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发现用于预防单克隆抗体自缔合的新型小分子化合物。

Discovering Novel Small Molecule Compound for Prevention of Monoclonal Antibody Self-Association.

作者信息

Lui Lok Hin, van der Walle Christopher F, Brocchini Steve, Velayudhan Ajoy

机构信息

UCL School of Pharmacy, University College London, London WC1N 1AX, UK.

Dosage Form Design and Development, R&D BioPharmaceutical Development, AstraZeneca, Aaron Klug Building, Granta Park, Cambridge CB21 6GH, UK.

出版信息

Antibodies (Basel). 2022 Jun 8;11(2):40. doi: 10.3390/antib11020040.

Abstract

Designing an antibody with the desired affinity to the antigen is challenging, often achieved by lengthening the hydrophobic CDRs, which can lead to aggregation and cause major hindrance to the development of successful biopharmaceutical products. Aggregation can cause immunogenicity, viscosity and stability issues affecting both the safety and quality of the product. As the hydrophobic residues on the CDR are required for direct binding to antigens, it is not always possible to substitute these residues for aggregation-reduction purposes. Therefore, discovery of specific excipients to prevent aggregation is highly desirable for formulation development. Here, we used a combination of in silico screening methods to identify aggregation-prone regions on an aggregation-prone therapeutic antibody. The most aggregation-prone region on the antibody was selected to conduct virtual screening of compounds that can bind to such regions and act as an aggregation breaker. The most promising excipient candidate was further studied alongside plain buffer formulations and formulations with trehalose using coarse-grained molecular dynamics (CGMD) simulations with MARTINI force field. Mean interaction value between two antibody molecules in each formulation was calculated based on 1024 replicates of 512 ns of such CGMD simulations. Corresponding formulations with an excipient:antibody ratio of 1:5 were compared experimentally by measuring the diffusion interaction parameter and accelerated stability studies. Although the compound with the highest affinity score did not show any additional protective effects compared with trehalose, this study proved using a combination of in silico tools can aid excipient design and formulation development.

摘要

设计出对抗原具有所需亲和力的抗体具有挑战性,通常通过延长疏水性互补决定区(CDR)来实现,这可能导致聚集,并对成功开发生物制药产品造成重大阻碍。聚集会引发免疫原性、粘度和稳定性问题,影响产品的安全性和质量。由于CDR上的疏水残基是直接与抗原结合所必需的,因此为了减少聚集而替换这些残基并不总是可行的。因此,发现特定的辅料以防止聚集对于制剂开发来说非常必要。在此,我们使用了多种计算机模拟筛选方法相结合,来识别一种易于聚集的治疗性抗体上的易于聚集区域。选择该抗体上最易于聚集的区域,对能够结合这些区域并充当聚集抑制剂的化合物进行虚拟筛选。使用MARTINI力场的粗粒度分子动力学(CGMD)模拟,进一步研究了最有前景的辅料候选物,以及与普通缓冲液制剂和含有海藻糖的制剂一起进行研究。基于此类512纳秒的CGMD模拟的1024次重复,计算了每种制剂中两个抗体分子之间的平均相互作用值。通过测量扩散相互作用参数并进行加速稳定性研究,对辅料与抗体比例为1:5的相应制剂进行了实验比较。尽管与海藻糖相比,亲和力得分最高的化合物没有显示出任何额外的保护作用,但这项研究证明,结合使用计算机模拟工具可以辅助辅料设计和制剂开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9988/9219649/bc75840c4cbc/antibodies-11-00040-g001.jpg

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