B-Cell lymphoma 2 (BCL-2) regulates cell death in humans. In this study, combined multiscale in silico approaches and in vitro studies were employed. A small-molecule library that includes more than 210 000 compounds was used. The predicted therapeutic activity value (TAV) of the compounds in this library was computed with the binary cancer quantitative structure–activity relationships (QSAR) model. The molecules with a high calculated TAV were used in 26 individual toxicity QSAR models. As a result of this screening protocol, 288 nontoxic molecules with high predicted TAV were identified. These selected hits were then screened against the BCL-2 target protein using hybrid docking and molecular dynamics (MD) simulations. The interaction energies of identified compounds were compared with two known BCL-2 inhibitors. Then, the short MD simulations were carried out by initiating the best docking poses of 288 molecules. Average MM/GBSA energies were computed, and long MD simulations were employed to selected hits. The same calculations were also applied for two known BCL-2 inhibitors. Moreover, a five-site (AHRRR) structure-based pharmacophore model was constructed, and this model was used in the screening of the same database. On the basis of hybrid data-driven ligand identification study, final hits were selected and used in in vitro studies. Based on results of the time-resolved fluorescence resonance energy transfer (TR-FRET) analysis, further filtration was carried out for the U87-MG cell line tests. MTT cell proliferation assay analysis results showed that selected three potent compounds were significantly effective on glioma cells.

中文翻译：

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新型 BCL-2 抑制剂的硅混合和 TR-FRET 引导发现

B 细胞淋巴瘤 2 (BCL-2) 调节人类的细胞死亡。在这项研究中，结合多尺度的计算机方法和体外研究受雇。使用了一个包含超过 210 000 种化合物的小分子库。使用二元癌症定量构效关系 (QSAR) 模型计算了该文库中化合物的预测治疗活性值 (TAV)。具有高 TAV 计算值的分子被用于 26 个单独的毒性 QSAR 模型。作为该筛选方案的结果，鉴定了 288 个具有高预测 TAV 的无毒分子。然后使用混合对接和分子动力学 (MD) 模拟针对 BCL-2 靶蛋白筛选这些选定的命中。已鉴定化合物的相互作用能与两种已知的 BCL-2 抑制剂进行了比较。然后，通过启动 288 个分子的最佳对接姿势来进行短 MD 模拟。计算平均 MM/GBSA 能量，和长 MD 模拟用于选定的命中。同样的计算也适用于两种已知的 BCL-2 抑制剂。此外，构建了基于五位点（AHRRR）结构的药效团模型，并将该模型用于同一数据库的筛选。在混合数据驱动的配体识别研究的基础上，选择最终命中并用于体外研究。基于时间分辨荧光共振能量转移（TR-FRET）分析的结果，对U87-MG细胞系测试进行进一步过滤。MTT细胞增殖试验分析结果表明，选择的三种强效化合物对胶质瘤细胞有显着疗效。