School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
School of Pharmacy and Bioengineering, Chongqing University of Technology, Pittsburgh, PA 15261, USA.
Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab143.
The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.
多年来,治疗性抗体的设计吸引了大量关注。抗体由于其高效性和低不良反应事件风险而被广泛用于治疗许多疾病。然而,抗体设计的实验方法既耗时又昂贵。尽管过去几年计算性抗体设计技术取得了重大进展,但仍存在一些需要解决的挑战,例如抗原结构的灵活性、缺乏抗体结构数据以及缺乏标准的抗体设计方案。在本工作中,我们详细阐述了一种计算性抗体设计方案,供用户轻松进行计算机辅助抗体设计。首先,如果没有结构信息可用,将应用 Rosetta web 服务器生成查询抗体的 3D 结构。然后,当结合信息未知时,将使用两步对接来识别抗体-抗原复合物的结合构象。ClusPro 将首先用于进行全局对接,而 SnugDock 将用于局部对接。其次,基于预测的结合构象,将进行计算性丙氨酸扫描以预测潜在的热点(或关键残基)。最后,将使用计算亲和力成熟方案来修饰抗体结构,理论上增加其亲和力和稳定性,这将在未来通过生物测定进一步验证。作为概念验证,我们重新设计了抗体 D44.1,并将其与之前报道的数据进行比较,以验证 IsAb 方案。为了进一步说明我们提出的方案,我们使用了 PD-1 检查点抑制剂 cemiplimab 抗体作为示例,展示了一个逐步的教程。