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针对 HIV-1 蛋白酶自加工的高通量药物发现和耐药性评估。

Targeting HIV-1 Protease Autoprocessing for High-throughput Drug Discovery and Drug Resistance Assessment.

机构信息

Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, Colorado, USA.

Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.

出版信息

Sci Rep. 2019 Jan 22;9(1):301. doi: 10.1038/s41598-018-36730-4.

Abstract

HIV-1 protease autoprocessing liberates the free mature protease from its Gag-Pol polyprotein precursor through a series of highly regulated autoproteolysis reactions. Herein, we report the development and validation (Z' ≥ 0.50) of a cell-based functional assay for high-throughput screening (HTS) of autoprocessing inhibitors using fusion precursors in combination with AlphaLISA (amplified luminescent proximity homogeneous assay ELISA). Through pilot screening of a collection of 130 known protease inhibitors, the AlphaLISA assay confirmed all 11 HIV protease inhibitors in the library capable of suppressing precursor autoprocessing at low micromolar concentrations. Meanwhile, other protease inhibitors had no impact on precursor autoprocessing. We next conducted HTS of ~23,000 compounds but found no positive hits. Such high selectivity is advantageous for large-scale HTS campaigns and as anticipated based on assay design because a positive hit needs simultaneously to be nontoxic, cell permeable, and inhibiting precursor autoprocessing. Furthermore, AlphaLISA quantification of fusion precursors carrying mutations known to cause resistance to HIV protease inhibitors faithfully recapitulated the reported resistance, suggesting that precursor autoprocessing is a critical step contributing to drug resistance. Taken together, this reported AlphaLISA platform will provide a useful tool for drug discovery targeting HIV-1 protease autoprocessing and for quantification of PI resistance.

摘要

HIV-1 蛋白酶自身切割通过一系列高度调控的自身切割反应将自由成熟蛋白酶从其 Gag-Pol 多蛋白前体中释放出来。在此,我们报告了一种基于细胞的高通量筛选 (HTS) 方法的开发和验证(Z' ≥ 0.50),该方法使用融合前体结合 AlphaLISA(放大的发光近同相分析 ELISA)用于自身切割抑制剂的筛选。通过对 130 种已知蛋白酶抑制剂的初步筛选,AlphaLISA 测定法证实了文库中所有 11 种 HIV 蛋白酶抑制剂均能以低微摩尔浓度抑制前体自身切割。同时,其他蛋白酶抑制剂对前体自身切割没有影响。接下来,我们对约 23,000 种化合物进行了 HTS,但没有发现阳性结果。这种高选择性有利于大规模 HTS 活动,并且根据测定设计进行了预期,因为阳性结果需要同时是非毒性的、细胞渗透性的并且抑制前体自身切割。此外,对携带已知导致 HIV 蛋白酶抑制剂耐药性突变的融合前体进行 AlphaLISA 定量能够忠实地再现报道的耐药性,这表明前体自身切割是导致耐药性的关键步骤。总之,该报告的 AlphaLISA 平台将为针对 HIV-1 蛋白酶自身切割的药物发现和 PI 耐药性的定量提供有用的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55cb/6343032/5333dfe59e17/41598_2018_36730_Fig1_HTML.jpg

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