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Identification of peptides within a known protein sequence using COMSEQ analysis of data containing multiple
1Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha 68198-6495.
Computer Methods and Programs in Biomedicine
|May 1, 1991
Summary
New software, COMSEQ and auxiliary programs, aids in analyzing complex protein samples. These tools help identify specific amino acid sequences within noisy data, improving protein analysis accuracy.
Area of Science:
- Biochemistry
- Bioinformatics
- Proteomics
Background:
- Automated protein sequence analysis generates high-quality data but struggles with impure samples.
- Reconciling multiple amino acid sequences in noisy data with parent protein sequences is challenging.
Purpose of the Study:
- To develop computational tools for analyzing and reconciling multiple amino acid sequences from impure protein samples.
- To facilitate the identification of specific peptide sequences within complex or noisy datasets.
Main Methods:
- Development of COMSEQ program to generate a matrix comparing known and experimental sequences.
- Utilizing RNDSEQ for randomized sequence analysis to tabulate potential matches.
- Employing TRANSEQ to translate database sequences for compatibility with COMSEQ and RNDSEQ.
Main Results:
- Successfully identified co-sequenced peptides from bovine serum albumin.
- Detected an albumin peptide sequence amidst hemoglobin contamination.
- Differentiated two rat alpha-2u-globulin sequences with varying amino termini.
Conclusions:
- COMSEQ and its auxiliary programs effectively reconcile multiple amino acid sequences in noisy data.
- These tools enhance the accuracy of protein identification and characterization from complex biological samples.
- The software provides a valuable aid for researchers dealing with challenging protein sequencing data.