A complete search of combinatorial peptide library greatly benefited from probabilistic incorporation of prior knowledge

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F22%3A73610275" target="_blank" >RIV/61989592:15310/22:73610275 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1387380621002049" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1387380621002049</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijms.2021.116723" target="_blank" >10.1016/j.ijms.2021.116723</a>

Result language
angličtina
Original language name
A complete search of combinatorial peptide library greatly benefited from probabilistic incorporation of prior knowledge
Original language description
The core of peptide detection in tandem mass spectrometry lies in associating fragment spectra with promising peptide candidates. We examined such detection in a synthetic combinatorial peptide library using four scoring metrics, against all theoretical peptides, and with a varying level of probabilistic prior knowledge—analyzing more than a trillion peptide-spectrum matches in total. Even after adjusting for peptide-length scoring bias, most MS/MS spectra had multiple at-least-as-good candidates as the correct peptide, showing that the highest spectral match was not a guarantee of correctness. As a remedy, we probabilistically integrated prior knowledge about expected cleavage behavior and expected peptide sequences into peptide scoring, reaching and even overcoming the performance of state-of-the-art de novo sequencing algorithms. Overall, we found that even partial and weak beliefs considerably improved peptide detection and are, in principle, generally applicable to any detection approach. Detection of peptides in a complete search thus often resulted in multiple admissible candidates near the maximal score, and the use of probabilistic prior knowledge substantially improved their discrimination.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10608 - Biochemistry and molecular biology

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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