Suppr超能文献

针对研究γ疱疹病毒损伤免疫系统和趋化因子相关疾病的模型,对 m3 蛋白拮抗剂进行虚拟筛选。

Virtual screening of m3 protein antagonists for finding a model to study the gammaherpesvirus damaged immune system and chemokine related diseases.

机构信息

Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Isfahan Cardiovascular Research Center, Isfahan cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran.

出版信息

Bioimpacts. 2013;3(4):177-83. doi: 10.5681/bi.2013.022. Epub 2013 Jul 17.

Abstract

INTRODUCTION

M3 protein is a chemokine decoy receptor involved in pathogenesis of persistent infection with gammaherpesvirus and complications related to the latency of this pathogen. We proposed that antagonists of the M3 would provide a unique opportunity for studying new therapeutic strategies in disordered immune system, immune-deficient states and role of chemokines in pathogenesis development.

METHODS

Comparative modeling and fold recognition algorithms have been used for prediction of M3 protein 3-D model. Evaluation of the models using Q-mean and ProSA-web score, has led to choosing predicted model by fold recognition algorithm as the best model which was minimized regarding energy level using Molegro Virtual Docker 2011.4.3.0 (MVD) software. Pockets and active sites of model were recognized using MVD cavity detection, and MetaPocket algorithms. Ten thousand compounds accessible on KEGG database were screened; MVD was used for computer simulated docking study; MolDock SE was selected as docking scoring function and final results were evaluated based on MolDock and Re-rank score.

RESULTS

Docking data suggested that prilocaine, which is generally applied as a topical anesthetic, binds strongly to 3-D model of M3 protein.

CONCLUSION

This study proposes that prilocaine is a potential inhibitor of M3 protein and possibly has immune enhancing properties.

摘要

简介

M3 蛋白是一种趋化因子诱饵受体,参与γ疱疹病毒的持续感染发病机制以及与该病原体潜伏期相关的并发症。我们提出,M3 的拮抗剂将为研究免疫系统紊乱、免疫缺陷状态以及趋化因子在发病机制发展中的作用的新治疗策略提供独特的机会。

方法

使用比较建模和折叠识别算法预测 M3 蛋白的 3D 模型。使用 Q-mean 和 ProSA-web 评分评估模型,选择折叠识别算法预测的模型作为最佳模型,然后使用 Molegro Virtual Docker 2011.4.3.0(MVD)软件根据能量水平对其进行最小化。使用 MVD 腔探测和 MetaPocket 算法识别模型的口袋和活性部位。筛选 KEGG 数据库中可用的一万种化合物;使用 MVD 进行计算机模拟对接研究;选择 MolDock SE 作为对接评分函数,并根据 MolDock 和重新排序评分评估最终结果。

结果

对接数据表明,普鲁卡因通常用作局部麻醉剂,与 M3 蛋白的 3D 模型结合紧密。

结论

本研究表明,普鲁卡因可能是 M3 蛋白的潜在抑制剂,并且具有增强免疫的特性。

相似文献

4
Molegro Virtual Docker for Docking.用于对接的Molegro虚拟容器。
Methods Mol Biol. 2019;2053:149-167. doi: 10.1007/978-1-4939-9752-7_10.

本文引用的文献

3
MolDock applied to structure-based virtual screening.分子对接在基于结构的虚拟筛选中的应用。
Curr Drug Targets. 2010 Mar;11(3):327-34. doi: 10.2174/138945010790711941.
6
The SWISS-MODEL Repository and associated resources.SWISS-MODEL 资源库及相关资源。
Nucleic Acids Res. 2009 Jan;37(Database issue):D387-92. doi: 10.1093/nar/gkn750. Epub 2008 Oct 18.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验