利用線上藥物資料庫與氨基酸變異預測藥物不良反應相關之非同義單核苷酸多態性

藥物不良反應是個造成上百萬死亡的嚴重問題，根據研究指出，藥物不良反應是在藥物相關產業上市後藥物造成死亡最主要的原因之一。在美國，它是每年造成十萬人死亡的第四大死因；根據研究(1, 2, 3)指出，非同義單核苷酸多態性有最高的可能性影響一個人是否會對某特定藥物有不良反應。在此篇論文當中，我們設計了一個結合了SIDER, DART以及dbSNP三個資料庫以及運用到SIFT去預測是否有氨基酸變異的流程。我們運用此流程去預測藥物是否有氨基酸變異，並且找出與某特定藥物不良反應最有可能相關的非同義單核苷酸多態性，找出那些與某特定藥物不良反應最有可能相關的非同義單核苷酸多態性候選人是我們的目的，生物學家可以利用此篇論文的方法縮小研究範圍，針對此篇論文設計流程找出的非同義單核苷酸多態性研究。在本篇論文出產之前，尚沒有一個完整針對非同義單核苷酸多態性與藥物不良反應的計算方法或者流程提出，我們希望這設計出的流程可以幫助生物學家更有效率的對藥物不良反應與非同義單核苷酸多態性的關聯做研究。

關鍵字

藥物不良反應；非同義單核苷酸多態性；線上資料庫；氨基酸變異

並列摘要

Adverse drug reactions are a serious problem, causing millions of death. According to report, adverse drug reaction is one of the main failure causes in industries such as drug withdrawal and development when a drug has been distributed to the market. Adverse drug reaction is the fourth leading cause of death in the United States, causing 100,000 deaths each year; nevertheless, adverse drug reactions occur depending on the individual. According to reports(1)(2)(3), it is nsSNP that has the highest possibility to determine whether a person will suffer adverse drug reaction when taking certain drugs. In our work, we designed a flow that incorporates the databases(SIDER, DART, dbSNP) and amino acid substitution prediction tool(SIFT) to make predictions about what nsSNPs might have the correlation with certain adverse drug reactions, and thus bio-techies may have these candidates to do clinical experiments. Before our work, there hasn’t been any methodology or flow proposed for the correlation between adverse drug reactions and nsSNPs. We hope our work can help improve the efficiency in bio-techies’ research on the adverse drug reactions.

並列關鍵字

adverse drug reaction ； Nonsynonymous Single Nucleotide Polymorphism ； SIDER ； DART ； dbSNP ； SIFT ； amino acid substitution

參考文獻

[1] Lei Chen, Tao Huang, Jian Zhang, Ming-Yue Zheng, Kai-Yan Feng, Yu-Dong Cai, and Kuo-Chen Chou, Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions, BioMed Research International, Volume 2013 (2013), 8 pages

[2] Yoshihiro Yamanishi, Edouard Pauwels, and Masaaki Kotera, Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces, Journal of Chemical Information and Modeling, 2012, 52(12), pp.3284-3292

[4] Pauline C. Ng and Steven Henikoff, Predicting the Effects of Amino Acid Substitutions on Protein Function, Annu Rev. Genomics Hum. Genet, 2006. July, pp.61-80

[5] Ng PC Hnikoff S. SIFT: predicting amino acid changes that affect protein function, Nucleic Acids Res., 2003 Jul, pp.3812-3814

[6] L. Z Sun, Z. L. Ji, X. Chen, J. F. Wang and Y. Z. Chen, ADME-AP: a database of ADME associated proteins, Bioinformatics Application Note, 2002, Vol. 18 pp. 1699-1700

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利用線上藥物資料庫與氨基酸變異預測藥物不良反應相關之非同義單核苷酸多態性

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