Combining biophysical analysis and computational methods to understand critical molecular attributes

背景和影响：新的抗体和新形式，如双特异性抗体，继续在下游加工和配方中构成挑战，高度依赖于分子序列和结构。主要的挑战行为包括聚集、颗粒形成、凝胶化和由于应力而增加的粘度。这些压力可能包括温度升高，蛋白质浓度增加，硅油或其他包装成分的存在，或配方稀释到输液袋中。希望对影响其在DSP、配方和最终给药步骤中的行为的关键分子属性有更多的了解。这将最终使这些属性能够在开发的早期阶段被设计出来。目的和目标：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、全原子分子动力学模拟和分子对接方法的结合，以深入了解蛋白质聚集、粘度和凝胶的分子属性和潜在机制，特别是在高蛋白质浓度、高温、钨和硅油存在的情况下。该项目将与Kymab/赛诺菲合作，定义一个生物物理分析方法平台，以表征一系列分子变异的分子配方。然后将其用于doe驱动的配方筛选，评估应力条件下的Tm、聚集、粘度和凝胶效应。在压力条件下，最先进的MD模拟和分子对接也将在选定的生物缓冲赋形剂条件下进行。然后，统计和ML分析将用于将从MD模拟、对接和生物物理测量中获得的分子特征和特性与每种应力条件（包括制造条件）下的性能联系起来。因此，该项目将在控制稳定性的蛋白质溶液特性方面产生新的知识，并使快速选择最佳配方和可制造的分子变体成为可能。它还将训练学生的数字技能。该项目与EPSRC“制造未来”的主题直接一致。

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.