» Articles » PMID: 26173036

The Contribution of Missense Mutations in Core and Rim Residues of Protein-Protein Interfaces to Human Disease

Overview
Journal J Mol Biol
Publisher Elsevier
Date 2015 Jul 15
PMID 26173036
Citations 59
Authors
Affiliations
Soon will be listed here.
Abstract

Missense mutations at protein-protein interaction sites, called interfaces, are important contributors to human disease. Interfaces are non-uniform surface areas characterized by two main regions, "core" and "rim", which differ in terms of evolutionary conservation and physicochemical properties. Moreover, within interfaces, only a small subset of residues ("hot spots") is crucial for the binding free energy of the protein-protein complex. We performed a large-scale structural analysis of human single amino acid variations (SAVs) and demonstrated that disease-causing mutations are preferentially located within the interface core, as opposed to the rim (p<0.01). In contrast, the interface rim is significantly enriched in polymorphisms, similar to the remaining non-interacting surface. Energetic hot spots tend to be enriched in disease-causing mutations compared to non-hot spots (p=0.05), regardless of their occurrence in core or rim residues. For individual amino acids, the frequency of substitution into a polymorphism or disease-causing mutation differed to other amino acids and was related to its structural location, as was the type of physicochemical change introduced by the SAV. In conclusion, this study demonstrated the different distribution and properties of disease-causing SAVs and polymorphisms within different structural regions and in relation to the energetic contribution of amino acid in protein-protein interfaces, thus highlighting the importance of a structural system biology approach for predicting the effect of SAVs.

Citing Articles

Decoding the functional impact of the cancer genome through protein-protein interactions.

Fu H, Mo X, Ivanov A Nat Rev Cancer. 2025; 25(3):189-208.

PMID: 39810024 DOI: 10.1038/s41568-024-00784-6.


Restoring adapter protein complex 4 function with small molecules: an in silico approach to spastic paraplegia 50.

Francisco S, Lamacchia L, Turco A, Ermondi G, Caron G, Rossi Sebastiano M Protein Sci. 2024; 34(1):e70006.

PMID: 39723768 PMC: 11670165. DOI: 10.1002/pro.70006.


Genetic variants associated with age-related episodic memory decline implicate distinct memory pathologies.

Ali A, Milman S, Weiss E, Gao T, Napolioni V, Barzilai N Alzheimers Dement. 2024; 21(1):e14379.

PMID: 39559945 PMC: 11775541. DOI: 10.1002/alz.14379.


MTR3D-AF2: Expanding the coverage of spatially derived missense tolerance scores across the human proteome using AlphaFold2.

Kovacs A, Portelli S, Silk M, Rodrigues C, Ascher D Protein Sci. 2024; 33(8):e5112.

PMID: 39031445 PMC: 11258768. DOI: 10.1002/pro.5112.


Proteome-scale characterisation of motif-based interactome rewiring by disease mutations.

Kliche J, Simonetti L, Krystkowiak I, Kuss H, Diallo M, Rask E Mol Syst Biol. 2024; 20(9):1025-1048.

PMID: 39009827 PMC: 11369174. DOI: 10.1038/s44320-024-00055-4.


References
1.
Gong S, Blundell T . Structural and functional restraints on the occurrence of single amino acid variations in human proteins. PLoS One. 2010; 5(2):e9186. PMC: 2820541. DOI: 10.1371/journal.pone.0009186. View

2.
Kucukkal T, Petukh M, Li L, Alexov E . Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins. Curr Opin Struct Biol. 2015; 32:18-24. PMC: 4511717. DOI: 10.1016/j.sbi.2015.01.003. View

3.
Adzhubei I, Schmidt S, Peshkin L, Ramensky V, Gerasimova A, Bork P . A method and server for predicting damaging missense mutations. Nat Methods. 2010; 7(4):248-9. PMC: 2855889. DOI: 10.1038/nmeth0410-248. View

4.
Kumar S, Nussinov R . Salt bridge stability in monomeric proteins. J Mol Biol. 1999; 293(5):1241-55. DOI: 10.1006/jmbi.1999.3218. View

5.
Thorn K, Bogan A . ASEdb: a database of alanine mutations and their effects on the free energy of binding in protein interactions. Bioinformatics. 2001; 17(3):284-5. DOI: 10.1093/bioinformatics/17.3.284. View