The Combination of Computational and Biosensing Technologies for Selecting Aptamer against Prostate Specific Antigen.
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 sequenc...
| Publicado en: | BioMed Research International Vol. 2017; pp. 1 - 12 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
3/28/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122103921&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122103921 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 3/28/2017 vid: 2017 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 122103921 122103921 122103921 10.1155/2017/5041683 122103921 ppf: 1 ppct: 11 formats: fmt: @attributes: type: P tig: atl: The Combination of Computational and Biosensing Technologies for Selecting Aptamer against Prostate Specific Antigen. aug: au: Hsieh, Pi-Chou Lin, Hui-Ting Chen, Wen-Yih Tsai, Jeffrey J. P. Hu, Wen-Pin affil: Department of Bioinformatics and Medical Engineering, Asia University, Taichung City 41354, Taiwan sug: subj: Prostate-Specific Antigen Analysis Oligonucleotide Array Sequence Analysis Biosensing Techniques Bioinformatics Human Male DNA Genetics Molecular Biology Imaging, Three-Dimensional Proteins Data Analysis Software Descriptive Statistics Funding Source Male ab: 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. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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