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利用蛋白酶底物特异性筛选在非天然氨基酸选择性蛋白酶抑制剂的合理设计中的应用:HGFA、matriptase 和 hepsin 的应用。

Use of protease substrate specificity screening in the rational design of selective protease inhibitors with unnatural amino acids: Application to HGFA, matriptase, and hepsin.

机构信息

Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri, USA.

Division of Chemical Biology and Bioimaging, Department of Chemistry, Wroclaw University of Science and Technology, Wroclaw, Poland.

出版信息

Protein Sci. 2024 Aug;33(8):e5110. doi: 10.1002/pro.5110.

Abstract

Inhibition of the proteolytic processing of hepatocyte growth factor (HGF) and macrophage stimulating protein (MSP) is an attractive approach for the drug discovery of novel anticancer therapeutics which prevent tumor progression and metastasis. Here, we utilized an improved and expanded version of positional scanning of substrate combinatorial libraries (PS-SCL) technique called HyCoSuL to optimize peptidomimetic inhibitors of the HGF/MSP activating serine proteases, HGFA, matriptase, and hepsin. These inhibitors have an electrophilic ketone serine trapping warhead and thus form a reversible covalent bond to the protease. We demonstrate that by varying the P2, P3, and P4 positions of the inhibitor with unnatural amino acids based on the protease substrate preferences learned from HyCoSuL, we can predictably modify the potency and selectivity of the inhibitor. We identified the tetrapeptide JH-1144 (8) as a single digit nM inhibitor of HGFA, matriptase and hepsin with excellent selectivity over Factor Xa and thrombin. These unnatural peptides have increased metabolic stability relative to natural peptides of similar structure. The tripeptide inhibitor PK-1-89 (2) has excellent pharmacokinetics in mice with good compound exposure out to 24 h. In addition, we obtained an X-ray structure of the inhibitor MM1132 (15) bound to matriptase revealing an interesting binding conformation useful for future inhibitor design.

摘要

抑制肝细胞生长因子 (HGF) 和巨噬细胞刺激蛋白 (MSP) 的蛋白水解加工是一种有吸引力的方法,可以用于发现新的抗癌治疗药物,以防止肿瘤的进展和转移。在这里,我们利用改进和扩展的底物组合文库定位扫描 (PS-SCL) 技术,即 HyCoSuL,来优化 HGF/MSP 激活丝氨酸蛋白酶 HGFA、matriptase 和 hepsin 的肽模拟抑制剂。这些抑制剂具有亲电酮丝氨酸捕获弹头,因此与蛋白酶形成可逆的共价键。我们证明,通过根据 HyCoSuL 从蛋白酶底物偏好中学习到的,在抑制剂的 P2、P3 和 P4 位置上改变基于非天然氨基酸的位置,可以可预测地修饰抑制剂的效力和选择性。我们确定了四肽 JH-1144 (8) 是 HGFA、matriptase 和 hepsin 的单位数 nM 抑制剂,对因子 Xa 和凝血酶具有极好的选择性。与类似结构的天然肽相比,这些非天然肽具有更高的代谢稳定性。三肽抑制剂 PK-1-89 (2) 在小鼠中具有出色的药代动力学特性,化合物暴露时间可长达 24 小时。此外,我们获得了抑制剂 MM1132 (15) 与 matriptase 结合的 X 射线结构,揭示了一种有趣的结合构象,可用于未来的抑制剂设计。

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