PDF(Pubmed)
Abstract：
Inflammation is caused by a cascade of events, one of which is the metabolism of arachidonic acid, that begins with oxidation by the enzyme 5-lipoxygenase. 5-Lipoxygenase (5-LOX) plays an important role in the inflammation process by synthesizing leukotrienes and several lipid mediators and has emerged as a possible therapeutic target for treatment of inflammatory diseases such as asthma and rheumatoid arthritis. Most of the existing 5-LOX inhibitors are synthetic and exhibit adverse side effects. In view of this, there is need to search for an alternate source of 5-LOX inhibitor with minimal side effects. The essential oil of several species of Curcuma has received considerable attention in recent times in traditional system of medicine especially for treating various inflammatory disorders. Therefore, the present study was carried out to screen the most potential 5-LOX inhibitors from essential oil components of Curcuma species and elucidate their mechanisms of action through computational biology approaches. Twenty-three phytoconstituents derived from the essential oil of Curcuma species were docked and their predictive binding energies were calculated to select the best possible ligand for 5-LOX. The top 8 ranked compounds from docking was tested for drug-likeness properties, bioactivity score, and toxicity analysis. The phytoconstituents such as α-turmerone, β-turmerone, α-terpineol and dihydrocarveolshowed the best binding affinity with 5-LOX and displayed favorable physicochemical properties. Molecular dynamics simulation in POPC lipid bilayers was carried out to understand the intrinsic dynamics and flexibility of the 5-LOX (apo) and 5-LOX-complex (α-terpineol, α-turmerone, β-turmerone and dihydrocarveol) systems. The molecular dynamic results showed that these 4 phytoconstituents interacted stably with the 5-LOX active site residues and the important bonds that were observed in the initial ligand docked compounds did not alter during the course of simulation. In general, our integrative computational approach demonstrated that the natural compounds like α-turmerone, β-turmerone, α-terpineol, and dihydrocarveol could be considered for designing specific anti-inflammatory drugs using structure-based drug design.
摘要：
炎症是由一系列事件引起的，其中之一是花生四烯酸的代谢，这始于酶5-脂氧合酶的氧化。5-脂氧合酶（5-LOX）通过合成白三烯和几种脂质介质在炎症过程中起重要作用，并已成为治疗炎性疾病如哮喘和类风湿性关节炎的可能治疗靶标。大多数现有的5-LOX抑制剂是合成的并且表现出不良副作用。鉴于此,需要寻找副作用最小的5-LOX抑制剂的替代来源。近年来，姜黄的几种精油在传统的药物系统中受到了相当大的关注，特别是用于治疗各种炎症性疾病。因此,本研究旨在从姜黄属物种的精油成分中筛选最有潜力的5-LOX抑制剂，并通过计算生物学方法阐明其作用机制。将来自姜黄属物种精油的23种植物成分对接，并计算其预测结合能，以选择5-LOX的最佳配体。对接中排名前8位的化合物进行了药物相似度测试，生物活性评分，和毒性分析。植物成分如α-姜黄酮，β-姜黄酮,α-松油醇和二氢卡维醇显示出与5-LOX的最佳结合亲和力，并显示出良好的理化性质。进行了POPC脂质双层中的分子动力学模拟，以了解5-LOX（apo）和5-LOX复合物（α-松油醇，α-姜黄酮,β-姜黄酮和二氢卡维醇）系统。分子动力学结果表明，这4种植物成分与5-LOX活性位点残基稳定相互作用，并且在初始配体对接化合物中观察到的重要键在模拟过程中没有改变。总的来说,我们的综合计算方法证明了像α-姜黄酮这样的天然化合物，β-姜黄酮,α-松油醇,和二氢卡维醇可以考虑使用基于结构的药物设计来设计特定的抗炎药。
