Analysis of botanicals and botanical supplements by LC-MS/MS-based molecular networking: Approaches for annotating plant metabolites and authentication

Prior to the advent of modern medicine, humans have used botanicals extensively for their therapeutic potential. With the majority of newly approved drugs having their origins in natural products, plants remain at the forefront of drug discovery. Continued research and discovery necessitate the use of high-throughput analytical methods to screen and identify bioactive components and potential therapeutic molecules from plants. Utilizing a pre-generated plant extract library, we subjected botanicals to LC-MS/MS-based molecular networking to determine their chemical composition and relatively quantify already known metabolites. The LC-MS/MS-based molecular networking approach was also used to authenticate the composition of dietary supplements against their corresponding plant specimens. The networking procedures provided concise visual representations of the chemical space and highly informative assessments of the botanicals. The procedures also proved to define the composition of the botanical supplements quickly and efficiently. This offered an innovative approach to metabolite profiling and authentication practices and additionally allowed for the identification of new, putatively unknown metabolites for future isolation and biological evaluation.

Automated summary

Prior to modern medicine, plants have been extensively used for their therapeutic potential, and the majority of newly approved drugs originate from natural products. High-throughput analytical methods such as LC-MS/MS-based molecular networking are crucial for screening and identifying bioactive components and potential therapeutic molecules from plants. This approach also enables the authentication of dietary supplements against plant specimens. The networking procedures offer concise visual representations of the chemical space and informative assessments of the botanicals, allowing for efficient composition determination and the identification of new metabolites for future evaluation.