An efficient and universal In silico screening strategy for acquisition of high-affinity Aptamer and its application in analytical utility

适体 化学 指数富集配体系统进化 生物信息学 离解常数 互补性(分子生物学) 互补决定区 组合化学 纳米技术 计算生物学 核糖核酸 分子生物学 生物化学 受体 生物 基因 肽序列 遗传学 材料科学
作者
Qionglin Wang,Pengbo Guo,Weyland Cheng,Yuchun Liu,Yaodong Zhang,Peng Huo,Shubin Feng,Wancun Zhang
出处
期刊:Talanta [Elsevier BV]
卷期号:269: 125535-125535
标识
DOI:10.1016/j.talanta.2023.125535
摘要

Numerous aptamers against various targets have been identified through the technology of systematic evolution of ligands by exponential enrichment (SELEX), but the affinity of these aptamers are often insufficient due to the limitations of SELEX. Therefore, a more rational in silico screening strategy (ISS) was developed for efficient screening of high affinity aptamers, which took shape complementarity and thermodynamic stability into consideration. Neuron specific enolase (NSE), a tumor marker, was selected as the target molecule. In the screening process, three aptamer candidates with good shape complementarity, lower ΔG values, and higher ZDOCK scores were produced. The dissociation constant (Kd) of these candidates to NSE was determined to be 10.13 nM, 14.82 nM, and 2.76 nM, respectively. Each of them exhibited higher affinity to NSE than the parent aptamer (Kd = 23.83 nM). Finally, an antibody-free fluorescence aptasensor assay, based on the aptamer with the highest affinity, P–5C8G, was conducted, resulting in a limit of detection (LOD) value of 1.8 nM, which was much lower than the parental aptamer (P, LOD = 12.6 nM). The proposed ISS approach provided an efficient and universal strategy to improve the aptamer to have a high affinity and good analytical utility.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
刚刚
刚刚
徐六硕完成签到,获得积分10
刚刚
dang发布了新的文献求助10
1秒前
1秒前
3秒前
科研通AI6.3应助健壮尔丝采纳,获得10
4秒前
4秒前
小半发布了新的文献求助10
4秒前
WJDNG5发布了新的文献求助10
6秒前
研友_ngOYYn完成签到,获得积分10
6秒前
今后应助游志涛采纳,获得10
7秒前
NexusExplorer应助gsgg采纳,获得10
7秒前
ccorange完成签到,获得积分10
7秒前
VitoLi发布了新的文献求助10
8秒前
9秒前
shoolarli完成签到,获得积分10
9秒前
9秒前
10秒前
孤独完成签到,获得积分10
11秒前
小半完成签到,获得积分10
11秒前
13秒前
13秒前
她说肚子是吃大的i完成签到,获得积分10
14秒前
水蒸气完成签到,获得积分10
14秒前
14秒前
科研通AI6.1应助刘大力采纳,获得10
15秒前
16秒前
16秒前
淳于汲完成签到 ,获得积分10
17秒前
无心的雅霜完成签到,获得积分10
17秒前
17秒前
健壮尔丝发布了新的文献求助10
18秒前
FashionBoy应助纯牛马打工人采纳,获得10
18秒前
18秒前
18秒前
18秒前
18秒前
18秒前
xiaoqiang发布了新的文献求助10
19秒前
高分求助中
Ideology and Meaning-Making under the Putin Regime 750
Prompt Engineering for Clinicians: Harnessing AI in Everyday Medical Practice 600
Handbook of Luminescence Dating 500
Safety Pharmacology 500
《KNN基无铅压电陶瓷电学性能优化与物理机理研究》 500
A Handbook of User Experience Research & Design in Libraries 400
Understanding Modeling and Simulation of Polymerization Reactions 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 计算机科学 化学工程 生物化学 物理 内科学 复合材料 催化作用 光电子学 物理化学 电极 细胞生物学 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6921700
求助须知:如何正确求助?哪些是违规求助? 8611588
关于积分的说明 18270090
捐赠科研通 6338235
什么是DOI,文献DOI怎么找? 3070356
关于科研通互助平台的介绍 2101120
邀请新用户注册赠送积分活动 2047590