Protein engineering and design principles employing the 20 standard amino acids have been extensively used to achieve stable protein scaffolds and deliver their specific activities. Although this confers some advantages, it often restricts the sequence, chemical space, and ultimately the functional diversity of proteins. Moreover, although site-specific incorporation of non-natural amino acids (nnAAs) has been proven to be a valuable strategy in protein engineering and therapeutics development, its utility in the affinity-maturation of nanobodies is not fully explored. Besides, current experimental methods do not routinely employ nnAAs due to their enormous library size and infinite combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics simulations and free energy calculations, for the binding affinity prediction of an nnAA-incorporated nanobody toward its target and selection of potent binders. We show that by incorporating halogenated tyrosines, the affinity of 9G8 nanobody can be improved toward epidermal growth factor receptor (EGFR), a crucial cancer target. Surface plasmon resonance (SPR) assays showed that the binding of several 3-chloro-l-tyrosine (3MY)-incorporated nanobodies were improved up to 6-fold into a picomolar range, and the computationally estimated binding affinities shared a Pearson’s r of 0.87 with SPR results. The improved affinity was found to be due to enhanced van der Waals interactions of key 3MY-proximate nanobody residues with EGFR, and an overall increase in the nanobody’s structural stability. In conclusion, we show that our method can facilitate screening large libraries and predict potent site-specific nnAA-incorporated nanobody binders against crucial disease-targets.

中文翻译：

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用于设计具有扩展遗传密码的高亲和力纳米抗体的集成计算管道

采用 20 种标准氨基酸的蛋白质工程和设计原则已被广泛用于实现稳定的蛋白质支架并提供其特定活性。尽管这带来了一些优势，但它通常会限制蛋白质的序列、化学空间以及最终的功能多样性。此外，尽管非天然氨基酸（nnAAs）的位点特异性掺入已被证明是蛋白质工程和治疗开发中的一种有价值的策略，但其在纳米抗体亲和力成熟中的效用尚未得到充分探索。此外，目前的实验方法由于其巨大的库大小和无限的组合，并不经常使用 nnAA。为了解决这个问题，我们开发了一个集成的计算管道，采用基于结构的蛋白质设计方法，分子动力学模拟和自由能计算，用于预测结合 nnAA 的纳米体与其目标的结合亲和力并选择有效的粘合剂。我们表明，通过掺入卤代酪氨酸，9G8 纳米抗体对表皮生长因子受体 (EGFR) 的亲和力可以提高，EGFR 是一种重要的癌症靶点。表面等离子共振 (SPR) 测定表明，几种掺入 3-氯-l-酪氨酸 (3MY) 的纳米抗体的结合提高了 6 倍，达到皮摩尔范围，并且计算估计的结合亲和力共享 0.87 的 Pearson's r与 SPR 结果。发现提高的亲和力是由于关键的 3MY 邻近纳米体残基与 EGFR 的范德华相互作用增强，以及纳米体结构稳定性的整体增加。综上所述，