A New Detailed Mass Offset Search in MSFragger for Improved Interpretation of Complex PTMs

Area of Science:

• Proteomics
• Computational Biology
• Biochemistry

Background:

• Conventional proteomics database searches face challenges in identifying multiple simultaneous protein modifications.
• Open or error-tolerant searches improve detection but complicate downstream data interpretation and quantification.
• Existing mass offset searches offer a middle ground but lack amino acid site specificity.

Purpose of the Study:

• To introduce a novel "detailed" mass offset (DMO) search strategy within the MSFragger engine.
• To enhance the simultaneous identification and site-specific localization of numerous protein modifications.
• To improve the interpretability and quantification of complex proteomic datasets.

Main Methods:

• Implementation of the DMO search in the MSFragger software.
• Development of site-specific restrictions and fragmentation rules for individual mass offsets.
• Application of DMO search to complex modification sets including post-translational modifications, FPOP-derived modifications, and amino acid substitutions.

Main Results:

• The DMO search successfully identified hundreds of modifications simultaneously across diverse datasets.
• DMO search significantly reduced ambiguity in site localization, especially for modifications with overlapping masses.
• Improved interpretability and scalability of results were demonstrated with increasing search complexity.

Conclusions:

• The DMO search represents a significant advancement over existing mass offset methods for proteomic analysis.
• This approach enhances the accuracy and ease of interpreting complex proteomic data with multiple modifications.
• DMO search provides a powerful tool for large-scale proteomic studies involving extensive modification analysis.