Development of a computational glycan engineering tool for biologics manufacturers

生物制剂目前是最成功的一类药物，2018年上市的前10种药物中有7种海陵这类药物，总收入为600亿美元。这些蛋白质药物中的大多数是糖基化的，这意味着它们被称为聚糖的碳水化合物链修饰。聚糖的存在导致高度的变异性，这源于构建聚糖的生物合成机制所促进的固有异质性。变异性是这些药物的一个问题，因为具有不同聚糖结构的蛋白质连接到它们显示功能差异。因此，生物制剂总是作为具有不同效率的药物分子的混合物出售，并且每批生物制剂可以显著不同。这种批次间的差异，特别是无法系统地控制它，确实削弱了制药工业开发新生物制剂的能力，特别是产生竞争性的非专利产品。聚糖异质性不是随机的，而是通过高尔基体中大量生物合成酶的组织以非直观的方式控制的。通过BBSRC IB催化剂项目和BBSRC博士培训合作伙伴资助的博士项目，我们最近开发了一种计算模型，可以有效地描述高尔基体中糖基化酶的组织。在一项原理证明理论研究（由BBSRC影响加速器奖资助）中，我们还能够展示如何使用这种计算工具来预测酶水平需要如何改变以改变细胞系产生的聚糖结构。这种计算工具可用于告知公司如何改变其生产细胞系，以产生具有更有益聚糖库的生物制剂。拟议的研究将验证使用这种建模工具来预测哪些聚糖生物合成酶在生物生产细胞系中过量生产，并验证这种干预确实将聚糖库转移到所需的聚糖结构范围。这项工作将与工业合作伙伴一起进行，以确保我们的验证是在具有工业相关性的实例上进行的。将使用合作伙伴生产的三种聚糖复杂性不断增加的生物制剂。在对高尔基体组成进行建模后，我们的合作伙伴报告了其产品中的聚糖，该模型将受到一组更理想的聚糖的挑战。预测的酶变化将用于在约克制造合成DNA结构，然后将其转移到公司的生产细胞中。将使用蛋白质和聚糖分析工具（包括蛋白质印迹法和质谱法）研究酶水平的变化以及新的聚糖库。将实验获得的结果与计算预测的结果进行比较，以评估生物聚糖状态工程的计算建模工具的效力。一旦完全开发和验证，我们打算为其他制药公司定制这种计算工具，因此将在项目过程中与其中一些公司举行会议，以确定他们的具体需求。

Biologics are currently the most successful class of pharmaceuticals, with seven of the top 10 drugs marketed in 2018 hailing from this class and grossing a total of $60 bn. The majority of these protein drugs are glycosylated, meaning they are decorated with carbohydrate chains also called glycans. The presence of glycans causes a high degree of variability, which stems from the inherent heterogeneity fostered by the biosynthetic machinery that builds glycans. Variability is a problem for these drugs because proteins with different glycan structures attached to them display functional differences. Consequently, biologics are always sold as a mixture of drug molecules with varying efficiency, and each batch of a biologic can be significantly different. Such batch-to-batch variation, and in particular the inability to systematically control it, does curtail the ability of the pharmaceutical industry to develop new biologics and in particular to generate competing off-patent products.Glycan heterogeneity is not random, but rather controlled in a non-intuitive way by the organisation of a large number of biosynthetic enzymes in the Golgi apparatus. Through a BBSRC IB catalyst project and a BBSRC Doctoral Training Partnership-funded PhD project, we have recently developed a computational model that can efficiently describe the organisation of glycosylation enzymes in the Golgi. In a proof-of-principle theoretical study (funded by a BBSRC impact accelerator award) we were also able to show how to use this computational tool for predicting how enzyme levels would need to be altered to shift the set of glycan structures produced by a cell line. This computational tool could be used to inform companies how to alter their production cell lines to generate biologics with more beneficial glycan repertoires. The proposed study will validate the use of this modelling tool for predicting which glycan biosynthetic enzymes to overproduce in a biologic-producing cell line, and to verify that this intervention indeed shifts the glycan repertoire to the desired range of glycan structures.The work will be carried out with an industrial partner to ensure that our validation is performed on examples with industrial relevance. Three biologics with increasing glycan complexity, which have been produced by the partner, will be used. Following modelling of the Golgi composition required for generating the glycans that our partner reports on its products, the model will be challenged with a more desirable set of glycans. The predicted change in enzymes will then be used to create synthetic DNA constructs in York, which can then be transferred into the production cells at the company. The alterations in enzyme levels as well as the new glycan repertoire will be investigated using protein and glycan analytical tools, including western blotting and mass spectrometry. The experimentally obtained results will be compared to those computationally predicted, to assess the potency of the computational modelling tool for the engineering of biologic glycan states. Once fully developed and validated, we intend to customize this computational tool for other pharmaceutical companies as well, and will therefore set up meetings with some of these during the course of the project to establish their specific needs.