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基于药效团的虚拟筛选和分子模拟方法发现有效的神经氨酸酶抑制剂。

Discovery of Potent Neuraminidase Inhibitors Using a Combination of Pharmacophore-Based Virtual Screening and Molecular Simulation Approach.

机构信息

Department of Biotechnology, School of Bio Sciences and Technology, VIT University, Vellore, Tamil Nadu, 632014, India.

出版信息

Appl Biochem Biotechnol. 2018 Apr;184(4):1421-1440. doi: 10.1007/s12010-017-2625-y. Epub 2017 Oct 23.

DOI:10.1007/s12010-017-2625-y
PMID:29063410
Abstract

Neuraminidase (NA), a surface protein, facilitates the release of nascent virus and thus spreads infection. It has been renowned as a potential drug target for influenza A virus infection. The drugs such as oseltamivir, zanamivir, peramivir, and laninamivir are approved for the treatment of influenza infection. Additionally, investigational drugs namely MK2206, tamiphosphor, crenatoside, and dehydroepiandrosterone (DHEA) are also available for the treatment. However, recent outbreaks of highly pathogenic and drug-resistant influenza A strains highlighted the need to discover novel NA inhibitor. Keeping this in mind, in the current investigation, an effort was made to ascertain potent inhibitors using pharmacophore-based virtual screening and docking approach. A 3D pharmacophore model was generated based on the chemical features of approved and investigational NA inhibitors using PHASE module of Schrödinger suite. The model consists of two hydrogen bond acceptors (A), one hydrogen bond donor (D), and one positively charged group (P), AADP. Subsequently, molecules with same pharmacophoric features were screened from among the two million compounds available in the ZINC database using the generated pharmacophore hypothesis. Ligand filtration was also done to obtain an efficient collection of hit molecules by employing Lipinski "rule of five" using Qikprop module. Finally, the screened molecule was subjected to docking and molecular dynamic simulations to examine the inhibiting activity of the compounds. The results of our analysis suggest that "acebutolol hydrochloride" (156792) could be the promising candidates for the treatment of influenza A virus infection.

摘要

神经氨酸酶(NA)是一种表面蛋白,它有助于新生病毒的释放,从而传播感染。它已被公认为流感 A 病毒感染的潜在药物靶点。奥司他韦、扎那米韦、帕拉米韦和拉尼米韦等药物已被批准用于治疗流感感染。此外,还可使用研究药物,如 MK2206、他米膦、菖蒲糖苷和脱氢表雄酮(DHEA)进行治疗。然而,最近高致病性和耐药性流感 A 株的爆发突出表明需要发现新型 NA 抑制剂。考虑到这一点,在当前的研究中,我们努力使用基于药效团的虚拟筛选和对接方法来确定有效的抑制剂。使用 Schrödinger 套件中的 PHASE 模块,基于已批准和研究中的 NA 抑制剂的化学特征,生成了一个 3D 药效团模型。该模型由两个氢键受体(A)、一个氢键供体(D)和一个正电荷基团(P)组成,即 AADP。随后,使用生成的药效团假说从 ZINC 数据库中 200 万个化合物中筛选出具有相同药效团特征的分子。还使用 Qikprop 模块通过 Lipinski“五规则”进行配体过滤,以获得高效的命中分子集合。最后,对筛选出的分子进行对接和分子动力学模拟,以检查化合物的抑制活性。我们的分析结果表明,“盐酸醋丁洛尔”(156792)可能是治疗流感 A 病毒感染的有前途的候选药物。

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