Computational design of a protein family that adopts two well-defined and structurally divergent de novo folds
Wei, K. Y.; Moschidi, D.; Bick, M. J.; Nerli, S.; McShan, A. C.; Carter, L. P.; Huang, P.-S.; Fletcher, D. A.; Sgourakis, N. G.; Boyken, S. E.; Baker, D.
Show abstract
The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used to de novo design proteins that fold to a single state with a deep free energy minima (Huang et al., 2016), and to reengineer natural proteins to alter their dynamics (Davey et al., 2017) or fold (Alexander et al., 2009), the de novo design of closely related sequences which adopt well-defined, but structurally divergent structures remains an outstanding challenge. Here, we design closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations -- one short ([~]66 [A] height) and the other long ([~]100 [A] height) -- reminiscent of the conformational transition of viral fusion proteins (Ivanovic et al., 2013; Podbilewicz, 2014; Skehel and Wiley, 2000). Crystallographic and NMR spectroscopic characterization show that both the short and long state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large scale conformational switches between structurally divergent forms.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps 96%
- A Suite of Designed Protein Cages Using Machine Learning Algorithms and Protein Fragment-Based Protocols 96%
- Catalytic cycling of human mitochondrial Lon protease 95%
Similar papers in this journal
- Design and characterization of a protein fold switching network 96%
- Hierarchical design of multi-scale protein complexes by combinatorial assembly of oligomeric helical bundle and repeat protein building blocks 96%
- Structural basis of undecaprenyl phosphate glycosylation leading to polymyxin resistance in Gram-negative bacteria 96%
Similar papers in this journal
- Structure of the Disulfide-rich Modules of a Striking Tandem Repeat Protein, Avian Cysteine-Rich Eggshell Membrane Protein 95%
- AlphaFold accurately predicts distinct conformations based on oligomeric state of a de novo designed protein 95%
- The role of evolutionarily metastable oligomeric states in the optimization of catalytic activity 95%
Similar papers in this journal
"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.