Back

Coevolution in Small Heat Shock Protein 1 (HSPB1) is Promoted by Interactions between the Alpha-Crystallin Domain and the Disordered Regions

Racigh, V.; Fornasari, M. S.; Rodriguez Sawicki, L.; Bravo, F. N. E.

2024-12-04 biochemistry
10.1101/2024.12.03.626587 bioRxiv
Show abstract

Human HSPB1, a member of the small heat shock protein (sHSP) family, functions as an ATP-independent molecular chaperone crucial for protein quality control and is implicated in several pathologies, including Charcot-Marie-Tooth neuropathy. This study investigates the coevolution of the disordered N-terminal and C-terminal regions (NTR and CTR) with the structured Alpha-Crystallin domain (ACD) of human HSPB1, focusing on interactions that regulate its chaperone activity. Using a manually curated dataset of HSPB1 orthologs, the composition of critical motifs within the NTR (6VPFSLL11) and CTR (179ITIPV183) that interact with the ACD was analyzed and evolutionary rates per site for the human HSPB1 sequence were estimated. Additionally, structural modeling with AlphaFold 2 was employed to assess the prevalence of these contacts in human HSPB1 models. The results reveal that while the disordered regions globally evolve faster than the structured ACD, specific residues within the 6VPFSLL11 and 179ITIPV183 motifs exhibit reduced evolutionary rates, reflecting evolutionary constraints imposed by the conservation of the proteins function. Structural modeling further indicates that coevolutionary-like information about the interaction between the 6VPFSLL11 motif and the ACD is encoded in the multiple sequence alignment used by Alphafold 2. Altogether, these findings suggest that the disordered regions and the ACD of human HSPB1 likely coevolved, preserving interactions crucial for its chaperone activity self-regulation. This evolutionary mechanism may also be extended to other sHSP featuring interacting motifs in the NTR, CTR, or both, and provides a framework to elucidate why pathogenic variants occurring in regions involved in these contacts contribute to disease.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Biomolecules
100 papers in training set
Top 0.1%
15.1%
2
Journal of Molecular Biology
232 papers in training set
Top 0.1%
9.8%
3
International Journal of Molecular Sciences
494 papers in training set
Top 0.3%
9.7%
4
PLOS ONE
5266 papers in training set
Top 19%
9.7%
5
International Journal of Biological Macromolecules
76 papers in training set
Top 0.1%
8.9%
50% of probability mass above
6
Protein Science
246 papers in training set
Top 0.5%
6.7%
7
Computational and Structural Biotechnology Journal
242 papers in training set
Top 1%
4.0%
8
Archives of Biochemistry and Biophysics
15 papers in training set
Top 0.1%
4.0%
9
Scientific Reports
3612 papers in training set
Top 42%
2.4%
10
Proteins: Structure, Function, and Bioinformatics
88 papers in training set
Top 0.6%
2.1%
11
Biochemical Journal
91 papers in training set
Top 0.6%
2.1%
12
FEBS Letters
47 papers in training set
Top 0.2%
1.3%
13
The FEBS Journal
93 papers in training set
Top 1%
1.3%
14
Biochimie
25 papers in training set
Top 0.4%
1.3%
15
PLOS Computational Biology
1863 papers in training set
Top 17%
1.1%
16
Bioscience Reports
27 papers in training set
Top 1.0%
1.1%
17
Biochemical and Biophysical Research Communications
84 papers in training set
Top 2%
1.1%
18
Frontiers in Molecular Biosciences
102 papers in training set
Top 2%
1.0%
19
Molecules
39 papers in training set
Top 1%
0.9%
20
Cell Stress and Chaperones
11 papers in training set
Top 0.1%
0.8%
21
FEBS Open Bio
31 papers in training set
Top 0.9%
0.8%
22
Biochemistry
148 papers in training set
Top 2%
0.8%
23
Molecular Immunology
14 papers in training set
Top 0.3%
0.6%
24
Viruses
332 papers in training set
Top 5%
0.6%
25
ACS Omega
105 papers in training set
Top 4%
0.6%
26
ChemBioChem
55 papers in training set
Top 1%
0.6%