首页> 外文期刊>European Journal of Medicinal Chemistry: Chimie Therapeutique >Docking and 3D-QSAR (quantitative structure activity relationship) studies of flavones, the potent inhibitors of p-glycoprotein targeting the nucleotide binding domain.
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Docking and 3D-QSAR (quantitative structure activity relationship) studies of flavones, the potent inhibitors of p-glycoprotein targeting the nucleotide binding domain.

机译:黄酮的对接和3D-QSAR(定量结构活性关系)研究,黄酮是靶向核苷酸结合域的p-糖蛋白的有效抑制剂。

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摘要

In order to explore the interactions between flavones and P-gp, in silico methodologies such as docking and 3D-QSAR were performed. CoMFA and CoMSIA analyses were done using ligand based and receptor guided alignment schemes. Validation statistics include leave-one-out cross-validated R(2) (q(2)), internal prediction parameter by progressive scrambling (Q(*2)), external prediction with test set. They show that models derived from this study are quite robust. Ligand based CoMFA (q(2) = 0.747, Q(*2) = 0.639, r(pred)(2)=0.802) and CoMSIA model (q(2) = 0.810, Q(*2) = 0.676, r(pred)(2)=0.785) were developed using atom by atom matching. Receptor guided CoMFA (q(2) = 0.712, Q(*2) = 0.497, r(pred)(2) = 0.841) and for CoMSIA (q(2) = 0.805, Q(*2) = 0.589, r(pred)(2) = 0.937) models were developed by docking of highly active flavone into the proposed NBD (nucleotide binding domain) of P-gp. The 3D-QSAR models generated here predicted that hydrophobic and steric parameters are important for activity toward P-gp. Our studies indicate the important amino acid in NBD crucial for binding in accordance with the previous results. This site forms a hydrophobic site. Since flavonoids have potential without toxicity, we propose to inspect this hydrophobic site including Asn1043 and Asp1049 should be considered for future inhibitor design.
机译:为了探索黄酮与P-gp之间的相互作用,进行了计算机方法学,例如对接和3D-QSAR。使用基于配体和受体指导的比对方案完成了CoMFA和CoMSIA分析。验证统计信息包括留一法交叉验证的R(2)(q(2)),通过渐进加扰的内部预测参数(Q(* 2)),带有测试集的外部预测。他们表明,从这项研究得出的模型非常可靠。基于配体的CoMFA(q(2)= 0.747,Q(* 2)= 0.639,r(pred)(2)= 0.802)和CoMSIA模型(q(2)= 0.810,Q(* 2)= 0.676,r( pred)(2)= 0.785)是使用原子逐原子匹配开发的。受体引导的CoMFA(q(2)= 0.712,Q(* 2)= 0.497,r(pred)(2)= 0.841)和CoMSIA(q(2)= 0.805,Q(* 2)= 0.589,r( pred)(2)= 0.937)模型是通过将高活性黄酮对接至拟议的P-gp NBD(核苷酸结合域)而开发的。此处生成的3D-QSAR模型预测,疏水性和空间参数对于P-gp的活性至关重要。我们的研究表明,根据先前的结果,NBD中的重要氨基酸对于结合至关重要。该位点形成疏水位点。由于类黄酮具有潜在的毒性,因此我们建议检查包括Asn1043和Asp1049在内的疏水位点,以便将来设计抑制剂。

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