Challenges in Protein Identification by LC-MS/MS and the need for Active Form-Specific FASTA files

Abstract

Protein identification by Nano liquid chromatography coupled to mass spectrometry (Nano LC-MS/MS) is a powerful technique widely used in proteomics to identify and profile proteins in complex biological samples. However, this approach often faces challenges when attempting to identify proteins with different isoforms or active forms, especially when using large, non-specific databases such as whole organism proteomes. This study highlights the critical importance of using curated FASTA files representing the active form of proteins, rather than whole organism databases, to achieve accurate protein identification. In our study, we attempted to match protein sequences for 14 specific proteins - Ercc6l2, Gdf15, IL-1b, IL-6, Myo18b, Peak1, Zfp113, Rb1cc1, Celsr2, Casp1, Akt1, Ceacam5, Cpne1, and Rsc1a1 - using their corresponding active form FASTA files. When querying the entire Mus musculus (mouse) proteome database, protein identification often failed due to the inclusion of inactive isoforms, precursor sequences, and redundant proteins. However, by focusing on FASTA files tailored to the active forms of these proteins, we significantly improved our identification success rate. These results highlight the need to use targeted, functionally relevant protein sequences to improve the precision of Nano LC-MS/MS analysis. Such strategies can improve both identification accuracy and sensitivity, thereby reducing false positives and increasing confidence in proteomic workflows.