Identification of potential antiviral compounds from Egyptian sea stars against seasonal influenza A/H1N1 virus

Journal of Genetic Engineering and Biotechnology(2024)

引用 0|浏览7
暂无评分
摘要
BACKGROUND:One of the most dangerous problems that the world faced recently is viral respiratory pathogens. Marine creatures, including Echinodermata, specially Asteroidea class (starfish) have been extensively studied due to their miscellaneous bioactivities, excellent pharmacological properties, and complex secondary metabolites, including steroids, steroidal glycosides, anthraquinones, alkaloids, phospholipids, peptides, and fatty acids. These chemical constituents show antiviral activities against a wide range of viruses, including respiratory viruses. RESULTS:The present study aimed at the identification of potential antiviral compounds from some starfish species. The bioactive compounds from Pentaceraster cumingi, Astropecten polyacanthus, and Pentaceraster mammillatus were extracted using two different solvents (ethyl acetate and methanol). The antiviral activity against influenza A/H1N1 virus showed that ethyl acetate extract from Pentaceraster cumingi has the highest activity, where the selective index was 150.8. The bioactive compounds of this extract were identified by GC/MS analysis. The molecular docking study highlighted the virtual mechanism of binding of the identified compounds towards polymerase basic protein 2 and neuraminidase for H1N1 virus. Interestingly, linoleic acid showed promising binding energy of -10.12 Kcal/mol and -24.20 Kcal/mol for the selected two targets, respectively, and it formed good interactive modes with the key amino acids inside both proteins. CONCLUSION:The molecular docking analysis showed that linoleic acid was the most active antiviral compound from P. cumingi. Further studies are recommended for in-vitro and in-vivo evaluation of this compound against influenza A/H1N1 virus.
更多
查看译文
关键词
Starfish,Antiviral,Pentaceraster cumingi,Influenza,H1N1,Linoleic acid
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要