Rationale-Based Engineering of a Potent Long-Acting FGF21 Analog for the Treatment of Type 2 Diabetes
Fibroblast growth factor 21 (FGF21) is a promising drug candidate for the treatment of type 2 diabetes. However, the use of wild type native FGF21 is challenging due to several limitations. Among these are its short half-life, its susceptibility to in vivo proteolytic degradation and its propensity to in vitro aggregation. We here describe a rationale-based protein engineering approach to generate a potent long-acting FGF21 analog with improved resistance to proteolysis and aggregation. A recombinant Fc-FGF21 fusion protein was constructed by fusing the Fc domain of human IgG1 to the N-terminus of human mature FGF21 via a linker peptide. The Fc positioned at the N-terminus was determined to be superior to the C-terminus as the N-terminal Fc fusion retained the βKlotho binding affinity and the in vitro and in vivo potency similar to native FGF21. Two specific point mutations were introduced into FGF21. The leucine to arginine substitution at position 98 (L98R) suppressed FGF21 aggregation at high concentrations and elevated temperatures. The proline to glycine replacement at position 171 (P171G) eliminated a site-specific proteolytic cleavage of FGF21 identified in mice and cynomolgus monkeys. The derived Fc-FGF21(RG) molecule demonstrated a significantly improved circulating half-life while maintaining the in vitro activity similar to that of wild type protein. The half-life of Fc-FGF21(RG) was 11 h in mice and 30 h in monkeys as compared to 1-2 h for native FGF21 or Fc-FGF21 wild type. A single administration of Fc-FGF21(RG) in diabetic mice resulted in a sustained reduction in blood glucose levels and body weight gains up to 5-7 days, whereas the efficacy of FGF21 or Fc-FGF21 lasted only for 1 day. In summary, we engineered a potent and efficacious long-acting FGF21 analog with a favorable pharmaceutical property for potential clinical development.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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