Mass Spectrometry Measurements for Complex PTMs

摘要： 重组蛋白表达技术彻底改变了人类健康研究，使 科学家为小分子药物发现活动产生大量蛋白质，为 发展以蛋白质为基础的药物，并用于研究蛋白质结构和功能。然而，当研究人员正在 擅长制造具有已知遗传序列的蛋白质，他们完全不了解 蛋白质的翻译后修饰，无论是在重组表达期间还是在蛋白质被 从内源性来源分离出来的。蛋白质翻译后修饰的改变可以改变 从活性酶到死亡酶的蛋白质；他们可以改变以蛋白质为基础的药物，从挽救生命 分子到一种无效或更糟糕的分子，具有危险的免疫原性；这些看似简单的“添加- 蛋白质的“ONS”可以是决定蛋白质是否如设计的那样发挥功能的决定性特征。 鉴定蛋白质的PTM是鉴定疾病状态、调节蛋白质的必要前提 结合和发挥作用，生产安全有效的蛋白质类药物和疫苗。长期目标 我的研究计划的一部分是加快蛋白质翻译后修饰(PTM)的分析，以 使用这些分析工具来回答与健康相关的关键挑战，并广泛传播该技术。 我们正在追求这两个近期的进步，例如开发一个强大的解决方案来量化反常 重组蛋白质中的二硫键，以及蛋白质形成方式的长期革命性变化 通过奠定将人工智能解决方案带到 PTM分析。我们将在有意义的生物问题的背景下开发和推出这些技术 如果没有关于蛋白质的PTM的信息，领域的进步是不可能实现的。以下领域的解决方案 HIV疫苗设计、癌症治疗和抗体治疗将首先成为目标。

Abstract: Recombinant protein expression technology has revolutionized human health research, enabling scientists to generate large quantities of protein for small-molecule drug discovery campaigns, for the development of protein-based drugs, and for studying protein structure and function. Yet while researchers are adept at producing proteins with known genetic sequences, they possess entirely inadequate knowledge about the protein's post-translational modifications, both during recombinant expression and when the proteins are isolated from endogenous sources. Alterations in a protein's post-translational modifications can change the protein from an active enzyme to a dead one; they can change a protein-based drug from a life-saving molecule to one that is either ineffective or worse, dangerously immunogenic; these seemingly simple “add- ons” to proteins can be the defining features that determine whether the protein functions as designed or not. Characterizing proteins' PTMs is a necessary prerequisite for identifying disease states, modulating protein binding and function, and producing safe and effective protein-based drugs and vaccines. The long term goals of my research program are to expedite the analysis of post-translational modifications (PTMs) on proteins, to use these analytical tools to answer critical health-related challenges, and to widely distribute the technology. We are pursuing both near-term advancements, such as developing a robust solution to quantifying aberrant disulfide bonds in recombinant proteins, as well as long-range, revolutionary changes in the way proteins are analyzed, by laying the foundational infrastructure needed to bring artificial intelligence solutions to the field of PTM analysis. We will develop and launch these technologies in the context of meaningful biological problems where field advancements cannot be made without information about proteins' PTMs. Solutions in the fields of HIV vaccine design, cancer treatment, and antibody therapy will be targeted first.