Non-SELEX Selection of Aptamers

指数富集配体系统进化 适体 化学 选择(遗传算法) 毛细管电泳 DNA 计算生物学 计算机科学 核糖核酸 色谱法 分子生物学 人工智能 生物 生物化学 基因
作者
Maxim V. Berezovski,Michael U. Musheev,Andrei P. Drabovich,Sergey N. Krylov
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
卷期号:128 (5): 1410-1411 被引量:235
标识
DOI:10.1021/ja056943j
摘要

Aptamers are typically selected from libraries of random DNA (or RNA) sequences by SELEX, which involves multiple rounds of alternating steps of partitioning and PCR amplification. Here we report, for the first time, non-SELEX selection of aptamersa process that involves repetitive steps of partitioning with no amplification between them. A highly efficient affinity method, non-equilibrium capillary electrophoresis of equilibrium mixtures (NECEEM), was used for partitioning. We found that three steps of NECEEM-based partitioning in the non-SELEX approach were sufficient to improve the affinity of a DNA library to a target protein by more than 4 orders of magnitude. The resulting affinity was higher than that of the enriched library obtained in three rounds of NECEEM-based SELEX. Remarkably, NECEEM-based non-SELEX selection took only 1 h in contrast to several days or several weeks required for a typical SELEX procedure by conventional partitioning methods. In addition, NECEEM-based non-SELEX allowed us to accurately measure the abundance of aptamers in the library. Not only does this work introduce an extremely fast and economical method for aptamer selection, but it also suggests that aptamers may be much more abundant than they are thought to be. Finally, this work opens the opportunity for selection of drug candidates from libraries of small molecules, which cannot be PCR-amplified and thus are not approachable by SELEX.
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
悠悠发布了新的文献求助10
1秒前
生动娩发布了新的文献求助10
2秒前
LEMON发布了新的文献求助10
2秒前
2秒前
2秒前
科研通AI6应助LiYong采纳,获得10
3秒前
二三发布了新的文献求助10
3秒前
林小雨完成签到,获得积分10
4秒前
4秒前
科研新兵完成签到,获得积分10
4秒前
fanfan完成签到 ,获得积分10
5秒前
wuqs发布了新的文献求助10
5秒前
正直的小熊猫完成签到,获得积分10
5秒前
量子星尘发布了新的文献求助10
6秒前
麦田守望者完成签到,获得积分10
6秒前
6秒前
JamesPei应助活泼巧曼采纳,获得10
7秒前
酷酷的笔记本完成签到,获得积分0
7秒前
dinmei发布了新的文献求助10
8秒前
IceyMY完成签到,获得积分20
8秒前
小二郎应助舒心的耷采纳,获得30
8秒前
9秒前
冷冷发布了新的文献求助10
10秒前
11秒前
Orange应助火星上笑蓝采纳,获得10
12秒前
12秒前
所所应助秦奎采纳,获得10
14秒前
14秒前
sadasdzd发布了新的文献求助30
17秒前
18秒前
19秒前
科目三应助aa采纳,获得10
20秒前
20秒前
20秒前
生动娩发布了新的文献求助10
21秒前
量子星尘发布了新的文献求助10
21秒前
dinmei完成签到,获得积分10
21秒前
21秒前
七七七七完成签到 ,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
Mechanics of Solids with Applications to Thin Bodies 5000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
人脑智能与人工智能 1000
King Tyrant 720
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5599407
求助须知:如何正确求助?哪些是违规求助? 4685010
关于积分的说明 14837502
捐赠科研通 4668037
什么是DOI,文献DOI怎么找? 2537906
邀请新用户注册赠送积分活动 1505398
关于科研通互助平台的介绍 1470783