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Crystal-C: A Computational Tool for Refinement of Open Search Results
Hui-Yin Chang1, Andy T Kong1, Felipe da Veiga Leprevost1
1Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States.
Journal of Proteome Research
|April 28, 2020
Summary
Crystal-C is a new computational tool that removes artifacts from open search results in shotgun proteomics. This improves the detection of true post-translational modifications by simplifying data analysis.
Area of Science:
- Proteomics
- Mass Spectrometry
- Computational Biology
Background:
- Shotgun proteomics with LC-MS identifies post-translational modifications (PTMs).
- Open search strategies in proteomics increase the detection of PTMs and chemical modifications.
- Artifacts like missed cleavages and chimeric spectra can be mistaken for true modifications in open search results.
Purpose of the Study:
- To develop a computational tool, Crystal-C, for detecting and removing artifacts from open search results in shotgun proteomics.
- To enhance the accuracy and interpretability of PTM analysis using open search data.
Main Methods:
- Development of the Crystal-C computational tool.
- Application of Crystal-C to analyze shotgun proteomics data.
- Evaluation of Crystal-C's performance in identifying and removing artifacts.
Main Results:
- Crystal-C effectively detects and removes artifacts from open search data.
- The number of artifacts in typical shotgun proteomics datasets is relatively small.
- Removal of artifacts simplifies mass shift histogram interpretation.
Conclusions:
- Crystal-C improves the reliability of open search in proteomics.
- The tool enhances the ability to identify true post-translational and chemical modifications.
- Crystal-C facilitates more accurate downstream analysis and discovery in proteomics research.
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