Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.
Madsen CT, Refsgaard JC, Teufel FG, et al. Combining mass spectrometry and machine learning to discover bioactive peptides. Nat Commun. 2022;13(1):6235.
Background: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) occurs in 10%-30% of patients with RA, and interstitial lung disease (ILD) is associated with increased mortality in up to 10% of patients with RA. The pathogenesis of RA-ILD is virtually unknown. The aim of this study is to investigate the proteins related to UIP pattern by comparing to OP pattern in RA-ILD using proteome analysis of bronchoalveolar lavage fluid (BALF).
Methods: Proteomic differences in BALF were compared between the UIP pattern and OP pattern by examining BALF from 5 patients with the UIP pattern and 7 patients with the OP pattern by two-dimensional gel electrophoresis and mass spectrometry.
Results: In individual comparisons of BALF samples, the levels of the protein gelsolin and Ig kappa chain C region were significantly higher in the UIP pattern than in the OP pattern. In contrast, the levels of α-1 antitrypsin, CRP, haptoglobin β, and surfactant protein A (isoform number 5) were all significantly higher in the OP pattern than in the UIP pattern. Gelsolin was cleaved into two fragments, a C-terminal half and N-terminal half, and the levels of both were significantly higher in the UIP pattern than in the OP pattern.
Suhara K, Miyazaki Y, Okamoto T, Ishizuka M, Tsuchiya K, Inase N. Fragmented gelsolins are increased in rheumatoid arthritis-associated interstitial lung disease with usual interstitial pneumonia pattern. Allergology International. 2016;65(1):88-95.
|006-84||Gelsolin (160-169) / PBP10 (Human, Rat, Mouse)||200μg||$185|
|006-86||Gelsolin (567-625), prepro (Mouse)||100μg||$395|
|006-88||Gelsolin (569-627), prepro (Human)||100μg||$395|
Social Network Confirmation