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Ligand- and Structure-based Virtual Screening Studies for the Discovery of Selective Inhibitors

机译:基于配体和基于结构的虚拟筛选研究,用于发现选择性抑制剂

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New drug design research using computer studies the relationship between 2D/3D quantitative structure and activity of target protein, derives pharmacophore model, which is essential for pharmacological activity that substrate should have, proceed screening to select the optimal inhibitor. Computer-aided drug design (CADD) studies are divided into structure- and ligand-based drug design. Structure-based drug design is to design a pharmacophore model for amino acid residues in active sites based on the 3D structure of the target protein under study. Ligand-based drug design predicts the activity of a new candidate compound by designing a pharmacophore model and a quantitative structure-activity relationship model using information of compounds known to be active against a target protein. In this study, selective inhibitors were designed using both methods. Ligand-based pharmacophore model consisting of ring aromatic, positive ionizable, negative ionizable, and hydrogen bonding receptors were generated from known active inhibitors. In addition, by analyzed the binding modes of known target proteins and ligands, we generated a structure-based pharmacophore model with the addition of hydrogen bonding donors. To increase bioavailability from a total of 1,890,602 commercial drug candidates databases, Lipinski's rule of five and ADMET analysis were used to filter 178,161 chemical compounds for virtual screening. After that, 20 selective inhibitors were finally selected through the process of selecting compounds with a fit value of 3.54 or higher and eliminating duplication.
机译:新药物设计研究使用计算机研究了2D / 3D定量结构与靶蛋白的活动的关系,衍生出药物学型,这对于基材应该具有的药理活性至关重要,进行筛选以选择最佳抑制剂。计算机辅助药物设计(CADD)研究分为结构和配体的药物设计。基于结构的药物设计是基于研究下的靶蛋白的3D结构设计活性位点中氨基酸残基的药物团模型。基于配体的药物设计通过使用已知对靶蛋白有效的化合物的信息来设计药物化学模型和定量结构 - 活性关系模型来预测新候选化合物的活性。在该研究中,使用两种方法设计了选择性抑制剂。由Reng芳族,正电离,负电离和氢键受体组成的基于LigAnd的药物模型是由已知的活性抑制剂产生的。另外,通过分析已知靶蛋白和配体的结合模式,我们通过添加氢键供体产生基于结构的药物模型。为了从总共1,890,602个商业药物候选数据库增加生物利用度,Lipinski的五个和呼气额度分析的规则用于过滤178,161个化学化合物进行虚拟筛选。之后,通过选择拟合值为3.54或更高的化合物或更高的化合物来选择20个选择性抑制剂。

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