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Acquiring multiple signals along with the reaction time: improving recognition capability of a multidimensional colorimetric sensor array for sensitive protein detection.
Yang, Jiaoe; He, Liuying; Lu, Yuexiang; Gao, Xinxin; Wang, Feiyang; Jing, Wenjie; Liu, Yueying.
Afiliação
  • Yang J; Department of Chemistry, Capital Normal University, Beijing, 100048, P.R. China. yueyingliu@cnu.edu.cn.
Analyst ; 142(14): 2663-2669, 2017 Jul 10.
Article em En | MEDLINE | ID: mdl-28616944
ABSTRACT
The development of sensitive and cheap sensor arrays for identification of proteins plays an important role in many bioanalytical and clinical investigations. Here, we introduce a multidimensional colorimetric sensor array for the detection of multiple proteins based on acquiring multiple signals along with the reaction time to enhance the discrimination ability. In a single experiment, the unique fingerprint for each protein against the sensor array is generated from a response absorbance signal at three reaction time points (at 10 min, 15 min, and 20 min). Our colorimetric sensing system is able to identify ten proteins not only in aqueous solution at 10 nM but also in human urine at the 50 nM level with an accuracy of 100%. Moreover, the identification of HSA in urine at the nanomolar level within a linear range of 0.05-1.0 µM is achieved. Our sensing array system is sufficiently sensitive for the discrimination of pure HSA, binary mixtures of HSA and Lys at a total concentration of 50 nM in urine. This study indicates that the application of the real-time resolved response signals enables the enhancement of the discrimination ability for protein recognition.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Colorimetria Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Colorimetria Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2017 Tipo de documento: Article