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首页> 外文期刊>PLoS Computational Biology >Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)
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Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

机译:化学信息学辅助的肿瘤坏死因子(TNF)和NF-κB配体受体激活剂(RANKL)的小分子蛋白-蛋白质相互作用(PPI)双重抑制剂的发现

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We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure–based with ligand–based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.
机译:我们介绍了一种计算机药物开发管道,该管道已开发并应用于小分子蛋白质-蛋白质相互作用(PPI)化合物的识别和虚拟筛选,这些化合物通过三聚化界面充当TNF和RANKL的双重抑制剂。通过使用文献中最大的已知TNF抑制剂组合(2481个小分子),将基于结构的建模与基于配体的建模相结合,开发了管线的化学信息学部分。为了促进虚拟筛选,可以在以下网址免费获得共识预测模型:http://enalos.insilicotox.com/TNFPubChem/。因此,我们生成了9个小分子的优先列表,作为直接抑制TNF功能的候选对象。这些化合物的体外评估导致选择了两个小分子,它们可作为有效的TNF功能直接抑制剂,其IC50值可与先前描述的直接抑制剂(SPD304)相比,但毒性显着降低。这些分子也被鉴定为RANKL抑制剂,并在体外就第二种功能进行了验证。证实了这两种化合物对TNF和RANKL的直接结合,以及它们抑制生物活性三聚体形式的能力。还对每种蛋白质中的两个小分子进行了分子动力学计算,以进一步了解控制TNF和RANKL复合物形成的相互作用。据我们所知,这些化合物,即T8和T23,构成TNF和RANKL双重小分子直接功能抑制剂的第二个和第三个已公开的实例,并且可以用作开发炎症和自身免疫性疾病新疗法的先导化合物。

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