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基于结构的无偏向性和RNA聚焦文库虚拟筛选,以鉴定丙型肝炎病毒内部核糖体进入位点(HCV IRES)模型系统的新配体。

Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system.

作者信息

Kallert Elisabeth, Almena Rodriguez Laura, Husmann Jan-Åke, Blatt Kathrin, Kersten Christian

机构信息

Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany

Institute for Quantitative and Computational Biosciences, Johannes Gutenberg-University BioZentrum I, Hanns-Dieter-Hüsch-Weg 15 55128 Mainz Germany.

出版信息

RSC Med Chem. 2024 Mar 18;15(5):1527-1538. doi: 10.1039/d3md00696d. eCollection 2024 May 22.

Abstract

Targeting RNA including viral RNAs with small molecules is an emerging field. The hepatitis C virus internal ribosome entry site (HCV IRES) is a potential target for translation inhibitor development to raise drug resistance mutation preparedness. Using RNA-focused and unbiased molecule libraries, a structure-based virtual screening (VS) by molecular docking and pharmacophore analysis was performed against the HCV IRES subdomain IIa. VS hits were validated by a microscale thermophoresis (MST) binding assay and a Förster resonance energy transfer (FRET) assay elucidating ligand-induced conformational changes. Ten hit molecules were identified with potencies in the high to medium micromolar range proving the suitability of structure-based virtual screenings against RNA-targets. Hit compounds from a 2-guanidino-quinazoline series, like the strongest binder, compound 8b with an EC of 61 μM, show low molecular weight, moderate lipophilicity and reduced basicity compared to previously reported IRES ligands. Therefore, it can be considered as a potential starting point for further optimization by chemical derivatization.

摘要

用小分子靶向包括病毒RNA在内的RNA是一个新兴领域。丙型肝炎病毒内部核糖体进入位点(HCV IRES)是开发翻译抑制剂以提高耐药性突变准备的潜在靶点。利用聚焦RNA且无偏向性的分子文库,通过分子对接和药效团分析对HCV IRES亚结构域IIa进行了基于结构的虚拟筛选(VS)。通过微量热泳(MST)结合试验和荧光共振能量转移(FRET)试验验证VS筛选出的命中分子,后者可阐明配体诱导的构象变化。鉴定出了10种命中分子,其效力在高微摩尔到低微摩尔范围内,证明了针对RNA靶点的基于结构的虚拟筛选的适用性。来自2-胍基喹唑啉系列的命中化合物,如最强结合剂、EC为61 μM的化合物8b,与先前报道的IRES配体相比,分子量低、亲脂性适中且碱性降低。因此,它可被视为通过化学衍生进行进一步优化的潜在起点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c8e/11110755/f1c10c19ee29/d3md00696d-f1.jpg

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