Satari Mieke Hemiawati, Apriyanti Eti, Dharsono Hendra Dian Adhita, Nurdin Denny, Gartika Meirina, Kurnia Dikdik
Department of Oral Biology, Faculty of Dentistry, Universitas Padjadjaran, Bandung 40132, Indonesia.
Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia.
Molecules. 2021 Apr 23;26(9):2465. doi: 10.3390/molecules26092465.
antibiotic resistance encourages the development of new therapies, or the discovery of novel antibacterial agents. Previous research revealed that (Sarang Semut) contain potential antibacterial agents. However, specific proteins inhibited by them have not yet been identified as either proteins targeted by antibiotics or proteins that have a role in the quorum-sensing system. This study aims to investigate and predict the action mode of antibacterial compounds with specific proteins by following the molecular docking approach.
butein (), biflavonoid (), 3″-methoxyepicatechin-3--epicatechin (), 2-dodecyl-4-hydroxylbenzaldehyde (), 2-dodecyl-4-hydroxylbenzaldehyde (), pomolic acid (), betulin (), and sitosterol-(6'--tridecanoil)-3---D-glucopyranoside () from act as the ligand. Antibiotics or substrates in each protein were used as a positive control. To screen the bioactivity of compounds, ligands were analyzed by Prediction of Activity Spectra for Substances (PASS) program. They were docked with 12 proteins by AutoDock Vina in the PyRx 0.8 software application. Those proteins are penicillin-binding protein (PBP), MurB, Sortase A (SrtA), deoxyribonucleic acid (DNA) gyrase, ribonucleic acid (RNA) polymerase, ribosomal protein, Cytolysin M (ClyM), FsrB, gelatinase binding-activating pheromone (GBAP), and PgrX retrieved from UniProt. The docking results were analyzed by the ProteinsPlus and Discovery Studio software applications.
most compounds have Pa value over 0.5 against proteins in the cell wall. In nearly all proteins, biflavonoid () has the strongest binding affinity. However, compound binds only three residues, so that is the non-competitive inhibitor.
compound can be a lead compound for an antibacterial agent in each pathway.
抗生素耐药性促使新疗法的开发或新型抗菌剂的发现。先前的研究表明,(蚂蚁)含有潜在的抗菌剂。然而,它们所抑制的特定蛋白质尚未被鉴定为抗生素靶向的蛋白质或在群体感应系统中起作用的蛋白质。本研究旨在通过分子对接方法研究并预测抗菌化合物与特定蛋白质的作用模式。
从(蚂蚁)中提取的紫铆因()、双黄酮()、3″-甲氧基表儿茶素-3-表儿茶素()、2-十二烷基-4-羟基苯甲醛()、2-十二烷基-4-羟基苯甲醛()、坡模酸()、桦木醇()和β-谷甾醇-(6'-O-十三烷酰基)-3-O-β-D-吡喃葡萄糖苷()作为配体。每种蛋白质中的抗生素或底物用作阳性对照。为了筛选化合物的生物活性,通过物质活性谱预测(PASS)程序分析配体。它们通过PyRx 0.8软件应用中的AutoDock Vina与12种蛋白质对接。这些蛋白质是青霉素结合蛋白(PBP)、MurB、分选酶A(SrtA)、脱氧核糖核酸(DNA)回旋酶、核糖核酸(RNA)聚合酶、核糖体蛋白、溶细胞素M(ClyM)、FsrB、明胶酶结合激活信息素(GBAP)以及从UniProt检索到的PgrX。对接结果通过ProteinsPlus和Discovery Studio软件应用进行分析。
大多数化合物对细胞壁中的蛋白质的Pa值超过0.5。在几乎所有蛋白质中,双黄酮()具有最强的结合亲和力。然而,化合物()仅结合三个残基,因此()是非竞争性抑制剂。
化合物()可以成为每种途径中抗菌剂的先导化合物。