Abstract
Given a peptide as a string of amino acids, the masses of all its prefixes and suffixes can be found by a trivial linear scan through the amino acid masses. The inverse problem is the ideal de novo peptide sequencing problem: Given all prefix and suffix masses, determine the string of amino acids. In biological reality, the given masses are measured in a lab experiment, and measurements by necessity are noisy. The (real, noisy) de novo peptide sequencing problem therefore has a noisy input: a few of the prefix and suffix masses of the peptide are missing and a few others are given in addition. For this setting we ask for an amino acid string that explains the given masses as accurately as possible. Past approaches interpreted accuracy by searching for a string that explains as many masses as possible. We feel, however, that it is not only bad to not explain a mass that appears, but also to explain a mass that does not appear. That is, we propose to minimize the symmetric difference between the set of given masses and the set of masses that the string explains. For this new optimization problem, we propose an efficient algorithm that computes both the best and the k best solutions. Experiments on measurements of 342 synthesized peptides show that our approach leads to better results compared to finding a string that explains as many given masses as possible.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Chen, T., Kao, M.-Y., Tepel, M., Rush, J., Church, G.M.: A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry. In: Proceedings of the Eleventh Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2000) (2000). (Conference version of [2])
Chen, T., Kao, M.-Y., Tepel, M., Rush, J., Church, G.M.: A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 8(3), 325–337 (2001). (Journal version of [1])
Dančík, V., Addona, T.A., Clauser, K.R., Vath, J.E., Pevzner, P.A.: De novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 6(3–4), 327–342 (1999)
Eppstein, D.: Finding the k shortest paths. SIAM J. Comput. 28(2), 652–673 (1998)
Gabow, H., Maheshwari, S., Osterweil, L.: On two problems in the generation of program test paths. IEEE Trans. Softw. Eng. SE–2(3), 227–231 (1976)
Hughes, C., Ma, B., Lajoie, G.A.: De novo sequencing methods in proteomics. Proteome Bioinf. 604, 105–121 (2010)
Jeong, K., Kim, S., Pevzner, P.A.: UniNovo: a universal tool for de novo peptide sequencing. Bioinformatics 29(16), 1953–1962 (2013). (Oxford, England)
Kinter, M., Sherman, N.E.: Protein Sequencing and Identication Using Tandem Mass Spectrometry. Wiley-Interscience, New York (2000)
Lu, B., Chen, T.: A suboptimal algorithm for de novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 10(1), 1–12 (2003)
Ma, B., Zhang, K., Liang, C.: An effctive algorithm for the peptide de novo sequencing from MS/MS spectrum. Comb. Pattern Matching 2676, 266–277 (2003)
Mo, L., Dutta, D., Wan, Y., Chen, T.: MSNovo: a dynamic programming algorithm for de novo peptide sequencing via tandem mass spectrometry. Anal. Chem. 79(13), 4870–4878 (2007)
Röst, H.L., Rosenberger, G., Navarro, P., Gillet, L., Miladinović, S.M., Schubert, O.T., Wolski, W., Collins, B.C., Malmström, J., Malmström, L., Aebersold, R.: OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat. Biotechnol. 32(3), 219–223 (2014)
Acknowledgments
We would like to thank Tomas Hruz, George Rosenberger, and Hannes Röst for helpful discussions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Gillet, L., Rösch, S., Tschager, T., Widmayer, P. (2016). A Better Scoring Model for De Novo Peptide Sequencing: The Symmetric Difference Between Explained and Measured Masses. In: Frith, M., Storm Pedersen, C. (eds) Algorithms in Bioinformatics. WABI 2016. Lecture Notes in Computer Science(), vol 9838. Springer, Cham. https://doi.org/10.1007/978-3-319-43681-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-43681-4_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-43680-7
Online ISBN: 978-3-319-43681-4
eBook Packages: Computer ScienceComputer Science (R0)