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基于适体的肉毒梭菌神经毒素 C 检测的对接模拟和三明治检测法。

Docking Simulation and Sandwich Assay for Aptamer-Based Botulinum Neurotoxin Type C Detection.

机构信息

School of Biological Sciences, Chungbuk National University, 1 Chungdae-Ro, Seowon-Gu, Cheongju 28644, Korea.

Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.

出版信息

Biosensors (Basel). 2020 Aug 12;10(8):98. doi: 10.3390/bios10080098.

DOI:10.3390/bios10080098
PMID:32806662
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7460441/
Abstract

Aptamers are biomaterials that bind to a target molecule through a unique structure, and have high applicability in the diagnostic and medical fields. To effectively utilize aptamers, it is important to analyze the structure of the aptamer binding to the target molecule; however, there are difficulties in experimentally identifying this structure. In the modern pharmaceutical industry, computer-driven docking simulations that predict intermolecular binding models are used to select candidates that effectively bind target molecules. Botulinum toxin (BoNT) is the most poisonous neurotoxin produced from the bacteria, and BoNT/C, one of the eight serotypes, causes paralysis in livestock. In this study, the aptamers that bound to BoNT/C were screened via the systematic evolution of ligands by exponential enrichment, and the binding affinity analysis and binding model were evaluated to select optimal aptamers. Based on surface plasmon resonance analysis and molecular operating environment docking simulation, a pair of aptamers that had high binding affinity to BoNT/C and were bound to different BoNT/C sites were selected. A sandwich assay based on this aptamer pair detected the BoNT/C protein to a concentration as low as ~0.2 ng Ml. These results show that docking simulations are a useful strategy for screening aptamers that bind to specific targets.

摘要

适配体是通过独特结构与靶分子结合的生物材料,在诊断和医学领域具有很高的适用性。为了有效地利用适配体,分析与靶分子结合的适配体的结构非常重要;然而,实验确定该结构存在困难。在现代制药行业中,使用计算机驱动的对接模拟来预测分子间结合模型,以选择有效结合靶分子的候选物。肉毒杆菌毒素(BoNT)是细菌产生的最毒神经毒素,其中一种血清型 BoNT/C 会导致牲畜瘫痪。在这项研究中,通过指数富集的配体系统进化筛选出与 BoNT/C 结合的适配体,并对其结合亲和力分析和结合模型进行评估,以选择最佳的适配体。基于表面等离子体共振分析和分子操作环境对接模拟,选择了一对与 BoNT/C 具有高结合亲和力且与不同 BoNT/C 结合位点结合的适配体。基于该适配体对的夹心测定法可检测到低至约 0.2ng/ml 的 BoNT/C 蛋白。这些结果表明,对接模拟是筛选与特定靶标结合的适配体的一种有效策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/34b2a9dbb942/biosensors-10-00098-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/0968d501ad7c/biosensors-10-00098-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/6df2280b7ad6/biosensors-10-00098-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/db7547fd0fd5/biosensors-10-00098-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/34b2a9dbb942/biosensors-10-00098-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/0968d501ad7c/biosensors-10-00098-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/6df2280b7ad6/biosensors-10-00098-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/db7547fd0fd5/biosensors-10-00098-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0ad/7460441/34b2a9dbb942/biosensors-10-00098-g004.jpg

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Aptamer-Based Pathogen Monitoring for ser. Typhimurium.基于适体的鼠伤寒沙门氏菌病原体监测。
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