药物发现
计算生物学
代谢组学
药物开发
基因组学
蛋白质组学
计算机科学
药品
基因组
生物
生物信息学
药理学
基因
遗传学
作者
Abdullahi Tunde Aborode,Wireko Andrew Awuah,Tatiana Mikhailova,Toufik Abdul- Rahman,Samantha M. Pavlock,Mrinmoy Kundu,Rohan Yarlagadda,Manas Pustake,Inês F. Silva Correia,Qasim Mehmood,Parth N. Shah,Aashna Mehta,Shahzaib Ahmad,Abiola Asekun,Esther Patience Nansubuga,Shekinah Obinna Amaka,Anastasiia D. Shkodina,Αθανάσιος Αλεξίου
标识
DOI:10.2174/1568026622666220726092034
摘要
Abstract: Compounds isolated from natural sources have been used for medicinal purposes for many centuries. Some metabolites of plants and microorganisms possess properties that would make them effective treatments against bacterial infection, inflammation, cancer, and an array of other medical conditions. In addition, natural compounds offer therapeutic approaches with lower toxicity compared to most synthetic analogues. However, it is challenging to identify and isolate potential drug candidates without specific information about structural specificity and limited knowledge of any specific physiological pathways in which they are involved. To solve this problem and find a way to efficiently utilize natural sources for the screening of compounds candidates, technologies, such as next-generation sequencing, bioinformatics techniques, and molecular analysis systems, should be adapted for screening many chemical compounds. Molecular techniques capable of performing analysis of large datasets, such as whole-genome sequencing and cellular protein expression profile, have become essential tools in drug discovery. OMICs, as genomics, proteomics, and metabolomics, are often used in targeted drug discovery, isolation, and characterization. This review summarizes technologies that are effective in natural source drug discovery and aid in a more precisely targeted pharmaceutical approach, including RNA interference or CRISPR technology. We strongly suggest that a multidisciplinary effort utilizing novel molecular tools to identify and isolate active compounds applicable for future drug discovery and production must be enhanced with all the available computational tools.
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