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Joint analysis of dynamically correlated networks and coevolved residue clusters : large-scale analysis and methods for predicting the effects of genetic disease associated mutations

Abstract : We presented COMMA, a method to describe and compare the dynamical architectures of different proteins or different variants of the same protein. COMMA extracts dynamical properties from conformational ensembles to identify communication pathways, chains of residues linked by stable interactions that move together, and independent cliques, clusters of residues that fluctuate in a concerted way. It provides a description of the infostery of a protein or protein complex that goes beyond the notions of chain, domain and secondary structure element/motif, and beyond classical measures of how a protein moves and/or changes its shape. We showed the efficiency of our approach in providing mechanistic insights on the effects of deleterious mutations by pinpointing residues playing key roles in the propagation of these effects. In addition COMMA reveals a link between clusters of coevolving residues and networks of dynamical correlations. It enables to contrast the different types of communication occurring between residues and to hierarchise the different regions of a protein depending on their communication efficiency. Furthermore, we presented an approach to exploit both the sequences and structural dynamics to predict a mutational landscape. The discussion of examples, revealed physical interpretation on how the study of conservation brings significant insights on the sensitivity of conserved positions to mutations. Our proposed method, can detect protein regions that are prone to disorder or substantial conformational rearrangements. Moreover, it enabled us to suggest mutations that regulate the stability of the disordered coiled-coils.
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Yasaman Karami. Joint analysis of dynamically correlated networks and coevolved residue clusters : large-scale analysis and methods for predicting the effects of genetic disease associated mutations. Biotechnology. Université Pierre et Marie Curie - Paris VI, 2016. English. ⟨NNT : 2016PA066375⟩. ⟨tel-01638201⟩

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