deriva-tive of lycorine, for cancer cells such as HCT116, HT29, MDA231, and MCF-7 were all greater than 100 µm. However, according to literature, the natu¬ral compound lycorine demonstrated an IC50 value of 14.51 µm against MCF-7 breast cancer cells, confirming its potential as a targeted therapeutic agent for breast cancer cells. To advance the development of artificially synthesized lycorine and its deriva-tives, and to explore reasons for suboptimal anti-breast cancer activity, SwissTargetPrediction was utilized to screen for hormones in breast cancer. The protein receptor identified as most likely to exhibit activity with natural lycorine and its derivatives was EGFR (Epidermal Growth Factor Receptor). The PDB ID: 1M17 was selected for simulating breast cancer EGFR. In order to further investigate the binding activity of lycorine and its deriva-tives to the epidermal growth factor receptor (EGFR), IGEMDOCK was used for assessing their activity. Both lycorine and its derivatives showed activity in IGEMDOCK. Consequently, four different network molecular docking predic¬tion programs were employed to perform virtual screening, seeking poten¬tial causes for differences in cell experiment activity. It was noted that the results from these four programs varied depending on the molecular dock-ing engine and scripts used. Subsequently, four EGFR inhibitor standards, namely Gefitinib, Erlotinib, Afat¬inib, and Lapatinib, were used to conduct accuracy tests on various molecu¬lar docking prediction programs. Actual experimental results from litera¬ture were employed as benchmarks. Ultimately, the FastDRH method, using MM/PB(GB)SA methodology and incorporating results from multiple built-in procedures, was adopted for pharmacological scoring. The obtained scores aligned with literature-reported EGFR (1M17) activity results: Genfitinib > Lapatinib > Afatinib > Erlotinib. Additionally, it was observed that natural lycorine demonstrated higher binding activity to the EGFR recep-tor in SwissDock and FastDRH, whereas lycorine derivatives exhibited higher binding activity in CB-Dock and DockThor. Notably, both CB-dock and FastDRH were developed based on the AutoDock Vina engine, yielding AutoDock scores similar to the scores (DS) obtained from FastDRH. In comparison between lycorine and its derivatives, both CB-dock and FastDRH scores indicated higher binding activity for lycorine deriva¬tives. Furthermore, in the pharmacological scoring based on MM/PB(GB)SA methodology, FastDRH yielded higher scores for lycorine. As MM/PB(GB)SA is considered more precise than AutoDock, FastDRH was concluded to provide higher lycorine scores. During the prediction of docking poses in CB-dock, FastDRH, and IGEMDOCK, it was observed that the anchor residues were mostly located around positions 700 to 800. This indicated the active binding site of lycorine and its derivatives with the EGFR protein receptor in this region. CB-dock's specialized cavity algorithm supported this inference. In IGEMDOCK, it was noted that LYS721 residues were primarily anchoring points for amino acid residues from both lycorine and its derivatives. In the prediction of docking poses, a close relationship was observed between LYS721 and the hydroxyl group on the second carbon, leading to an increase in van der Waals forces and strong hydrogen bonding energy at that site, resulting in an overall energy increase of -6.2 kcal/mole. The anchor points for lycorane and lycorine were identified as VAL702, LYS721, THR766, and LEYU820. These anchor points suggested that IGEMDOCK's molecular docking pose prediction yielded similar binding orienta¬tions for both compounds. Positions on the first and second carbon were identified as crucial docking sites with the EGFR protein receptor. Moreo¬ver, natural lycorine exhibited superior binding energies across various residues compared to its derivatives. To enhance the development of lycorine, DeepFrag was employed to predict ligand improvement directions for lycorine and EGFR (1M17). It was found that introducing a hydroxyl group at the third and eighth carbon positions, as well as adding an alkyl group at the eleventh position, optimized the ligands. The resulting improved ligands were labeled as follows: T-Lycorine (hy-droxyl at the third position), TE-Lycorine (hydroxyl at the third and eighth positions), and TEE-Lycorine (hydroxyl at the third and eighth positions, and alkyl at the eleventh position). Ultimately, only TEE-Lycorine exhibited predic¬tive results surpassing the EGFR inhibitor standard Erlotinib. In MM/PB(GB)SA-based statistical scoring, TEE-Lycorine scored 8 points, whereas Erlotinib scored 7 points. Despite a slight difference compared to the third-ranked Afatinib among the four standard compounds, the enhanced TEE-Lycorine still demonstrated potential surpassing commercially available standard EGFR drugs. Consequently, future directions for drug improvement could focus on synthesizing compounds in line with these findings.