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研究生:黃怡誠
研究生(外文):Yi-Cheng Huang
論文名稱:開發以結構及細胞為基礎之魚類神經壞死症病毒抑制劑
論文名稱(外文):Development of Anti-Nervous Necrosis Virus Agents with Structure- and Cell-based Assays
指導教授:韓玉山韓玉山引用關係
指導教授(外文):Yu-San Han
口試委員:廖一久彭正周信佑呂明偉李宗徽
口試日期:2015-07-13
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:漁業科學研究所
學門:農業科學學門
學類:漁業學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:131
中文關鍵詞:魚類結病毒魚類神經壞死症病毒藥物篩選RNA聚合酶同源模擬石斑魚
外文關鍵詞:betanodavirusnervous necrosis virusdrug screeningRNA-dependent RNA polymerasehomology modelingGrouper
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魚類神經壞死症病毒 (Nervous necrosis virus, NNV) 是一具有高度傳染性之病原體,在水產養殖產業中造成嚴重的損失。直到目前為止,仍無任何商品化之抗病毒藥物可用來防治魚苗早期發育階段因該病毒感染而產生之大量死亡現象。因此,為了加速抗NNV藥物之開發,建立藥物開發所需之工具顯得十分重要。本研究中,我們建立了以細胞存活率為基礎之藥物篩選平台,並針對NNV之RNA聚合酶 (RdRp) 進行以蛋白質結構為基礎之模擬分析。本研究首先進行藥物篩選試驗條件之最佳化,並進行篩選結果之強韌性確認,其中代表藥物篩選結果穩定性之Z’ factor值分布於0.70至0.94間。利用此篩選平台篩選2,000種小分子化合物之後,共有43種化合物之病毒抑制能力≥55%。其中,proadifen hydrochloride 屬於細胞色素 (cytochrome) P450抑制劑,其EC50及CC50分別為6.48μM及20.63μM,並在石斑魚鰭細胞株 (GF-1) 感染病毒五天後降低病毒RNA量達99.68%。除此之外,我們更發現這43種化合物中共有18種化合物屬於神經傳導物質藥劑 (neurotransmitter agents)。在病毒RdRp結構分析中,其蛋白質結構藉由SWISS-MODEL server進行同源模擬而建立。將該結構與口蹄疫病毒RdRp 蛋白質結晶結構(與ribavirin triphosphate結合) 進行結構比對的結果顯示其配體結合位置之結構具有高度保留性。由於ribavirin在過去被發現可以抑制多種病毒之RdRp,因此,本研究利用濃度相依實驗以及病毒RNA量測來確認ribavirin在GF-1細胞中抑制病毒之活性。實驗結果顯示ribavirin在濃度25 μM可抑制病毒引發之細胞病變效應(cytopathic effect) 達54.41%。同時病毒RdRp以及蛋白質外殼之RNA量在細胞感染病毒後48小時皆有顯著之下降,本結果顯示ribavirin可能藉由與NNV RdRp間之作用抑制病毒在GF-1細胞中之感染。總結本研究,以結構及細胞為基礎之魚類神經壞死症病毒抑制劑開發之工具已成功建立,本研究亦發現數種抗魚類神經壞死症病毒之抑制劑。本研究結果除了提供魚類神經壞死症病毒防治之候選藥物,亦可用以探討該病毒與宿主間之交互作用。

