Combining biophysical analysis and computational methods to understand critical molecular attributes

背景和影响：新的抗体和新的形式如双特异性抗体继续在高度依赖于分子序列和结构的下游加工和配制中提出挑战。关键的挑战行为包括聚集、颗粒形成、凝胶化和应力导致的粘度增加。此类应力可包括升高的温度、增加的蛋白质浓度、硅油或其他包装组分的存在，或将制剂稀释到输液袋中。希望增加对影响其在DSP、制剂和最终给药步骤中的行为的关键分子属性的理解。这最终将使这些财产能够在发展的早期阶段就设计出来。该项目的目的是探索生物物理分析方法与机器学习/统计分析的结合，以及全原子分子动力学模拟和分子对接方法，以深入了解蛋白质聚集的分子属性和潜在机制，研究方法：包括将研究的工程和物理科学方面的新知识或新技术该项目将与Kyumab/Sanofi合作，定义一个生物物理分析方法平台，以确定一系列分子变体的分子制剂。然后将其用于DoE驱动的制剂筛选，在强制降解条件下评估Tm、聚集、粘度和凝胶化效应。在强制降解条件下，还将对选定的生物-缓冲液-辅料条件进行最先进的MD模拟和分子对接，然后使用统计和ML分析将从MD模拟、对接和生物物理测量中获得的分子特征和性质与各强制降解条件（包括生产条件）下的性能联系起来。因此，该项目将产生关于蛋白质溶液稳定性特征的新知识，并能够快速选择最佳配方和可制造的分子变体。它还将培养学生的数字技能。该项目直接与EPSRC未来制造主题保持一致。

Context & impact: New antibodies and novel formats such as bispecifics continue to pose challenges in downstream processing and formulation that are highly dependent on molecular sequence and structure. Key challenge behaviours include aggregation, particle formation, gelation and increased viscosity, as a result of stresses. Such stresses can include elevated temperature, increased protein concentration, the presence of silicone oil or other packing components, or the dilution of formulations into infusion bags. It is desirable to gain increased understanding of the critical molecular attributes that influence their behaviours in DSP, formulation and final drug administration steps. This would ultimately enable such properties to be engineered out an early stage of development.Aims and objectives: The aim of this project will be to explore the combination of biophysical analysis approaches with the use of machine-learning / statistical analyses, as well as all-atom molecular dynamics simulations, and molecular docking approaches to gain insights into the molecular attributes and underlying mechanisms of protein aggregation, viscosity and gelation, particularly at high protein concentrations, elevated temperature, and in the presence of tungsten and silicone oil.Research methodology: including new knowledge or techniques in engineering and physical sciences that will be investigated The project will collaborate with Kymab/Sanofi to define a platform of biophysical analytical approaches to characterise molecular formulations for a range of molecular variants. This will then be used in a DoE-driven formulation screen, assessed for Tm, aggregation, viscosity and gelation effects, under stress conditions. State of the art MD simulations and molecular docking will also be performed for selected biologic-buffer-excipient conditions, under stress conditions.Statistical and ML analyses will then be used to link molecular features and properties obtained from MD simulations, docking, and biophysical measurements, with the performance under each stress condition, including manufacturing conditions. Thus, the project will generate new knowledge in the characteristics of protein solutions that govern stability, and enable the rapid selection of optimal formulations and manufacturable molecular variants. It will also train the student in digital skills. The project is aligned directly to the EPSRC Manufacturing the Future theme.