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首页> 外文期刊>QSAR & combinatorial science >Exploring QSAR for the Inhibitory Activity of a Large Set of Aromatic/Heterocyclic Sulfonamides toward Four Different Isoenzymes of Carbonic Anhydrase
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Exploring QSAR for the Inhibitory Activity of a Large Set of Aromatic/Heterocyclic Sulfonamides toward Four Different Isoenzymes of Carbonic Anhydrase

机译:探索QSAR对大量芳香/杂环磺酰胺类化合物对碳酸酐酶的四种同工酶的抑制活性

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The Carbonic Anhydrase (CA) inhibitory activities of a large number of sulfonamide derivatives toward CA isoenzyme types I, II, IV, and IX were collected and then subjected to QSAR analyses. The dataset used consisted of 343 sulfonamide derivatives with 200 calculated descriptors. For each type of isoenzyme, a separate QSAR model was obtained using multiple linear regression analysis with stepwise selection of variables. The generalization, stability, and predictivity of the models were evaluated by leave-many-out cross-validation, using an external test set and chance correlation. All the obtained models represented high statistical quality and prediction ability with q~2 and R_P~2 greater than 0.80. The relative errors of prediction were lower than 5%. By the developed models, the ligand - receptor interactions involved in the binding of sulfonamides to different CA isoenzymes were discussed. For all types of isoenzymes, the topological indices represented significant impacts on the ligand-enzyme interactions. It was found that, for CAI, the acid-base properties play a significant role whereas for CAII the coulombic interactions are controlling factors. In addition, number of thiol functional groups exhibited significant negative effect on the binding of sulfonamides to CAII. For CAIV, the hydrogen bonding interactions were detected as a major factor. Finally, for the binding of sulfonamides to CAIX, the lipophilicity, and acid-base properties were selected as highly influential parameters. ,
机译:收集了大量磺酰胺衍生物对CA同工酶I,II,IV和IX的碳酸酐酶(CA)抑制活性,然后进行QSAR分析。使用的数据集由343个磺酰胺衍生物和200个计算的描述符组成。对于每种同工酶,使用多元线性回归分析并逐步选择变量来获得单独的QSAR模型。通过使用外部测试集和机会相关性,通过多点交叉验证对模型的泛化性,稳定性和可预测性进行了评估。所有获得的模型都具有较高的统计质量和预测能力,其中q〜2和R_P〜2大于0.80。预测的相对误差低于5%。通过已开发的模型,讨论了磺酰胺与不同CA同工酶结合所涉及的配体-受体相互作用。对于所有类型的同工酶,拓扑指数都表示对配体-酶相互作用的重大影响。发现对于CAI,酸碱性质起重要作用,而对于CAII,库仑相互作用是控制因素。此外,许多硫醇官能团对磺酰胺与CAII的结合表现出显着的负面影响。对于CAIV,检测到氢键相互作用是主要因素。最后,为了使磺酰胺与CAIX结合,选择了亲脂性和酸碱性质作为极具影响力的参数。 ,

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