IN SILICO STUDY OF Stachytarpheta jamaicensis ACTIVE COMPOUNDS AS ANTIBACTERIAL MATERIAL

Juliyatin Putri Utami, S. Diana, Rahmad Arifin
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Abstract

Background: Stachytarpheta jamaicensis is a wild plant from the Verbenanceae family that grows in tropical areas such as Indonesia. S. jamaecensis extract was proven to contain secondary metabolite compounds such as flavonoids, phenols, saponins, tannins and terpenoids. The active compound of S. jamaecensis can be used as a drug candidate in the medicine field, especially as an antibacterial compound. One of the first steps in predicting the effectiveness of these compounds can be done through in-Silico studies with molecular docking. Objective: This study aims to evaluate the interaction of active compound S. jamaecensis with bacterial proteins through an in silico study. Methods: Using in silico method with computational docking analysis on seven active compounds of S. jamaecensis namely apigenin, luteolin, chlorogenic acid, gamma butyric acid, dopamine, ipolamide and geraniol, as well as two antibacterial drugs (metronidazole and chlorhexidine) as comparisons bound with bacterial cell wall protein, namely Glucosamine-6-phosphate synthase (G1mS). Docking in silico uses Autodock Vina, which is integrated with PyRx 8.0 and visualized using Discovery Studio Visualizer v19.1.0.18287 (2019 version) with data presentation based on docking scores. Conclusion: The best binding affinity score has been the luteolin-G1mS complex with a binding affinity value of -10.8 kcal/mol and was the highest value compared to the comparison ligand binding and the binding of other active compounds of S. jamaecensis.
牙买加水毛果有效成分作为抗菌物质的硅片研究
背景:牙买加Stachytarpheta jamaicensis是马鞭草科的一种野生植物,生长在印度尼西亚等热带地区。牙买加树提取物被证明含有次生代谢物化合物,如黄酮类化合物、酚类化合物、皂苷、单宁和萜类化合物。牙买加芽孢杆菌的活性化合物在医学领域具有重要的候选药物价值,尤其是抗菌化合物。预测这些化合物有效性的第一步可以通过分子对接的计算机研究来完成。目的:通过计算机实验研究牙买加芽孢杆菌活性化合物与细菌蛋白的相互作用。方法:采用计算机对接分析的方法,用芹菜素、木犀草素、绿原酸、伽马丁酸、多巴胺、异丙酰胺、香叶醇等7种有效成分,以及甲硝唑和氯己定两种抗菌药物与细菌细胞壁蛋白葡萄糖胺-6-磷酸合成酶(Glucosamine-6-phosphate synthase, G1mS)结合进行比较。在硅中对接使用Autodock Vina,它集成了PyRx 8.0,并使用Discovery Studio Visualizer v19.1.0.18287(2019版本)进行可视化,并基于对接分数进行数据显示。结论:木黄素- g1ms复合物的结合亲和力评分最高,其结合亲和力值为-10.8 kcal/mol,与对照配体结合及与牙买加草其他活性化合物的结合相比,木黄素- g1ms复合物的结合亲和力值最高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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24 weeks
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