Coarse-grained model simulation-guided localized DNA signal amplification probe for miRNA detection

信号(编程语言) DNA 计算机科学 生物系统 分子诊断学 纳米技术 滚动圆复制 探测理论 功能(生物学) 杂交探针 计算生物学 生物物理学 化学 材料科学 细胞生物学 生物 生物信息学 DNA复制 探测器 生物化学 电信 程序设计语言
作者
Linghao Zhang,Hongyang Zhao,Huixiao Yang,Xin Su
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:239: 115622-115622 被引量:14
标识
DOI:10.1016/j.bios.2023.115622
摘要

DNA-based enzyme-free signal amplification strategies are widely employed to detect biomarkers in low abundance. To enhance signal amplification, localized DNA reaction units which increases molecular collision probability is commonly utilized. However, the current understanding of the structure-function relationships in localized DNA signal amplification probes is limited, leading to unsatisfied performance. In this study, we introduced a coarse-grained molecular model to simulate the dynamic behavior of two DNA reaction units within a DNA enzyme-free signal amplification circuit called Localized Catalytic Hairpin Assembly (LCHA). We investigated the impact of localized distance and flexibility on reaction performance. The most efficient LCHA probe guided by simulation exhibits sensitivity 28 times greater that of free CHA, with a detection limit of miR-21 reaching 16 pM, while the least effective LCHA probe demonstrated a modest improvement of only 7 times. We successfully employed the optimized probe to differentiate cancer cells from normal cells based on their miR-21 expression levels, showcasing its quantification ability. By elucidating the mechanistic insights and structure-function relationship in our work, we aim to contribute valuable information that can save users' time and reduce costs when designing localized DNA probes. With a comprehensive understanding of how the localization affects probe performance, researchers can now make more informed and efficient decisions during the design process. This work would find broad applications of DNA nanotechnology in biosensing, biocomputing, and bionic robots.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
黄黄发布了新的文献求助10
1秒前
1秒前
SciGPT应助高冷办采纳,获得10
1秒前
CodeCraft应助圈圈采纳,获得10
1秒前
saf0852完成签到,获得积分10
3秒前
zhang发布了新的文献求助10
3秒前
量子星尘发布了新的文献求助10
4秒前
6秒前
炸虾仁发布了新的文献求助10
6秒前
7秒前
777完成签到,获得积分10
7秒前
8秒前
9秒前
9秒前
10秒前
10秒前
12秒前
13秒前
chendacai发布了新的文献求助10
13秒前
皮卡丘完成签到,获得积分10
13秒前
13秒前
Jasper应助黄黄采纳,获得10
14秒前
14秒前
仁爱凡阳发布了新的文献求助10
15秒前
JF123_发布了新的文献求助10
15秒前
机灵饼干发布了新的文献求助10
16秒前
unique关注了科研通微信公众号
16秒前
orixero应助summer采纳,获得10
16秒前
栗子驳回了Lucas应助
17秒前
白小黑发布了新的文献求助10
18秒前
陈末应助女爰舍予采纳,获得10
18秒前
小帆船发布了新的文献求助10
19秒前
m彬m彬完成签到 ,获得积分10
19秒前
SciGPT应助嘉欣采纳,获得10
20秒前
方子怡发布了新的文献求助10
20秒前
20秒前
文艺涵瑶完成签到,获得积分10
21秒前
Jasper应助文献狗采纳,获得10
21秒前
chendacai完成签到,获得积分10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 921
Identifying dimensions of interest to support learning in disengaged students: the MINE project 800
Synthesis and properties of compounds of the type A (III) B2 (VI) X4 (VI), A (III) B4 (V) X7 (VI), and A3 (III) B4 (V) X9 (VI) 500
Antihistamine substances. XXII; Synthetic antispasmodics. IV. Basic ethers derived from aliphatic carbinols and α-substituted benzyl alcohols 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5430823
求助须知:如何正确求助?哪些是违规求助? 4543941
关于积分的说明 14189780
捐赠科研通 4462379
什么是DOI,文献DOI怎么找? 2446515
邀请新用户注册赠送积分活动 1437962
关于科研通互助平台的介绍 1414553