Deorphanizing Peptides Using Structure Prediction.

Many endogenous peptides rely on signaling pathways to exert their function, but identifying their cognate receptors remains a challenging problem. We investigate the use of AlphaFold-Multimer complex structure prediction together with transmembrane topology prediction for peptide deorphanization. We find that AlphaFold's confidence metrics have strong performance for prioritizing true peptide-receptor interactions. In a library of 1112 human receptors, the method ranks true receptors in the top percentile on average for 11 benchmark peptide-receptor pairs.

Combining mass spectrometry and machine learning to discover bioactive peptides.

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.

A Two-step Protein Quality Control Pathway for a Misfolded DJ-1 Variant in Fission Yeast.

A mutation, L166P, in the cytosolic protein, PARK7/DJ-1, causes protein misfolding and is linked to Parkinson disease. Here, we identify the fission yeast protein Sdj1 as the orthologue of DJ-1 and calculate by in silico saturation mutagenesis the effects of point mutants on its structural stability. We also map the degradation pathways for Sdj1-L169P, the fission yeast orthologue of the disease-causing DJ-1 L166P protein. Sdj1-L169P forms inclusions, which are enriched for the Hsp104 disaggregase. Hsp104 and Hsp70-type chaperones are required for efficient degradation of Sdj1-L169P. This also depends on the ribosome-associated E3 ligase Ltn1 and its co-factor Rqc1. Although Hsp104 is absolutely required for proteasomal degradation of Sdj1-L169P aggregates, the degradation of already aggregated Sdj1-L169P occurs independently of Ltn1 and Rqc1. Thus, our data point to soluble Sdj1-L169P being targeted early by Ltn1 and Rqc1. The fraction of Sdj1-L169P that escapes this first inspection then forms aggregates that are subsequently cleared via an Hsp104- and proteasome-dependent pathway.