Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (M.Y., W.Z., J.T.M., M.Z.); School of Pharmacy and Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin (B.C., L.L.); School of Life Sciences, Tianjin University, Nankai, Tianjin, People's Republic of China (L.L.); and MassDefect Technologies, Princeton, New Jersey (M.Z.).
Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (M.Y., W.Z., J.T.M., M.Z.); School of Pharmacy and Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin (B.C., L.L.); School of Life Sciences, Tianjin University, Nankai, Tianjin, People's Republic of China (L.L.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
Drug Metab Dispos. 2018 Apr;46(4):451-457. doi: 10.1124/dmd.117.077792. Epub 2018 Jan 31.
Therapeutic biologics have become a fast-growing segment within the pharmaceutical industry during the past 3 decades. Although the metabolism of biologics is more predictable than small molecule drugs, biotransformation can significantly affect the activity of biologics. Unfortunately, there are only a limited number of published studies on the biotransformation of biologics, most of which are focused on one or a few types of modifications. In this study, an untargeted LC-MS-based differential analysis approach was developed to rapidly and precisely determine the universal biotransformation profile of biologics with the assistance of bioinformatic tools. A human monoclonal antibody (mAb) was treated with -butyl hydroperoxide and compared with control mAb using a bottom-up proteomics approach. Thirty-seven types of post-translational modifications were identified, and 38 peptides were significantly changed. Moreover, although all modifications were screened and detected, only the ones related to the treatment process were revealed by differential analysis. Other modifications that coexist in both groups were filtered out. This novel analytical strategy can be effectively applied to study biotransformation-mediated protein modifications, which will streamline the process of biologic drug discovery and development.
在过去的 30 年中，治疗性生物制剂已成为制药行业中快速发展的一个领域。尽管生物制剂的代谢比小分子药物更可预测，但生物转化仍会显著影响生物制剂的活性。遗憾的是，目前仅有数量有限的关于生物制剂生物转化的已发表研究，其中大多数研究集中于一种或几种修饰类型。在本研究中，我们开发了一种基于 LC-MS 的非靶向差异分析方法，并借助生物信息学工具，快速而准确地确定生物制剂的通用生物转化特征。我们采用正丁酸过氧化氢氧化处理人源单克隆抗体（mAb），并通过自上而下的蛋白质组学方法与对照 mAb 进行比较。共鉴定出 37 种翻译后修饰类型，有 38 个肽段发生了显著变化。此外，虽然筛选并检测到了所有修饰类型，但差异分析仅揭示了与处理过程相关的修饰类型。其他在两组中共同存在的修饰类型被过滤掉了。这种新颖的分析策略可有效地应用于研究生物转化介导的蛋白质修饰，从而简化生物药物发现和开发的过程。
