Key amino acids for initial round of mutations.

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

胸腺基质淋巴细胞生成素（Thymic stromal lymphopoietin, TSLP）是参与哮喘及其他过敏性疾病发病机制的关键细胞因子。靶向TSLP及其信号通路已日益被认为是哮喘治疗的有效策略。本研究通过整合计算与实验方法，对特异性靶向TSLP的T6抗体进行亲和力优化。T6抗体对TSLP的初始亲和力低于参比抗体AMG157。为提升该亲和力，研究团队利用丙氨酸扫描、分子对接以及mCSM-PPI2、GEO-PPI等计算工具，筛选出可用于定点突变的关键氨基酸残基。后续的突变实验与验证结果显示，所获抗体对TSLP的阻断能力显著提升。本研究结果证实了计算机辅助技术在加速抗体亲和力成熟方面的应用潜力，可有效缩短实验周期、降低实验成本。计算方法与实验手段的结合，为开发针对TSLP相关疾病的靶向治疗抗体提供了广阔前景。