Department of Bioinformatics and Medical Engineering, Asia University, Taichung City 41354, Taiwan.
Department of Physical Therapy, I-Shou University, Kaohsiung City 82445, Taiwan.
Biomed Res Int. 2017;2017:5041683. doi: 10.1155/2017/5041683. Epub 2017 Mar 28.
Herein, we report a method of combining bioinformatics and biosensing technologies to select aptamers against prostate specific antigen (PSA). The main objective of this study is to select DNA aptamers with higher binding affinity for PSA by using the proposed method. Based on the five known sequences of PSA-binding aptamers, we adopted the functions of reproduction and crossover in the genetic algorithm to produce next-generation sequences for the computational and experimental analysis. RNAfold web server was utilized to analyze the secondary structures, and the 3-dimensional molecular models of aptamer sequences were generated by using RNAComposer web server. ZRANK scoring function was used to rerank the docking predictions from ZDOCK. The biosensors, the quartz crystal microbalance (QCM) and a surface plasmon resonance (SPR) instrument, were used to verify the binding ability of selected aptamer for PSA. By carrying out the simulations and experiments after two generations, we obtain one aptamer that can have the highest binding affinity with PSA, which generates almost 2-fold and 3-fold greater measured signals than the responses produced by the best known DNA sequence in the QCM and SPR experiments, respectively.
在此，我们报告了一种结合生物信息学和生物传感技术来筛选针对前列腺特异性抗原（PSA）的适体的方法。本研究的主要目的是通过使用所提出的方法选择对 PSA 具有更高结合亲和力的 DNA 适体。基于已知的 PSA 结合适体的五个序列，我们采用遗传算法中的繁殖和交叉功能来生成新一代序列，进行计算和实验分析。使用 RNAfold 网络服务器分析二级结构，并使用 RNAComposer 网络服务器生成适体序列的三维分子模型。使用 ZRANK 评分函数对 ZDOCK 的对接预测进行重新排序。使用石英晶体微天平（QCM）和表面等离子体共振（SPR）仪器作为生物传感器，验证所选适体与 PSA 的结合能力。经过两代的模拟和实验，我们获得了一个能够与 PSA 具有最高结合亲和力的适体，它在 QCM 和 SPR 实验中产生的测量信号分别比已知的最佳 DNA 序列产生的响应高近 2 倍和 3 倍。
