mMass

mMass analyzes mass spectrometry (MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) data to process spectra and support identification and structural interpretation of peptides, lipids, and nonribosomal natural products.

Key Features:

• Data import and preprocessing: Import of multiple MS and LC-MS/MS data formats with smoothing, baseline correction, peak picking, deisotoping, charge determination, and recalibration.
• In silico digestion and fragmentation: Computational prediction of peptide digestion products and fragmentation spectra for spectrum interpretation.
• Search engine interfaces: Integration interfaces for Mascot and ProFound to support database-driven peptide identification.
• Isotopic pattern modeling: Precise isotopic pattern simulation for validation of measured spectra.
• Lipid identification: Compound search and identification using the LIPID MAPS Consortium database and support for user-defined compound libraries.
• Nonribosomal peptide annotation: Annotation and interpretation of complex fragmentation patterns for linear and cyclic nonribosomal peptides.
• Modular implementation: Core functionality implemented as a stand-alone Python library for data processing and interpretation.

Scientific Applications:

• Proteomics: Analysis and interpretation of protein spectra with export and integration to Mascot and ProFound search workflows.
• Lipidomics: Identification of lipid species using LIPID MAPS Consortium data to support studies of lipid composition and metabolism.
• Natural product discovery: Structural annotation and confirmation of bioactive nonribosomal peptides and other complex natural products.

Methodology:

Computational methods explicitly include importing MS and LC-MS/MS formats, smoothing, baseline correction, peak picking, deisotoping, charge determination, recalibration, in silico digestion and fragmentation, isotopic pattern modeling, nonribosomal peptide annotation, interfaces to Mascot and ProFound, LIPID MAPS database access, compound search and custom library support, implemented in a stand-alone Python library.