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使用单价噬菌体展示进行抗体人源化。

Antibody humanization using monovalent phage display.

作者信息

Baca M, Presta L G, O'Connor S J, Wells J A

机构信息

Department of Protein Engineering, Genentech, Inc., South San Francisco, California 94080, USA.

出版信息

J Biol Chem. 1997 Apr 18;272(16):10678-84. doi: 10.1074/jbc.272.16.10678.

Abstract

Antibody humanization often requires the replacement of key residues in the framework regions with corresponding residues from the parent non-human antibody. These changes are in addition to grafting of the antigen-binding loops. Although guided by molecular modeling, assessment of which framework changes are beneficial to antigen binding usually requires the analysis of many different antibody mutants. Here we describe a phage display method for optimizing the framework of humanized antibodies by random mutagenesis of important framework residues. We have applied this method to humanization of the anti-vascular endothelial growth factor murine monoclonal antibody A4.6.1. Affinity panning of a library of humanized A4.6.1 antibody mutants led to the selection of one variant with greater than 125-fold enhanced affinity for antigen relative to the initial humanized antibody with no framework changes. A single additional mutation gave a further 6-fold improvement in binding. The affinity of this variant, 9.3 nM, was only 6-fold weaker than that of a murine/human chimera of A4.6.1. This method provides a general means of rapidly selecting framework mutations that improve the binding of humanized antibodies to their cognate antigens and may prove an attractive alternative to current methods of framework optimization based on cycles of site-directed mutagenesis.

摘要

抗体人源化通常需要将框架区中的关键残基替换为亲本非人类抗体的相应残基。这些改变是在移植抗原结合环之外的。尽管有分子建模的指导,但评估哪些框架改变对抗原结合有益通常需要分析许多不同的抗体突变体。在此,我们描述了一种通过对重要框架残基进行随机诱变来优化人源化抗体框架的噬菌体展示方法。我们已将此方法应用于抗血管内皮生长因子鼠单克隆抗体A4.6.1的人源化。对人源化A4.6.1抗体突变体文库进行亲和力淘选,相对于未进行框架改变的初始人源化抗体,筛选出了一种对抗原亲和力提高超过125倍的变体。单一的额外突变使结合力进一步提高了6倍。该变体的亲和力为9.3 nM,仅比A4.6.1的鼠/人嵌合体弱6倍。此方法提供了一种快速选择框架突变的通用方法,可改善人源化抗体与其同源抗原的结合,并且可能被证明是基于定点诱变循环的当前框架优化方法的一种有吸引力的替代方法。

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