设计和评估新型 IL-1RA 融合细胞因子,提高药代动力学和受体亲和力,更好地治疗炎症性疾病。

Anith Kumar Rajendran, Kalimuthu Karuppanan, Senthilkumar Palanisamy
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引用次数: 0

摘要

IL-1活性的延长与自身免疫性疾病有关,如类风湿关节炎、糖尿病和帕金森病,以及伤口愈合延迟。此外,在致病性感染期间,它可以导致细胞因子风暴。方法:通过关键抗炎分子白介素-1受体拮抗剂(IL-1RA)进行调节。IL-1RA作为诱饵蛋白,与白细胞介素-1受体(IL-1RI和IL-1RII)竞争结合,有效抵消白细胞介素-1 (IL-1)的活性。这种缺陷被市售重组IL-1RA Anakinra证实。现有药物的主要问题是它的药代动力学和与受体的结合亲和力较低,这需要经常给药。为了克服这些缺点,我们设计了一种新的融合蛋白,通过添加人类IgGI的Fc片段与IL-1RA融合,并在两者之间使用连接体,该设计旨在将蛋白质转运到n -糖基化途径。这些特征增加了蛋白质的药代动力学、溶解度和结合效率。由于该蛋白被设计为在真核系统中表达,为了了解所提出假设的可能性,我们使用基于机器学习的AlphaFold2来模拟蛋白质结构和分子模拟研究,以了解所设计蛋白质的功能完整性。结果:模拟结果表明,在21个氢键和7个盐桥的支持下,模拟的融合蛋白结构与受体有很好的结合,并且与MD模拟相比保持了结合的稳定性。结论:这些发现支持融合蛋白作为一种有前途和稳定的治疗候选者的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing and Evaluation of a Novel IL-1RA Fusion Cytokine to Enhance the Pharmacokinetics and Receptor Affinity for Better Therapeutic Intervention in Inflammatory Disorders.

Introduction: The extended IL-1 activity is implicated in autoimmune disorders, such as rheumatoid arthritis, diabetes mellitus, and Parkinson's disease, as well as delayed wound healing. Additionally, it can result in cytokine storms during pathogenic infections.

Methods: The regulation was carried out by Interleukin-1 receptor antagonist (IL-1RA), a key anti-inflammatory molecule. IL-1RA serves as a decoy protein that competes with Interleukin-1 receptors (IL-1RI and IL-1RII) for binding, effectively counteracting the activity of Interleukin- 1 (IL-1). The deficiency was substantiated by commercially available recombinant IL-1RA called Anakinra. The main problem with the existing drug is that it has less pharmacokinetics and reduced binding affinity to its receptor, which requires frequent administration of the drug. To overcome these drawbacks, we have designed a new fusion protein by adding an Fc fragment of Human IgGI fused with IL-1RA using a linker in between, and the design aimed to transport the protein into the N-glycosylation pathway. These characteristic features increase the pharmacokinetics, solubility, and binding efficiency of the protein. As the protein was designed to be expressed in a eukaryotic system, to understand the possibility of the proposed hypothesis, we used machine learning-based AlphaFold2 to model the protein structure and molecular simulation studies to understand the functional integrity of the designed protein.

Results: The in silico results showed that the modeled fusion protein structure has very good binding to its receptor with the support of 21 H bonds and 7 salt bridges and maintained the binding stability over the MD simulations.

Conclusion: These findings support fusion protein's potential as a promising and stable therapeutic candidate.

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