Suppr超能文献

抗体亲和力成熟的计算方法:从初始命中到优化结合物的小规模表达。

Antibody Affinity Maturation Using Computational Methods: From an Initial Hit to Small-Scale Expression of Optimized Binders.

机构信息

Department of Chemical and Pharmaceutical Sciences, University of Trieste, Trieste, Italy.

CONCEPT Lab, Istituto Italiano di Tecnologia, Genova, Italy.

出版信息

Methods Mol Biol. 2023;2552:333-359. doi: 10.1007/978-1-0716-2609-2_19.

Abstract

Nanobodies (VHHs) are engineered fragments of the camelid single-chain immunoglobulins. The VHH domain contains the highly variable segments responsible for antigen recognition. VHHs can be easily produced as recombinant proteins. Their small size is a good advantage for in silico approaches. Computer methods represent a valuable strategy for the optimization and improvement of their binding affinity. They also allow for epitope selection offering the possibility to design new VHHs for regions of a target protein that are not naturally immunogenic. Here we present an in silico mutagenic protocol developed to improve the binding affinity of nanobodies together with the first step of their in vitro production. The method, already proven successful in improving the low Kd of a nanobody hit obtained by panning, can be employed for the ex novo design of antibody fragments against selected protein target epitopes.

摘要

纳米抗体(VHH)是经过工程改造的骆驼科单链免疫球蛋白片段。VHH 结构域包含负责抗原识别的高度可变片段。VHH 可以很容易地作为重组蛋白进行生产。其体积小的特点使其非常适合计算机模拟方法。计算机方法是优化和提高其结合亲和力的有效策略。它们还允许进行表位选择,为设计针对目标蛋白中天然非免疫原性区域的新型 VHH 提供了可能性。在这里,我们提出了一种用于提高纳米抗体结合亲和力的计算机诱变方案,以及其体外生产的第一步。该方法已经在通过淘选获得的低亲和力纳米抗体命中的改进中被证明是成功的,可用于针对选定的蛋白靶标表位的抗体片段的从头设计。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验