Pandya Akash, Howard Mark J, Zloh Mire, Dalby Paul A
Department of Biochemical Engineering, University College London, Gordon Street, London WC1E 7JE, UK.
School of Chemistry, University of Leeds, Leeds LS2 9JT, UK.
Pharmaceutics. 2018 Sep 21;10(4):165. doi: 10.3390/pharmaceutics10040165.
Protein-based therapeutics are considered to be one of the most important classes of pharmaceuticals on the market. The growing need to prolong stability of high protein concentrations in liquid form has proven to be challenging. Therefore, significant effort is being made to design formulations which can enable the storage of these highly concentrated protein therapies for up to 2 years. Currently, the excipient selection approach involves empirical high-throughput screening, but does not reveal details on aggregation mechanisms or the molecular-level effects of the formulations under storage conditions. Computational modelling approaches have the potential to elucidate such mechanisms, and rapidly screen in silico prior to experimental testing. Nuclear Magnetic Resonance (NMR) spectroscopy can also provide complementary insights into excipient⁻protein interactions. This review will highlight the underpinning principles of molecular modelling and NMR spectroscopy. It will also discuss the advancements in the applications of computational and NMR approaches in investigating excipient⁻protein interactions.
基于蛋白质的治疗药物被认为是市场上最重要的一类药物。事实证明，延长高浓度蛋白质液体形式稳定性的需求日益增长，这颇具挑战性。因此，人们正在付出巨大努力来设计能够将这些高浓度蛋白质疗法储存长达两年的制剂。目前，辅料选择方法涉及经验性高通量筛选，但并未揭示聚集机制的细节或储存条件下制剂的分子水平效应。计算建模方法有潜力阐明此类机制，并在实验测试之前进行快速的计算机模拟筛选。核磁共振（NMR）光谱也可以为辅料与蛋白质的相互作用提供补充见解。本综述将重点介绍分子建模和NMR光谱的基础原理。还将讨论计算和NMR方法在研究辅料与蛋白质相互作用方面应用的进展。
