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基于台湾中医药数据库,通过高性能筛选、结构及分子动力学分析来鉴定H1抑制剂。

High performance screening, structural and molecular dynamics analysis to identify H1 inhibitors from TCM Database@Taiwan.

作者信息

Chang Su-Sen, Huang Hung-Jin, Chen Calvin Yu-Chian

机构信息

Laboratory of Computational and Systems Biology, School of Chinese Medicine, China Medical University, Taichung 40402, Taiwan.

出版信息

Mol Biosyst. 2011 Dec;7(12):3366-74. doi: 10.1039/c1mb05320e. Epub 2011 Oct 19.

Abstract

New-type oseltamivir-resistant H1N1 influenza viruses have been a major threat to human health since the 2009 flu pandemic. To resolve the drug resistance issue, we aimed to identify a new type of inhibitors against H1 from traditional Chinese medicine (TCM) by employing the world's largest TCM database () for virtual screening and molecular dynamics (MD). From the virtual screening results, sodium (+)-isolaricireinol-2 alpha-sulfate, sodium 3,4-dihydroxy-5-methoxybenzoic acid methyl ester-4-sulfate, sodium (E)-7-hydroxy-1,7-bis(4-hydroxyphenyl)hept-5-ene-3S-sulfonate, and 3-methoxytyramine-betaxanthin were identified as potential drug-like compounds. MD simulation of the binding poses with the key residues Asp103 and Glu83, as well as other binding site residues, identified higher numbers of hydrogen bonds than N-Acetyl-D-Glucosamine (NAG), the natural ligand of the esterase domain in H1. Ionic bonds, salt bridges, and electrostatic energy also contribute to binding stability. Key binding residues include Lys71, Glu83, Asp103, and Arg238. Structural moieties promoting H-bond or salt bridge formations at these locations greatly contribute to a stable ligand-protein complex. An available sodium atom for ionic interactions with Asp103 can further stabilize the ligands. Based on virtual screening, MD simulation, and interaction energy evaluation, TCM candidates demonstrate good potential as novel H1 inhibitors. In addition, the identified stabilizing features can provide insights for designing highly stable H1 inhibitors.

摘要

自2009年流感大流行以来,新型耐奥司他韦H1N1流感病毒一直是人类健康的重大威胁。为了解决耐药性问题,我们旨在通过利用世界上最大的中药数据库进行虚拟筛选和分子动力学(MD),从中药中鉴定出一种新型的H1抑制剂。从虚拟筛选结果中,鉴定出(+)-异落叶松脂醇-2α-硫酸盐钠、3,4-二羟基-5-甲氧基苯甲酸甲酯-4-硫酸盐钠、(E)-7-羟基-1,7-双(4-羟基苯基)庚-5-烯-3S-磺酸盐和3-甲氧基酪胺-甜菜红素为潜在的类药物化合物。对与关键残基Asp103和Glu83以及其他结合位点残基的结合构象进行MD模拟,发现氢键数量比H1中酯酶结构域的天然配体N-乙酰-D-葡萄糖胺(NAG)更多。离子键、盐桥和静电能也有助于结合稳定性。关键结合残基包括Lys71、Glu83、Asp103和Arg238。在这些位置促进氢键或盐桥形成的结构部分对稳定的配体-蛋白质复合物有很大贡献。一个可用于与Asp103进行离子相互作用的钠原子可以进一步稳定配体。基于虚拟筛选、MD模拟和相互作用能评估,中药候选物作为新型H1抑制剂具有良好的潜力。此外,所确定的稳定特征可为设计高度稳定的H1抑制剂提供见解。

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