One-step site-specific antibody fragment auto-conjugation using SNAP-tag technology

咬合 片段(逻辑) 计算生物学 生物 计算机科学 算法 计算机图形学(图像)
作者
Ahmad Fawzi Hussain,Paul A. Heppenstall,Florian Kampmeier,Ivo Meinhold‐Heerlein,Stefan Barth
出处
期刊:Nature Protocols [Nature Portfolio]
卷期号:14 (11): 3101-3125 被引量:23
标识
DOI:10.1038/s41596-019-0214-y
摘要

Antibody-based diagnostic and therapeutic agents play a substantial role in medicine, especially in cancer management. A variety of chemical, genetic and enzymatic site-specific conjugation methods have been developed for equipping antibodies with effector molecules to generate homogeneous antibody conjugates with tailored properties. However, most of these methods are relatively complicated and expensive and require several reaction steps. Self-labeling proteins such as the SNAP-tag are an innovative solution for addressing these challenges. The SNAP-tag is a modified version of the human DNA repair enzyme alkylguanine-DNA alkyltransferase (AGT), which reacts specifically with O(6)-benzylguanine (BG)-modified molecules via irreversible transfer of an alkyl group to a cysteine residue. It provides a simple, controlled and robust site-specific method for labeling antibodies with different synthetic small effector molecules. Fusing a SNAP-tag to recombinant antibodies allows efficient conjugation of BG-containing substrates by autocatalytic, irreversible transfer of the alkyl group to a cysteine residue in the enzyme's active site under physiological conditions and with a 1:1 stoichiometry. This protocol describes how to generate site-specific SNAP-tag single-chain antibody fragment (scFv) conjugates with different types of BG-modified effector molecules. A specific example is included for the design and production of an scFv-photosensitizer conjugate and its characterization as an immuno-theranostic agent. This protocol includes DNA sequences encoding scFV-SNAP-tag fusion proteins and outlines strategies for expression, purification and testing of the resulting scFv-SNAP-tag-based immuno-conjugates. All experiments can be performed by a graduate-level researcher with basic molecular biology skills within an 8-week time frame.
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
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
荧123456完成签到,获得积分10
刚刚
HHHHH发布了新的文献求助10
3秒前
舒心靖琪完成签到 ,获得积分10
4秒前
一桶吃八碗完成签到,获得积分10
5秒前
科研通AI5应助亢kxh采纳,获得10
6秒前
冷月芳华完成签到,获得积分10
6秒前
小二郎应助Ella采纳,获得10
6秒前
自由的雁完成签到,获得积分10
7秒前
7秒前
刻苦的坤完成签到,获得积分10
8秒前
9秒前
12秒前
13秒前
14秒前
jeremy发布了新的文献求助10
18秒前
完美世界应助lqm采纳,获得10
19秒前
22秒前
李倇仪完成签到,获得积分10
23秒前
swjs08发布了新的文献求助20
24秒前
英俊的铭应助越战越勇采纳,获得10
24秒前
稀里糊涂的吃瓜人完成签到 ,获得积分10
25秒前
亢kxh发布了新的文献求助10
25秒前
26秒前
lihua完成签到,获得积分10
27秒前
mamahaha完成签到 ,获得积分10
27秒前
28秒前
花花完成签到,获得积分10
28秒前
月亮完成签到,获得积分10
29秒前
30秒前
31秒前
beyondjun发布了新的文献求助10
32秒前
32秒前
张张发布了新的文献求助30
33秒前
科研通AI5应助欧了买了噶采纳,获得10
33秒前
Yunis完成签到 ,获得积分10
34秒前
AiX-zzzzz完成签到,获得积分10
34秒前
科研通AI5应助亢kxh采纳,获得10
34秒前
34秒前
哈哈发布了新的文献求助30
35秒前
华仔应助ori采纳,获得10
35秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Advances in Underwater Acoustics, Structural Acoustics, and Computational Methodologies 400
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
The Monocyte-to-HDL ratio (MHR) as a prognostic and diagnostic biomarker in Acute Ischemic Stroke: A systematic review with meta-analysis (P9-14.010) 240
The Burge and Minnechaduza Clarendonian mammalian faunas of north-central Nebraska 206
Fatigue of Materials and Structures 200
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3831508
求助须知:如何正确求助?哪些是违规求助? 3373738
关于积分的说明 10481136
捐赠科研通 3093686
什么是DOI,文献DOI怎么找? 1702949
邀请新用户注册赠送积分活动 819215
科研通“疑难数据库(出版商)”最低求助积分说明 771307