Lalaurie C J, Zhang C, Liu S M, Bunting K A, Dalby P A
Department of Biochemical Engineering, University College London, London, United Kingdom.
IPSEN Bioinnovation, 5th Floor, The Point, 37 North Wharf Road, London W2 1AF, United Kingdom.
Comput Biol Chem. 2024 Dec;113:108209. doi: 10.1016/j.compbiolchem.2024.108209. Epub 2024 Sep 10.
Fusion proteins have the potential to become the new norm for targeted therapeutic treatments. Highly specific payload delivery can be achieved by combining custom targeting moieties, such as V domains, with active parts of proteins that have a particular activity not naturally targeted to the intended cells. Conversely, novel drug products may make use of the highly specific targeting properties of naturally occurring proteins and combine them with custom payloads. When designing such a product, there is rarely a known structure for the final construct which makes it difficult to assess molecular behaviour that may ultimately impact therapeutic outcome. Considering the time and cost of expressing a construct, optimising the purification procedure, obtaining sufficient quantities for biophysical characterisation, and performing structural studies in vitro, there is an enormous benefit to conduct in silico studies ahead of wet lab work. By following a repeatable, streamlined, and fast workflow of molecular dynamics assessment, it is possible to eliminate low-performing candidates from costly experimental work. There are, however, many aspects to consider when designing a novel fusion protein and it is crucial not to overlook some elements. In this work, we suggest a set of user-friendly, open-source methods which can be used to screen fusion protein candidates from the sequence alone. We used the light chain and translocation domain of botulinum toxin A (BoNT/A) fused with a selected V domain, termed here LC-H-V, as a case study for a general approach to designing, modelling, and simulating fusion proteins. Its behaviour in silico correlated well with initial in vitro work, with SEC HPLC showing multiple protein states in solution and a dynamic protein shifting between these states over time without loss of material.
融合蛋白有潜力成为靶向治疗的新规范。通过将定制的靶向部分（如V结构域）与具有特定活性但并非天然靶向目标细胞的蛋白质活性部分相结合，可以实现高度特异性的有效载荷递送。相反，新型药物产品可以利用天然存在的蛋白质的高度特异性靶向特性，并将它们与定制的有效载荷相结合。在设计这样一种产品时，最终构建体的结构很少是已知的，这使得评估可能最终影响治疗效果的分子行为变得困难。考虑到表达构建体、优化纯化程序、获得足够数量用于生物物理表征以及在体外进行结构研究的时间和成本，在湿实验室工作之前进行计算机模拟研究有巨大的好处。通过遵循分子动力学评估的可重复、简化且快速的工作流程，可以从昂贵的实验工作中剔除表现不佳的候选物。然而，在设计新型融合蛋白时需要考虑很多方面，且绝不能忽视某些因素。在这项工作中，我们提出了一套用户友好的开源方法，可用于仅从序列筛选融合蛋白候选物。我们使用与选定的V结构域融合的肉毒杆菌毒素A（BoNT/A）的轻链和易位结构域（在此称为LC-H-V）作为设计、建模和模拟融合蛋白的通用方法的案例研究。其在计算机模拟中的行为与最初的体外工作良好相关，尺寸排阻高效液相色谱（SEC HPLC）显示溶液中有多种蛋白质状态，且随着时间推移，一种动态蛋白质在这些状态之间转换而无物质损失。
