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We present FoxNovo, a hybrid deep learning-combinatorial framework for de novo sequencing of immunopeptides trained on a large-scale HLA-I immunopeptidomics dataset assembled and reprocessed from publ

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The global scenario of antimicrobial resistance is alarming, and the development of new drugs has not appeared to make substantial progress. The constraints on drug discovery are due to difficultie...

De novo peptide sequencing using LC–MS/MS enables database-independent sequence determination and facilitates the discovery of bioactive peptides and biomarkers in untargeted peptidomics. However, conventional MS/MS analyses often produce fragment ions that are insufficient for complete sequencing. Here, we established an LC–MS/MS workflow using N-succinimidyl 7-methoxycoumarin-3-carboxylate (Me-Cou) as an N-terminal tag to improve de novo sequencing performance. Me-Cou derivatization generated highly informative fragment ions, particularly b1–b3 ions, for (Gly)4 at 1 μmol/L, surpassing the performance of established tags, such as 2,4,6-trinitrobenzenesulfonic acid, 3-aminopyridyl-hydroxy-succinimidyl carbamate, and N-succinimidyl [tris(2,4,6-trimethoxyphenyl)phosphonio]acetate bromide. The Me-Cou tag also enabled confident sequencing of (Gly)10, generating abundant b1–b9 ions. Notably, intact de novo sequencing identified 74 peptides with 32 misidentified peptides that were not included in a 132-standard peptide mixture (86 dipeptides and 46 oligopeptides). However, all peptides were correctly identified using Me-Cou-aided de novo sequencing with no misidentification, demonstrating high specificity and accuracy. Additionally, Me-Cou-aided de novo sequencing successfully identified 328 peptides in casein peptone, all of which were assigned as casein protein fragments. Overall, Me-Cou-based LC–MS/MS significantly enhanced peptide detection and the characterization of sequence diversity compared with intact analysis. This methodology is a promising strategy for untargeted peptidomics, enabling comprehensive characterization of endogenous peptides in both protein hydrolysates and biological fluids.

A nickel-modified nanopore enables simultaneous, unambiguous identification of amino acids and peptides. Direct analysis or hydrolysis-based sequencing can be used for profiling and reconstruction, an...

Protein synthesis is among the most energy-demanding processes in a cell. Yet, some proteins are synthesized and immediately degraded. This may seem like a futile cycle, but it’s a remarkable…

Genomic and microscopy evidence shows that the Bacillaceae, assumed to only stain Gram-positive, actually have some lineages staining Gram-negative, yet unexpectedly maintaining a thick wall and no ou...

Data-independent acquisition mass spectrometry (DIA-MS) has emerged as a key technology in quantitative proteomics. Here, the authors introduce DIA-BERT, a transformer model pre-trained on existing DI...

Official repo for pUniFind, the first open de novo sequencing and open database search rescoring deep learning model. - pFindStudio/pUniFind

Peptides are sequenced by converting each amino acid into amplifiable DNA barcodes.

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In a mouse model, environmental immunostimulation in early life led to cross-reactive adaptive immune memory and reduced type II immune responses to allergens, indicating a mechanistic relationship be...

Psoriasis, a chronic inflammatory disease, is associated with metabolic disturbances and oxidative stress. Alpha-lipoic acid (ALA), a potent antioxidant with anti-inflammatory properties, may offer th...

Building custom data analysis platforms has traditionally required extensive software engineering expertise, limiting access for many researchers. Here, I demonstrate that modern large language models...