Deep homology and design of proteasome chaperone proteins in Candida auris
Rapala, J. R.; Siddiq, M.; Wittkopp, P. J.; O'Meara, M. J.; O'Meara, T. R.
Show abstract
A central tenet of biology is that protein structure mediates the sequence-function relationship. Recently, there has been excitement about the promise of advances in protein structure modeling to generate hypotheses about sequence-structure-function relationships based on successes with controlled benchmarks. Here, we leverage structural similarity to identify rapidly evolving proteasome assembly chaperones and characterize their function in the emerging fungal pathogen Candida auris. Despite the large sequence divergence, we demonstrate conservation of structure and function across hundreds of millions of years of evolution, representing a case of rapid neutral evolution. Using the functional constraints on structure from these naturally evolved sequences, we prospectively designed de novo chaperones and demonstrate that these artificial proteins can rescue complex biological processes in the context of the whole cell.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Guanidine hydrochloride reactivates an ancient septin hetero-oligomer assembly pathway in budding yeast 96%
- Systematic genetic characterization of the human PKR kinase domain highlights its functional malleability to escape a poxvirus substrate mimic 96%
- Function and firing of the Streptomyces coelicolor contractile injection system requires the membrane protein CisA 95%
Similar papers in this journal
Similar papers in this journal
- Three small partner proteins facilitate the type VII-dependent secretion export of an antibacterial nuclease 96%
- Functional diversification despite structural congruence in the HipBST toxin-antitoxin system of Legionella pneumophila 95%
- Secreted retropepsin-like enzymes are essential for stress tolerance and biofilm formation in Pseudomonas aeruginosa 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.