Structural Consequences of Disease‐Related Mutations for Protein–Protein Interactions

Abstract

Mutation of a single amino acid in a protein often has consequences on the interaction with other proteins, which may affect other interaction networks and pathways and ultimately lead to pathological phenotypes. A detailed structural analysis of these altered protein–protein complexes is essential to interpret the impact of a given mutation at the molecular level, which may facilitate intervention with therapeutic purposes. Given current limitations in the structural coverage of the human interactome, computational docking is emerging as a complementary source of information. Structural analysis can help to locate a given mutation at a protein–protein interface, but further characterisation of its impact on binding affinity is needed for a full interpretation. The integration of computational docking methods and energy‐based descriptors is facilitating the characterisation of an increasing number of disease‐related mutations, thus improving our understanding of the consequences of such mutations at the phenotypic level. Key Concepts Protein–protein interactions are key to understand disease at the molecular level. Disease‐related mutations can have significant structural and energetic impact on protein–protein interactions. The 3D structure of a complex is essential to interpret the functional impact of a mutation. Computational docking can provide structural models for protein–protein interactions with no available structure. In addition to structural data, further energetic description is needed to fully interpret the impact of a mutation. Hot‐spot interface residues are causing the greater impact on a protein–protein interaction when mutated. Altered protein–protein interactions are potentially suitable drug targets for therapeutic purposes.