Towards the automated optimisation of protein labelling methods

迈向蛋白质标记方法的自动化优化

• 批准号: 2440229
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2440229
• 关键词: Towards; automated; optimisation; protein; labelling

The objective of the project is to develop autonomous, self-optimising approaches towards modified biopharmaceuticals. This will be achieved by development of a liquid-handling system for reaction sampling, together with a software platform for automated analysis of reaction.Aims: 1. Develop a computational platform for automated deconvolution, integration and kinetic analysis of MS-based protein-labelling data. 2. Develop a liquid-handling approach for automated reaction set-up and sampling of protein-labelling approaches. 3. Develop a computational approach to identify and optimise reaction conditions for automated reaction optimisation by linking aim 1 and 2. Methodology:The initial planned approach to reaction optimisation is to use solid-phase extraction approaches to automatically sample and prepare fixed-time reaction samples. These samples (in a 96-well plate format) will then be directly analysed via MS before automated deconvolution, integration and quantification. Reaction sample data will be automatically integrated into a software package for kinetic analysis and subsequent optimisation of reactions to obtain the highest quality product while using minimal reagent quantities. A range of protein modification reactions will be used, initially exemplified by the use of recently-developed peptide-ligase-based methodologies at the University. During the project, it is anticipated that the system will be applied to a variety of novel variant protein modification methods to exemplify the approach further. Potential Impact:The project will develop a generic platform technology for the optimisation of protein-small molecule conjugate production. The approach is designed to be agnostic to both the protein and small molecule target and will therefore be transferable to any new biopharmaceutical preparation method. Rapid optimisation using this approach will reduce both the costs of optimisation and also provide economic advantages in terms of tightly defining reaction parameters required for production as well as defining attributes which can be used as part of the product specification for IP purposes.

该项目的目标是开发自主的、自我优化的方法来改进生物制药。这将通过开发用于反应取样的液体处理系统以及用于反应自动分析的软件平台来实现。开发一个计算平台，用于基于MS的蛋白质标记数据的自动解卷积、积分和动力学分析。2.开发一种液体处理方法，用于蛋白质标记方法的自动反应设置和采样。3.通过连接目标1和目标2，开发一种计算方法来识别和优化自动化反应优化的反应条件。方法学：最初计划的反应优化方法是使用固相萃取方法自动采样和制备固定时间的反应样品。然后在自动去卷积、积分和定量之前，通过MS直接分析这些样品（96孔板格式）。反应样品数据将自动集成到一个软件包中，用于动力学分析和随后的反应优化，以获得最高质量的产品，同时使用最少的试剂量。将使用一系列蛋白质修饰反应，最初通过使用最近开发的基于肽连接酶的方法在大学举例说明。在该项目期间，预计该系统将应用于各种新的变体蛋白质修饰方法，以进一步验证该方法。潜在影响：该项目将开发一种通用平台技术，用于优化蛋白质-小分子缀合物的生产。该方法被设计为对蛋白质和小分子靶标都是不可知的，因此将可转移到任何新的生物制药制备方法中。使用这种方法的快速优化将降低优化成本，并且还在严格定义生产所需的反应参数以及定义可用作IP目的的产品规格的一部分的属性方面提供经济优势。