Integrated algorithms for high-throughput examination of covalently labeled biomolecules by structural mass spectrometry.
Mass spectrometry based structural proteomics approaches for probing protein structures are increasingly gaining in popularity. The potential for such studies is limited because of the lack of analytical techniques for the automated interpretation of resulting data. In this article, a suite of algorithms called ProtMapMS is developed, integrated, and implemented specifically for the comprehensive automatic analysis of mass spectrometry data obtained for protein structure studies using covalent labeling. The functions include data format conversion, mass spectrum interpretation, detection, and verification of all peptide species, confirmation of the modified peptide products, and quantification of the extent of peptide modification. The results thus obtained provide valuable data for use in combination with computational approaches for protein structure modeling. The structures of both monomeric and hexameric forms of insulin were investigated by oxidative protein footprinting followed by high-resolution mass spectrometry. The resultant data was analyzed both manually and using ProtMapMS without any manual intervention. The results obtained using the two methods were found to be in close agreement and overall were consistent with predictions from the crystallographic structure.
Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio 44106, USA. pkhatra@case.edu
Parminder
P
Kaur
Janna G
JG
Kiselar
Mark R
MR
Chance
D000465:Algorithms; D000595:Amino Acid Sequence; D006801:Humans; D017665:Hydroxyl Radical / Q000737:chemistry; D007328:Insulin / Q000737:chemistry*; D013058:Mass Spectrometry / Q000379:methods*; D010084:Oxidation-Reduction; D040901:Proteomics
D007328:Insulin; D017665:Hydroxyl Radical