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Soft disorder modulates the assembly path of protein complexes
Open accessPreprint — published as 10.1371/journal.pcbi.1010713 · Paper page
Abstract
The relationship between interactions, flexibility and disorder in proteins has been explored from many angles over the years: folding upon binding, flexibility of the core relative to the periphery, entropy changes, etc. In this work, we provide statistical evidence for the involvement of highly mobile and disordered regions in complex assembly. We ordered the entire set of X-ray crystallographic structures in the Protein Data Bank into hierarchies of progressive interactions involving identical or very similar protein chains, yielding 40205 hierarchies of protein complexes with increasing numbers of partners. We then examine them as proxies for the assembly pathways. Using this database, we show that upon oligomerisation, the new interfaces tend to be observed at residues that were characterised as softly disordered (flexible, amorphous or missing residues) in the complexes preceding them in the hierarchy. We also rule out the possibility that this correlation is just a surface effect by restricting the analysis to residues on the surface of the complexes. Interestingly, we find that the location of soft disordered residues in the sequence changes as the number of partners increases. Our results show that there is a general mechanism for protein assembly that involves soft disorder and modulates the way protein complexes are assembled. This work highlights the difficulty of predicting the structure of large protein complexes from sequence and emphasises the importance of linking predictors of soft disorder to the next generation of predictors of complex structure. Finally, we investigate the relationship between the Alphafold2’s confidence metric pLDDT for structure prediction in unbound versus bound structures, and soft disorder. We show a strong correlation between Alphafold2 low confidence residues and the union of all regions of soft disorder observed in the hierarchy. This paves the way for using the pLDDT metric as a proxy for predicting interfaces and assembly paths. Availability: All the data used for these analyses (hierarchies of interactions and soft disorder) are available at the website http://www.lcqb.upmc.fr/softdisorder-assembly/ . Author summary: Both flexibility and intrinsic disorder are used as regulatory mechanisms in proteins. They can alter the spatial positions of important recognition sites, and increased mobility appears to facilitate ligand binding through conformational selection. In this work, we show statistical evidence that soft disorder is directly involved in the process of protein assembly and that migration of soft disorder after binding gives rise to new or altered functions in the protein complex. Given the impressive progress that AlphaFold2 has made in protein structure prediction in recent years, this work highlights the importance of also correctly predicting conformational heterogeneity, mobility and intrinsic disorder in order to access the full functional repertoire and interaction network of a given protein.
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Citations
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
AlphaFold and Implications for Intrinsically Disordered Proteins
Ruff, K. M., & Pappu, R. V. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167208 · Cited by 635 · cited 2×
“In [3, 9], it has been observed that the regions where intrinsic disorder is present correspond to those with high uncertainty for AF2.”
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Metadata
- Authors
- Seoane, B., & Carbone, A.
- Affiliations
- Universidad Complutense de Madrid (ES)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Seoane, Beatriz
- Venue
- PLoS Computational Biology
- Publisher
- openRxiv
- Published
- 2022-03-07
- Volume
- 18
- Issue
- 11
- Pages
- e1010713-e1010713
- ISSN
- 1553-734X (ISSN-L)
- PMC
- PMC9714922
- OpenAlex
- W4309231812
- Cited by
- 13
- References
- 2
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 4 · 2023: 3
- FWCI
- 0.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Fundación Banco Santander (PR44/21-29937)
- Banco Santander (PR44/21, PR44/21-29937)
- Comunidad de Madrid (2019-T1/TIC-12776, PGC2018)
- Agence Nationale de la Recherche (ANRS–AAP2021CSS12-D21342)
- Universidad Complutense de Madrid (PR44/21-29937, 2019-T1/TIC-12776, PID2021-125506NA-I00)
- Ministerio de Ciencia e Innovación (PID2021-125506NA-I00)
- European Regional Development Fund (PID2021-125506NA-I00)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Keywords
- protein disorder, protein complex formation, assembly pathways, oligomerization, protein interfaces, protein flexibility, protein surface residues, Protein Data Bank, AlphaFold2, protein-protein interaction
- MeSH terms
- Mental Processes, Crystallography, X-Ray, Entropy, Databases, Protein
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