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设计环延伸后进行组合筛选可赋予广谱基质金属蛋白酶抑制剂高特异性。

Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix MetalloproteinaseInhibitor.

机构信息

Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Israel.

Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Jacksonville, Florida, USA; Paracelsus Medical University, Salzburg, Austria.

出版信息

J Mol Biol. 2023 Jul 1;435(13):168095. doi: 10.1016/j.jmb.2023.168095. Epub 2023 Apr 15.

DOI:10.1016/j.jmb.2023.168095
PMID:37068580
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10312305/
Abstract

Matrix metalloproteinases (MMPs) are key drivers of various diseases, including cancer. Development of probes and drugs capable of selectively inhibiting the individual members of the large MMP family remains a persistent challenge. The inhibitory N-terminal domain of tissue inhibitor of metalloproteinases-2 (N-TIMP2), a natural broad MMP inhibitor, can provide a scaffold for protein engineering to create more selective MMP inhibitors. Here, we pursued a unique approach harnessing both computational design and combinatorial screening to confer high binding specificity toward a target MMP in preference to an anti-target MMP. We designed a loop extension of N-TIMP2 to allow new interactions with the non-conserved MMP surface and generated an efficient focused library for yeast surface display, which was then screened for high binding to the target MMP-14 and low binding to anti-target MMP-3. Deep sequencing analysis identified the most promising variants, which were expressed, purified, and tested for selectivity of inhibition. Our best N-TIMP2 variant exhibited 29 pM binding affinity to MMP-14 and 2.4 µM affinity to MMP-3, revealing 7500-fold greater specificity than WT N-TIMP2. High-confidence structural models were obtained by including NGS data in the AlphaFold multiple sequence alignment. The modeling together with experimental mutagenesis validated our design predictions, demonstrating that the loop extension packs tightly against non-conserved residues on MMP-14 and clashes with MMP-3. This study demonstrates how introduction of loop extensions in a manner guided by target protein conservation data and loop design can offer an attractive strategy to achieve specificity in design of protein ligands.

摘要

基质金属蛋白酶(MMPs)是多种疾病的关键驱动因素,包括癌症。开发能够选择性抑制大型 MMP 家族中各个成员的探针和药物仍然是一个持续的挑战。组织金属蛋白酶抑制剂-2(TIMP2)的抑制性 N 端结构域是一种天然的广谱 MMP 抑制剂,它可以为蛋白质工程提供一个支架,以创造更具选择性的 MMP 抑制剂。在这里,我们采用了一种独特的方法,利用计算设计和组合筛选来赋予针对目标 MMP 的高结合特异性,而不是针对抗目标 MMP 的结合特异性。我们设计了一个 TIMP2 的环延伸结构,以允许与非保守的 MMP 表面进行新的相互作用,并生成了一个用于酵母表面展示的高效聚焦文库,然后对其进行筛选,以实现与目标 MMP-14 的高结合和与抗目标 MMP-3 的低结合。深度测序分析确定了最有前途的变体,这些变体被表达、纯化,并测试其抑制的选择性。我们最好的 TIMP2 变体对 MMP-14 的结合亲和力为 29 pM,对 MMP-3 的亲和力为 2.4 μM,与 WT TIMP2 相比,特异性提高了 7500 倍。通过将 NGS 数据纳入 AlphaFold 多序列比对,获得了高可信度的结构模型。建模与实验性突变验证了我们的设计预测,表明环延伸结构紧密地与 MMP-14 上的非保守残基结合,并与 MMP-3 发生冲突。这项研究表明,如何在目标蛋白保守性数据和环设计的指导下引入环延伸结构,可以为设计蛋白配体的特异性提供一种有吸引力的策略。

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本文引用的文献

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Biomolecules. 2024 Sep 20;14(9):1187. doi: 10.3390/biom14091187.
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Mirror-Image Random Nonstandard Peptides Integrated Discovery (MI-RaPID) Technology Yields Highly Stable and Selective Macrocyclic Peptide Inhibitors for Matrix Metallopeptidase 7.镜像随机非标准肽整合发现(MI-RaPID)技术产生了用于基质金属肽酶7的高度稳定且选择性的大环肽抑制剂。
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