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oai:repisalud.isciii.es:20.500.12105/165762024-09-27T09:37:57Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605

00925njm 22002777a 4500 dc Laguillo-Gómez, Andrea author Calvo, Enrique author Martín-Cófreces, Noa author Lozano-Prieto, Marta author Sánchez-Madrid, Francisco author Vazquez, Jesus author 2023-09-15 Open-search methods allow unbiased, high-throughput identification of post-translational modifications in proteins at an unprecedented scale. The performance of current open-search algorithms is diminished by experimental errors in the determination of the precursor peptide mass. In this work we propose a semi-supervised open search approach, called ReCom, that minimizes this effect by taking advantage of a priori known information from a reference database, such as Unimod or a database provided by the user. We present a proof-of-concept study using Comet-ReCom, an improved version of Comet-PTM. Comet-ReCom increased identification performance of Comet-PTM by 68%. This increased performance of Comet-ReCom to score the MS/MS spectrum comes in parallel with a significantly better assignation of the monoisotopic peak of the precursor peptide in the MS spectrum, even in cases of peptide coelution. Our data demonstrate that open searches using ultra-tolerant mass windows can benefit from using a semi-supervised approach that takes advantage from previous knowledge on the nature of protein modifications. SIGNIFICANCE: The present study introduces a novel approach to ultra-tolerant database search, which employs prior knowledge of post-translational modifications (PTMs) to improve identification of modified peptides. This method addresses the limitations related to experimental errors and precursor mass assignation of previous open-search methods. Thus, it enables the study of the biological significance of a wider variety of PTMs, including unknown or unexpected modifications that may have gone unnoticed using non-supervised search methods. J Proteomics. 2023 Sep 15:287:104968. http://hdl.handle.net/20.500.12105/16576 37463622 10.1016/j.jprot.2023.104968 1876-7737 Journal of proteomics ReCom: A semi-supervised approach to ultra-tolerant database search for improved identification of modified peptides.