中国仓鼠卵巢细胞
计算生物学
生物制药
计算机科学
过程(计算)
生物
生物信息学
化学
遗传学
生物化学
受体
操作系统
作者
Xuan Xu,Lan Wang,Gang Wu,Shengyuan Xu,Li Yang,Ning Sheng,Jinlan Zhang
标识
DOI:10.1021/acs.jproteome.5c00369
摘要
Host cell proteins (HCPs) are critical process-related impurities in biotherapeutics that threaten drug stability and safety. The substantial dynamic range (>5 orders of magnitude) between therapeutic proteins and residual HCPs often leads to difficulty in detecting high-risk species. Herein, we developed a novel strategy integrating data-dependent acquisition (DDA), parallel reaction monitoring (PRM), and multiple reaction monitoring (MRM) techniques to comprehensively profile and accurately quantify high-risk HCPs. We constructed a Chinese hamster ovary (CHO) cell spectral library by DDA that covers all potential HCPs present in downstream purification processes. Based on the constructed library, 38 reported high-risk HCPs were focused and their unique peptides and transitions were predicted. PRM and MRM were performed to cross-validate the existing high-risk HCPs in CHO cell samples, and 28 high-risk HCPs with 47 peptides and 141 transitions were validated. A new dynamic MRM (dMRM) method was established and validated to simultaneously quantify 28 high-risk HCPs. We applied this strategy to analyze five purified monoclonal antibody process samples, using the DDA method for comprehensive profiling of unknown HCPs and the dMRM method for rapid quantification of 28 known high-risk HCPs. Overall, this strategy enables thorough analysis of known and unknown HCPs, optimizing biopharmaceutical process development.
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