计算机引导文库生成应用于单结构域抗体的优化。

IF 2.6 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Hiroki Akiba, Hiroko Tamura, Jose M M Caaveiro, Kouhei Tsumoto
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引用次数: 6

摘要

计算机引导文库生成是一种优化抗体的可行策略。在此,我们报告了使用这种方法提高单域骆驼抗体对其抗原的亲和力。我们首先进行了实验和计算丙氨酸扫描来描述抗体-抗原相互作用表面的精确能量剖面。基于这一特性,我们假设可以利用硅诱变技术来指导噬菌体展示小文库的开发,目的是提高抗体对其抗原的亲和力。经过三轮筛选,优化的抗体突变体被确定,其中抗体-抗原界面核心的丙氨酸残基被具有大侧链的残基取代,产生不同的动力学响应,并且对抗原具有更大的亲和力(>10倍)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-guided library generation applied to the optimization of single-domain antibodies.

Computer-guided library generation is a plausible strategy to optimize antibodies. Herein, we report the improvement of the affinity of a single-domain camelid antibody for its antigen using such approach. We first conducted experimental and computational alanine scanning to describe the precise energetic profile of the antibody-antigen interaction surface. Based on this characterization, we hypothesized that in-silico mutagenesis could be employed to guide the development of a small library for phage display with the goal of improving the affinity of an antibody for its antigen. Optimized antibody mutants were identified after three rounds of selection, in which an alanine residue at the core of the antibody-antigen interface was substituted by residues with large side-chains, generating diverse kinetic responses, and resulting in greater affinity (>10-fold) for the antigen.

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来源期刊
Protein Engineering Design & Selection
Protein Engineering Design & Selection 生物-生化与分子生物学
CiteScore
3.30
自引率
4.20%
发文量
14
审稿时长
6-12 weeks
期刊介绍: Protein Engineering, Design and Selection (PEDS) publishes high-quality research papers and review articles relevant to the engineering, design and selection of proteins for use in biotechnology and therapy, and for understanding the fundamental link between protein sequence, structure, dynamics, function, and evolution.
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