SMfinder: Small Molecules Finder for Metabolomics and Lipidomics Analysis

Area of Science:

• Biochemistry
• Computational Biology
• Analytical Chemistry

Background:

• Metabolomics and lipidomics are growing fields with limited automated data analysis tools.
• Accurate metabolite identification is a major challenge in untargeted metabolomics.

Purpose of the Study:

• To introduce SMfinder, a user-friendly, open-source software for robust identification and quantification of small molecules.
• To improve the accuracy of metabolite identification in metabolomics and lipidomics studies.

Main Methods:

• Development of SMfinder software with an MS2 false discovery rate approach based on single spectral permutation.
• Application to shotgun and targeted metabolomics and lipidomics analysis.
• Utilizes available MS2 libraries for instrument-independent identification.

Main Results:

• SMfinder increases identification accuracy through its novel MS2 false discovery rate method.
• The software enables robust identification and quantification of small molecules.
• It reduces the need for extensive in-house standard acquisition.

Conclusions:

• SMfinder offers a powerful solution for automated data analysis in metabolomics and lipidomics.
• The software is suitable for untargeted, targeted, and flux analysis.
• It enhances the reliability and efficiency of small molecule identification.