4.7 Article

Preparation of anti-nonspecific adsorption polydopamine-based surface protein-imprinted magnetic microspheres with the assistance of 2-methacryloyloxyethyl phosphorylcholine and its application for protein recognition

期刊

SENSORS AND ACTUATORS B-CHEMICAL
卷 241, 期 -, 页码 413-421

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2016.10.105

关键词

Protein imprinting; Anti-nonspecific adsorption; 2-Methacryloyloxyethyl phosphorylcholine; Polydopamine; Recognition specificity

资金

  1. National Natural Science Foundation of China [51433008]
  2. National High Technology Research and Development Program of China (863 program) [2012AA02A404]
  3. Natural Science Foundation of Shaanxi Province [2015JQ2055]

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A new anti-protein nonspecific adsorption polydopamine-based surface protein-imprinted magnetic microsphere was prepared by using surface imprinting and AGET-ATRP in this work. The highlights were as follows. Firstly, different from our previous work, we could guarantee that there was no anti-protein nonspecific adsorption MPC chain segment in the imprinted sites. This fact could eliminate the negative influence of MPC chain segment on imprinted sites and further ensure the high imprinting efficiency. Secondly, the length of MPC chain segment was optimized to weaken the influence of protein resistance effect on adsorption capacity on the premise of guaranteeing excellent anti-protein nonspecific adsorption. The results showed that the optimal dopamine layer thickness was 10 nm. The mass ratio of MPC and Fe3O4@SiO2@Pdop-MIPs-Br was determined as 12/1. Under such conditions, after the graft of MPC, the adsorption capacity of imprinted microspheres for BSA decreased only a little from 9.39 mg/g to 8.26 mg/g, whereas the imprinting factor increased markedly from 1.53 to 5.74, revealing the advantage of this work. Finally, the successful applications in protein recognition showed that the new strategy was expected to be an effective means for improving the detection sensitivity of molecularly imprinted biosensors. (C) 2016 Elsevier B.V. All rights reserved.

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