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， 科学家为小分子药物发现活动生产大量蛋白质， 开发蛋白质药物，研究蛋白质结构和功能。尽管研究人员 他们擅长生产具有已知基因序列的蛋白质，但对以下方面的知识完全不足： 蛋白质的翻译后修饰，无论是在重组表达过程中，还是当蛋白质 与内源性来源分离。蛋白质翻译后修饰的改变可以改变蛋白质的结构。 蛋白质从活性酶到死酶;他们可以改变蛋白质为基础的药物从挽救生命 分子到一个无效或更糟，危险的免疫原性;这些看似简单的“添加- 对蛋白质的”依赖“可以是决定蛋白质是否按设计发挥功能的定义特征。 表征蛋白质的PTM是识别疾病状态、调节蛋白质合成、调节蛋白质合成的必要前提。 结合和功能，并生产安全有效的蛋白质药物和疫苗。长期目标 我的研究计划的重点是加快蛋白质翻译后修饰（PTM）的分析， 使用这些分析工具来应对与健康有关的重大挑战，并广泛传播这项技术。 我们正在寻求这两个近期的进展，例如开发一个强大的解决方案，以量化异常 重组蛋白质中的二硫键，以及蛋白质合成方式的长期革命性变化， 分析，通过奠定将人工智能解决方案引入人工智能领域所需的基础设施， PTM分析。我们将在有意义的生物学问题的背景下开发和推出这些技术 如果没有蛋白质的PTM信息，就无法取得领域的进展。解决方案领域： 艾滋病毒疫苗设计、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.