AET 2024:利用尖端 DNA 技术构建精准的抗体工程文库

alt text
演讲者
Radha Parmar
Twist 生物制剂 - 欧洲、中东和非洲地区科技顾问

本次网络研讨会中涵盖的内容
如何利用基于结构的机器学习来设计针对 GPCR 靶标 C5aR1 的预测抗体结合体
Twist 的寡聚合成平台及其在创建高度多样化的 CDR 重排文库和构建全新噬菌体展示中的应用
在细胞实验中鉴定出几种能在功能上阻断 C5aR1 信号的高亲和力先导物

Structure-based machine learning was leveraged to design predicted antibody binders against the GPCR target C5aR1. The CDR sequences of these predicted binders were then used to construct a de-novo phage-display library. Twist’s oligo-synthesis platform enabled fabrication of a highly diverse CDR-shuffle library with excellent variant representation and with no unwanted bias or motifs. Following panning, several high-affinity leads were identified that functionally blocked C5aR1 signaling in cellular assays. 

This symposium was part of the event Antibody Engineering & Therapeutics Europe 2024.

填写您的详细信息,观看网络研讨会

 

 

Powered by Translations.com GlobalLink Web Software