biostudies-literatureUnknown24(1)Beslic DMonoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody-antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to idenBriefings in bioinformaticsbbac542https://www.ebi.ac.uk/biostudies/studies/S-EPMC9851299biostudies-literatureComprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly.PMC9851299Renard BYWeller MGBeslic DMuth TTscheuschner GfalseComprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly.Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody-antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to iden2023-01-01T00:00:00Z2023 Jan2026-03-18T13:45:09.618Z2025-04-04T11:33:16.844ZS-EPMC98512993654580410.1093/bib/bbac542