Nervous necrosis virus (NNV) is a highly contagious pathogen, responsible for severe losses incurred in the aquaculture industry. Currently, no commercially available antivirals against the virulence observed during very early stages of fish larvae development. Therefore, to facilitate the discovery of antivirals against NNV, establishing tools for discovering anti-NNV agents is important. In this study, we developed a novel cell viability-based screening assay as well as a structure-based survey of viral RNA-dependent RNA polymerase (RdRp). The cell viability-based screening assay conditions were optimized and the robustness of the assay was confirmed by a Z’ factor value ranging from 0.7 to 0.94. After screening a library of 2,000 small molecule compounds, 43 compounds with a virus inhibition capacity of ≥55% were identified. A cytochrome P450 inhibitor, proadifen hydrochloride, was validated with an EC50 value of 6.48 μM and a CC50 value of 20.63 μM. This compound reduced viral RNA level by 99.68% in grouper fin-1 cells (GF-1) at 5 days post-infection. Surprisingly, we found that 18 of 43 compounds act as neurotransmitter agents. For structure-based survey of NNV RdRp, the three-dimensional structure of NNV RdRp was modeled using the SWISS-MODEL server. Structure-based alignment of the modeled NNV RdRp and foot-and-mouth disease virus RdRp crystal structure (in complex with ribavirin triphosphate) indicated that the conformation of the ligand-binding pockets were highly conserved. Since ribavirin was shown to inhibit the RdRp from various viruses, it was thus tested for its ability to inhibit NNV infection by a dose-dependent assay and viral RNA determination in GF-1 cells. Ribavirin inhibited the virus-induced CPE by 54.41% at a concentration of 25 μM, and the viral RNA levels of both RdRp and capsid protein decreased significantly at 48 hours post-infection. These results indicate that ribavirin may interact with the RdRp of NNV to inhibit viral infection in GF-1 cells. In summary, novel tools for discovering anti-NNV agents with structure and cell-based assays have been established. The inhibitors of NNV were also revealed. These results may not only be used as antiviral therapies, but also help us to further understand the interactions between viruses and host cells.

誌謝 i
中文摘要 ii
Abstract iv
Table of Contents vi
List of Figures ix
List of Tables x
Abbreviations xi
Chapter 1. Introduction 1
1.1 The outbreaks of viral nervous necrosis 1
1.2 Molecular biology of betanodavirus 1
1.3 The epidemiology of betanodavirus 2
1.4 Control measures for VNN 3
1.5 Antiviral agents 4
1.6 The nodaviral RdRp 5
1.7 Ribavirin: an RdRp inhibitor 6
1.8 A structure-based investigation for betanodaviral RdRp 7
1.9 The object of this study 8
Chapter 2. Materials and methods 9
2.1 Cells, viruses, and compounds 9
2.2 Cell preparation 9
2.3 Antiviral screen 9
2.3.1 Optimization of DMSO concentration 9
2.3.2 Optimization of infection dosage and time 10
2.3.3 Screening procedure 10
2.4 MTT cell viability assay 11
2.5 Hits validation 11
2.5.1 Dose-dependent assay 11
2.5.2 RNA extraction, reverse-transcription, and real-time PCR 12
2.6 Homology modeling 13
2.7 RT-qPCR validation for anti-RGNNV activity of ribavirin 14
Chapter 3. Results 16
3.1 Optimization of the cell-based screen 16
3.2 Antiviral screen 16
3.3 Hits validation 17
3.3.1 Dose-dependent assay 17
3.3.2 RT-qPCR confirmation of viral RNA amplification 17
3.4 Homology modeling of RGNNV RdRp 18
3.5 Protein sequence and structure alignment 18
3.6 Dose-dependent assay of ribavirin 20
3.7 RT-qPCR validation for anti-RGNNV activity of ribavirin 20
Chapter 4. Discussion 22
4.1 The anti-RGNNV screening 22
4.2 The bioactivity of hit compounds 22
4.3 The neurotransmitter agents 23
4.4 Proadifen: a non-specific cytochrome P450 inhibitor 24
4.5 Summary of the cell viability-based assay 25
4.6 The homology modeling of RGNNV RdRp 25
4.7 The anti-RGNNV efficacy of ribavirin 26
4.8 Summary of the structure-based investigation of RGNNV RdRp 27
Chapter 5. Conclusion 28
References 29
Figures 38
Tables 48
Appendixes 51
Screen results 51
SWISS-MODEL homology modeling report 109
Publications 118
Journal papers 118
Conference papers 118

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