Abstract：
BACKGROUND: A bacterial biofilm is a cluster of bacterial cells embedded in a self-produced matrix of extracellular polymeric substances such as DNA, proteins, and polysaccharides. Several diseases have been reported to cause by bacterial biofilms, and difficulties in treating these infections are of concern. This work aimed to identify the inhibitor with the highest binding affinity for the receptor protein by screening various inhibitors obtained from Azorella species for a potential target to inhibit dispersin B. This work shows that azorellolide has the highest binding affinity (- 8.2 kcal/mol) among the compounds tested, followed by dyhydroazorellolide, mulinone A, and 7-acetoxy-mulin-9,12-diene which all had a binding affinity of - 8.0 kcal/mol. To the best of our knowledge, this is the first study to evaluate and contrast several diterpene compounds as antibacterial biofilm chemicals.
METHODS: Here, molecular modelling techniques tested 49 diterpene compounds of Azorella and six FDA-approved antibiotics medicines for antibiofilm activity. Since protein-like interactions are crucial in drug discovery, AutoDock Vina was initially employed to carry out structure-based virtual screening. The drug-likeness and ADMET properties of the chosen compounds were examined to assess the antibiofilm activity further. Lipinski\'s rule of five was then applied to determine the antibiofilm activity. Then, molecular electrostatic potential was used to determine the relative polarity of a molecule using the Gaussian 09 package and GaussView 5.08. Following three replica molecular dynamic simulations (using the Schrodinger program, Desmond 2019-4 package) that each lasted 100 ns on the promising candidates, binding free energy was estimated using MM-GBSA. Structural visualisation was used to test the binding affinity of each compound to the crystal structure of dispersin B protein (PDB: 1YHT), a well-known antibiofilm compound.
METHODS: Here, molecular modelling techniques tested 49 diterpene compounds of Azorella and six FDA-approved antibiotics medicines for antibiofilm activity. Since protein-like interactions are crucial in drug discovery, AutoDock Vina was initially employed to carry out structure-based virtual screening. The drug-likeness and ADMET properties of the chosen compounds were examined to assess the antibiofilm activity further. Lipinski\'s rule of five was then applied to determine the antibiofilm activity. Then, molecular electrostatic potential was used to determine the relative polarity of a molecule using the Gaussian 09 package and GaussView 5.08. Following three replica molecular dynamic simulations (using the Schrodinger program, Desmond 2019-4 package) that each lasted 100 ns on the promising candidates, binding free energy was estimated using MM-GBSA. Structural visualisation was used to test the binding affinity of each compound to the crystal structure of dispersin B protein (PDB: 1YHT), a well-known antibiofilm compound.
摘要：
背景：细菌生物膜是一群细菌细胞，它们嵌入在自产生的细胞外聚合物质如DNA的基质中，蛋白质，和多糖。据报道，一些疾病是由细菌生物膜引起的，治疗这些感染的困难令人担忧。这项工作旨在通过筛选从Azorella物种获得的各种抑制剂来鉴定对受体蛋白具有最高结合亲和力的抑制剂，以抑制分散素B的潜在靶标。这项工作表明，阿唑瑞利特具有最高的结合亲和力（-8.2kcal/mol）在测试的化合物中，其次是二氢唑列利，MulinoneA,和7-乙酰氧基-木素-9,12-二烯，它们都具有-8.0kcal/mol的结合亲和力。据我们所知,这是第一个评价和对比几种二萜化合物作为抗菌生物膜化学物质的研究。
方法：这里，分子建模技术测试了49种Azorella的二萜化合物和六种FDA批准的抗生素药物的抗生物膜活性。由于蛋白质样相互作用在药物发现中至关重要，AutoDockVina最初用于进行基于结构的虚拟筛选。检查所选化合物的药物相似性和ADMET特性以进一步评估抗生物膜活性。然后应用Lipinski的5法则来确定抗生物膜活性。然后，分子静电势用于使用高斯09包和高斯视图5.08确定分子的相对极性。在三个复制分子动力学模拟之后(使用薛定谔程序，德斯蒙德2019-4套餐)，每个人对有希望的候选人持续100ns，使用MM-GBSA估计结合自由能。结构可视化用于测试每种化合物与分散蛋白B（PDB：1YHT）晶体结构的结合亲和力，一种众所周知的抗生物膜化合物。
方法：这里，分子建模技术测试了49种Azorella的二萜化合物和六种FDA批准的抗生素药物的抗生物膜活性。由于蛋白质样相互作用在药物发现中至关重要，AutoDockVina最初用于进行基于结构的虚拟筛选。检查所选化合物的药物相似性和ADMET特性以进一步评估抗生物膜活性。然后应用Lipinski的5法则来确定抗生物膜活性。然后，分子静电势用于使用高斯09包和高斯视图5.08确定分子的相对极性。在三个复制分子动力学模拟之后(使用薛定谔程序，德斯蒙德2019-4套餐)，每个人对有希望的候选人持续100ns，使用MM-GBSA估计结合自由能。结构可视化用于测试每种化合物与分散蛋白B（PDB：1YHT）晶体结构的结合亲和力，一种众所周知的抗生物膜化合物。
