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Detalle de: Structural and computational characterization of disease-related mutations involved in protein-protein interfaces

Title Structural and computational characterization of disease-related mutations involved in protein-protein interfaces
Abstract

One of the known potential effects of disease-causing amino acid substitutions in proteins is to modulate protein-protein interactions (PPIs). To interpret such variants at the molecular level and to obtain useful information for prediction purposes, it is important to determine whether they are located at protein-protein interfaces, which are composed of two main regions, core and rim, with different evolutionary conservation and physicochemical properties. Here we have performed a structural, energetics and computational analysis of interactions between proteins hosting mutations related to diseases detected in newborn screening. Interface residues were classified as core or rim, showing that the core residues contribute the most to the binding free energy of the PPI. Disease-causing variants are more likely to occur at the interface core region rather than at the interface rim (p < 0.0001). In contrast, neutral variants are more often found at the interface rim or at the non-interacting surface rather than at the interface core region. We also found that arginine, tryptophan, and tyrosine are over-represented among mutated residues leading to disease. These results can enhance our understanding of disease at molecular level and thus contribute towards personalized medicine by helping clinicians to provide adequate diagnosis and treatments.

Apa Reference Navío, D., Rosell, M., Aguirre, J., de la Cruz, X., & Fernández-Recio, J. (2019). Structural and Computational Characterization of Disease-Related Mutations Involved in Protein-Protein Interfaces. International Journal of Molecular Sciences, 20(7), 1583. 10.3390/ijms20071583
Doi 10.3390/ijms20071583
Publication Date 29 Mar 2019
Publication Type Article
Researcher Juan Fernández Recio
Ontology Protein-Protein Interactions, Medicine
Research Groups Structural Bioinformatics, Modeling and Biological Mechanisms
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