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.

中文翻译：

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计算机指导的文库生成应用于单域抗体的优化。

计算机指导的文库生成是优化抗体的合理策略。在本文中，我们报道了使用这种方法改善了单域骆驼科动物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，以描述抗体-抗原相互作用表面的精确能量分布。基于此特性，我们推测，在计算机芯片诱变可用于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。经过三轮选择后，确定了优化的抗体突变体，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，产生各种动力学响应，并产生更大的亲和力（> 10倍） ）的抗原。