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EpiSweep: Computationally-driven Reengineering of Therapeutic Proteins to Reduce immunogenicity while Maintaining Function

机译:EpiSweep:计算驱动的治疗性蛋白质改造以降低免疫原性同时保持功能

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摘要

Therapeutic proteins are yielding ever more advanced and efficacious new drugs, but the biological origins of these highly effective therapeutics renders them subject to immune surveillance within the patient’s body. When recognized by the immune system as a foreign agent, protein drugs elicit a coordinated response that can manifest a range of clinical complications including rapid drug clearance, loss of functionality and efficacy, delayed infusion-like allergic reactions, more serious anaphylactic shock, and even induced auto-immunity. It is thus often necessary to deimmunize an exogenous protein in order to enable its clinical application; critically, the deimmunization process must also maintain the desired therapeutic activity.To meet the growing need for effective, efficient, and broadly applicable protein deimmunization technologies, we have developed the EpiSweep suite of protein design algorithms. EpiSweep seamlessly integrates computational prediction of immunogenic T cell epitopes with sequence- or structure- based assessment of the impacts of mutations on protein stability and function, in order to select combinations of mutations that make Pareto optimal trade-offs between the competing goals of low immunogenicity and high-level function. The methods are applicable both to the design of individual functionally deimmunized variants as well as the design of combinatorial libraries enriched in functionally deimmunized variants. After validating EpiSweep in a series of retrospective case studies providing comparisons to conventional approaches to T cell epitope deletion, we have experimentally demonstrated it to be highly effective in prospective application to deimmunization of a number of different therapeutic candidates. We conclude that our broadly applicable computational protein design algorithms guide the engineer towards the most promising deimmunized therapeutic candidates, and thereby have the potential to accelerate development of new protein drugs by shortening time frames and improving hit rates.
机译:治疗性蛋白质正在产生越来越先进和有效的新药,但是这些高效治疗剂的生物学起源使它们在患者体内受到免疫监视。当被免疫系统识别为异物时,蛋白药物会引起协同反应,可表现出一系列临床并发症,包括快速清除药物,功能和功效丧失,输液样变态反应延迟,更严重的过敏性休克,甚至诱导自身免疫。因此,经常有必要对一种外源蛋白质进行免疫处理,以使其能够临床应用。至关重要的是,脱免疫过程还必须保持所需的治疗活性。为了满足对有效,高效且广泛适用的蛋白质脱免疫技术不断增长的需求,我们开发了EpiSweep蛋白质设计算法套件。 EpiSweep将免疫原性T细胞抗原决定簇的计算预测与基于序列或结构的突变对蛋白质稳定性和功能影响的评估无缝集成在一起,以选择能够使Pareto在低免疫原性竞争目标之间达到最佳平衡的突变组合和高级功能。该方法既可用于单个功能性去免疫的变体的设计,又可用于富含功能性去免疫的变体的组合文库的设计。在一系列回顾性案例研究中对EpiSweep进行了验证后,提供了与T细胞表位缺失的常规方法进行比较的结果,我们通过实验证明了它在前瞻性应用到许多不同治疗候选者的去免疫中非常有效。我们得出的结论是,我们广泛适用的计算蛋白质设计算法可指导工程师朝最有希望的脱免疫治疗候选药物方向发展,从而有可能通过缩短时间框架和提高命中率来加速新蛋白质药物的开发。

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