Computational exploration of Ganoderma lucidum metabolites as potential anti-atherosclerotic agents: Insights from molecular docking and dynamics simulations
{"title":"Computational exploration of Ganoderma lucidum metabolites as potential anti-atherosclerotic agents: Insights from molecular docking and dynamics simulations","authors":"","doi":"10.1016/j.compbiolchem.2024.108160","DOIUrl":null,"url":null,"abstract":"<div><p><em><strong>Ganoderma lucidum</strong></em> 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 <em>G. lucidium</em> 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.</p></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927124001488","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.