Human Health Therapeutics Research Centre, National Research Council Canada, Montreal, Quebec, Canada.
MAbs. 2024 Jan-Dec;16(1):2404064. doi: 10.1080/19420862.2024.2404064. Epub 2024 Sep 17.
The engineering of pH-sensitive therapeutic antibodies, particularly for improving effectiveness and specificity in acidic solid-tumor microenvironments, has recently gained traction. While there is a justified need for pH-dependent immunotherapies, current engineering techniques are tedious and laborious, requiring repeated rounds of experiments under different pH conditions. Inexpensive computational techniques to predict the effectiveness of His pH-switches require antibody-antigen complex structures, but these are lacking in most cases. To circumvent these requirements, we introduce a sequence-based method for predicting His mutations in the variable region of antibodies, which could lead to pH-biased antigen binding. This method, called Sequence-based Identification of pH-sensitive Antibody Binding (SIpHAB), was trained on 3D-structure-based calculations of 3,490 antibody-antigen complexes with solved experimental structures. SIpHAB was parametrized to enhance preferential binding either toward or against the acidic pH, for selective targeting of solid tumors or for antigen release in the endosome, respectively. Applications to nine antibody-antigen systems with previously reported binding preferences at different pHs demonstrated the utility and enrichment capabilities of this high-throughput computational tool. SIpHAB, which only requires knowledge of the antibody primary amino-acid sequence, could enable a more efficient triage of pH-sensitive antibody candidates than could be achieved conventionally. An online webserver for running SipHAB is available freely at https://mm.nrc-cnrc.gc.ca/software/siphab/runner/.
工程 pH 敏感治疗性抗体,特别是提高效力和特异性在酸性实体瘤微环境中,最近得到了重视。虽然有合理的需要 pH 依赖性免疫疗法,目前的工程技术繁琐而乏味,需要在不同的 pH 条件下进行反复实验。预测 His pH 开关的有效性的廉价计算技术需要抗体-抗原复合物结构,但在大多数情况下缺乏这些结构。为了规避这些要求,我们引入了一种基于序列的方法来预测抗体可变区中的 His 突变,这可能导致 pH 偏向性抗原结合。这种方法称为基于序列的 pH 敏感抗体结合识别(SIpHAB),是基于 3490 个具有解决实验结构的抗体-抗原复合物的 3D 结构计算进行训练的。SIpHAB 进行了参数化设置,以增强对酸性 pH 的优先结合,分别用于选择性靶向实体瘤或在内涵体中释放抗原。应用于 9 个抗体-抗原系统,这些系统在不同 pH 值下具有先前报道的结合偏好,证明了这种高通量计算工具的实用性和富集能力。SIpHAB 只需要抗体的一级氨基酸序列的知识,就可以比传统方法更有效地对 pH 敏感的抗体候选物进行分类。一个用于运行 SipHAB 的在线网络服务器可在 https://mm.nrc-cnrc.gc.ca/software/siphab/runner/ 上免费获得。