Molecular networking: An efficient tool for discovering and identifying natural products

Area of Science:

• Chemistry
• Pharmacology
• Bioinformatics

Background:

• Natural products (NPs) are vital for drug development, but their discovery is often accidental and identification methods lack precision.
• Molecular networking (MN), utilizing secondary mass spectrometry, is emerging as a powerful tool for NP separation, purification, and structural identification.
• Many novel MN tools remain underutilized, necessitating a comprehensive overview.

Purpose of the Study:

• To provide a detailed review of established and novel Molecular Networking (MN) tools for natural product (NP) discovery.
• To compare the scope and reliability of various MN tools using applications in phytochemistry and metabolomics.
• To introduce and classify 12 structural annotation tools, summarizing their advantages, disadvantages, and suitability for different compound structures.

Main Methods:

• Systematic review of existing literature on Molecular Networking (MN) principles, workflows, and applications.
• Comparative analysis of nine different MN tools based on their application in phytochemistry and metabolomics.
• Categorization and evaluation of twelve structural annotation tools for identifying natural products.

Main Results:

• Detailed explanation of basic and eight new types of MN tools, including their principles and workflows.
• Reliability assessment of MN tools through case studies in phytochemistry and metabolomics.
• Classification of 12 structural annotation tools based on their effectiveness for identifying various compound structures.

Conclusions:

• Molecular networking (MN) significantly enhances the efficiency of natural product (NP) discovery and identification.
• This review offers a valuable resource for researchers by comparing MN tools and structural annotation methods.
• Future directions emphasize the development of advanced computational tools to further optimize NP research.