灵芝代谢物作为潜在抗动脉粥样硬化药物的计算探索:分子对接和动力学模拟的启示

IF 2.6 4区 生物学 Q2 BIOLOGY
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引用次数: 0

摘要

灵芝是一种独特的真菌,具有广泛的药理活性,被中医用于各种治疗。本研究的目的是评估灵芝代谢物可能具有的类药物特性,以及这些代谢物对动脉粥样硬化相关途径的影响。在整个研究过程中,我们根据类似药物的特性共选择了 17 种化合物。这些化合物被用于随后的联网和对接模拟。根据研究结果,化合物甘诺酮的最大结合能为-7.243 Kcal/mol。在结合能方面,发现杉烷醇化合物的结合能值最低。根据分子对接研究的结果,确定 TNF、AKT1、SRC 和 STAT3 对复合物的亲和力较高。为了确定这一点,进行了大约 100 纳秒的分子动力学模拟。在完成 GO 功能分析后,发现目标基因参与了蛋白质结合、ATP 结合、酶结合和蛋白质酪氨酸激酶活性等过程。总之,研究结果提供了一种可能影响疾病进展的代谢物的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational exploration of Ganoderma lucidum metabolites as potential anti-atherosclerotic agents: Insights from molecular docking and dynamics simulations

Ganoderma lucidum is a unique form of fungus utilized in Chinese medicine for various therapies as it exhibits a wide range of pharmacological activity. In this study, the purpose is to evaluate the possible drug-like qualities of the metabolites of G. lucidium as well as the impact that these metabolites have on the pathways involved in atherosclerosis. Throughout our research, a total of 17 compounds were chosen based on their drug-like properties. These compounds were then utilized in the subsequent networking and docking simulations. According to the findings, the compound ganodone has a maximum binding energy of −7.243 Kcal/mol. In terms of the binding energy, it has been discovered that the compound cianidanol has the lowest value. Based on the findings of the molecular docking investigations, it was determined that TNF, AKT1, SRC, and STAT3 exhibited a higher affinity for the complex. To determine this, molecular dynamics simulation was performed for about 100 nanoseconds. Following the completion of the GO functional analysis, it was discovered that the target genes were involved in the processes of protein binding, ATP binding, enzyme binding, and protein tyrosine kinase activity. Overall, the study results provide a view of possible metabolites that may have an impact on disease progression.

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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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