Synthesis of bee venom loaded chitosan nanoparticles for anti-MERS-COV and multi-drug resistance bacteria

International Journal of Biological Macromolecules(2023)

引用 8|浏览5
暂无评分
摘要
This study aims to fully exploit the natural compound; bee venom (BV) as a substance that can kill and inhibit the growth of microbes and viruses. For this target, BV was loaded onto a safe, natural, and economically inexpensive polymer; chitosan (Ch) in its nano-size form prepared using ionic gelation method in the presence of chemical crosslinking agent (sodium tripolyphosphate; TPP). The findings illustrated that chitosan nanoparticles (ChNPs) were prepared thru this method and exhibited spherical shape and average hydrodynamic size of 202 nm with a polydispersity index (PDI = 0.44). However, the size was increased to 221 nm with PDI (0.37) when chitosan nanoparticles were loaded with BV (ChNC). In addition, the particles of BV appeared as a core and chitosan nanoparticles as a shell implying the successful preparation of nanocomposite (ChNC). Encapsulation of BV into ChNPs with significantly small size distribution and good stability that protect these formed nanocomposites from agglomeration. The cytopathic effect (CPE) inhibition assay was used to identify potential antivirals for Middle East respiratory syndrome coronavirus (MERS-CoV). The response of the dose study was designed to influence the range of effectiveness for the chosen antiviral, i.e., the 50 % inhibitory concentration (IC50), as well as the range of cytotoxicity (CC50). However, our results indicated that crude BV had mild anti-MERS-COV with selective index (SI = 4.6), followed by ChNPs that exhibited moderate anti-MERS-COV with SI = 8.6. Meanwhile. The nanocomposite of ChNC displayed a promising anti-MERS-COV with SI = 12.1. Additionally, the synthesized nanocomposite (ChNC) had greater antimicrobial activity against both Gram-positive and Gram-negative bacteria when compared with ChNPs, BV or the utilized model drug.
更多
查看译文
关键词
Chitosan nanoparticles,Bee venom,MERS,MDR bacteria
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