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费氏弧菌诱导物合成酶LuxI三级结构的计算机模拟预测与对接

In silico Prediction and Docking of Tertiary Structure of LuxI, an Inducer Synthase of Vibrio fischeri.

作者信息

Al-Khayyat Mohammed Zaghlool Saeed, Al-Dabbagh Ammar Ghanem Ameen

机构信息

Biology Department, College of Education for Pure Sciences, University of Mosul, Mosul, Iraq.

Biology Department, College of Sciences, University of Mosul, Mosul city, Iraq.

出版信息

Rep Biochem Mol Biol. 2016 Apr;4(2):66-75.

Abstract

BACKGROUND

LuxI is a component of the quorum sensing signaling pathway in Vibrio fischeriresponsible for the inducer synthesis that is essential for bioluminescence.

METHODS

Homology modeling of LuxI was carried out using Phyre2 and refined with the GalaxyWEB server. Five models were generated and evaluated by ERRAT, ANOLEA, QMEAN6, and Procheck.

RESULTS

Five refined models were generated by the GalaxyWEB server, with Model 4 having the greatest quality based on the QMEAN6 score of 0.732. ERRAT analysis revealed an overall quality of 98.9%, while the overall quality of the initial model was 54%. The mean force potential energy, as analyzed by ANOLEA, were better compared to the initial model. Sterochemical quality estimation by Procheck showed that the refined Model 4 had a reliable structure, and was therefore submitted to the protein model database. Drug Discovery Workbench V.2 was used to screen 2700 experimental compounds from the DrugBank database to identify inhibitors that can bind to the active site between amino acids 24 and 110. Ten compounds with high negative scores were selected as the best in binding.

CONCLUSION

The model produced, and the predicted acteyltransferase binding site, could be useful in modeling homologous sequences from other microorganisms and the design of new antimicrobials.

摘要

背景

LuxI是费氏弧菌群体感应信号通路的一个组成部分,负责合成对生物发光至关重要的诱导物。

方法

使用Phyre2对LuxI进行同源建模,并通过GalaxyWEB服务器进行优化。生成了五个模型,并通过ERRAT、ANOLEA、QMEAN6和Procheck进行评估。

结果

GalaxyWEB服务器生成了五个优化模型,基于QMEAN6评分为0.732,模型4的质量最高。ERRAT分析显示整体质量为98.9%,而初始模型的整体质量为54%。通过ANOLEA分析的平均力势能与初始模型相比更好。Procheck进行的立体化学质量评估表明,优化后的模型4具有可靠的结构,因此提交到蛋白质模型数据库。使用Drug Discovery Workbench V.2从DrugBank数据库中筛选2700种实验化合物,以鉴定可与24至110位氨基酸之间的活性位点结合的抑制剂。选择了十个负评分高的化合物作为结合效果最佳的化合物。

结论

所生成的模型以及预测的乙酰转移酶结合位点,可用于对其他微生物的同源序列进行建模以及设计新的抗菌药物。

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