Designing high affinity therapeutic nanobodies through the incorporation of unnatural a mino acids

采用20种标准氨基酸的蛋白质工程和设计原理已广泛应用于稳定蛋白支架的生产和治疗蛋白的亲和成熟。虽然这带来了一些优势，但它往往限制了蛋白质的序列、化学空间，并最终限制了蛋白质的功能多样性。此外，目前的实验方法往往排除了nnAAs的使用，因为它们的库规模巨大，组合的可能性无限。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、自由能计算和大脑方法，用于预测与nnAA结合的蛋白质对其靶标的结合亲和力，并用于选择有效的结合物。为了测试我们的方法的适用性，表皮生长因子受体（EGFR）的细胞外区域被9G8纳米体靶向，酪氨酸残基被3-氯- l -酪氨酸（3MY）取代，因为它们经常出现在可变结构域，负责抗原结合。因此，一些3my结合的纳米体设计被列入候选名单，它们提高了对EGFR细胞外区域的亲和力，这是许多癌症的关键靶点。我们的研究结果表明，基于结构的计算管道可用于提高与nnAAs结合的治疗蛋白的亲和力，并且可能在其他生物学上重要的蛋白质复合物中被证明是有用的，因为nnAAs的需求正在增长。

Protein engineering and design principles employing the twenty standard amino acids have been extensively used in the production of stable protein scaffolds and in the affinity maturation of therapeutic proteins. While this confers some advantages, it often restricts the sequence, chemical space, and ultimately the functional diversity of proteins. Besides, current experimental methods often exclude the use of nnAAs due to their enormous library size and infinite possibility of combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics simulations, free energy calculations and in cerebro approaches, for the prediction of the binding affinity of proteins incorporated with nnAA toward their target and for the selection of the potent binders. To test the applicability of our approach, the extracellular region of epidermal growth factor receptor (EGFR) was targeted by 9G8 nanobody with tyrosine residues substituted with 3-chloro-L-tyrosine (3MY), as they are frequently found in the variable domain and responsible for antigen binding. Owing to this, several 3MY-incorporated nanobody designs were shortlisted that improve the affinity towards the extracellular region of EGFR, a crucial target for many cancers. Our results demonstrate that the structure-based computational pipeline can be used to improve the affinity of therapeutic proteins incorporated with nnAAs, and may prove to be useful in other biologically important protein complexes in light of the growing demand of nnAAs.