The network of stabilizing contacts in proteins studied by coevolutionary data

Abstract

The primary structure of proteins, that is their sequence, represents one of the most abundant set of experimental data concerning biomolecules. The study of correlations in families of co--evolving proteins by means of an inverse Ising--model approach allows to obtain information on their native conformation. Following up on a recent development along this line, we optimize the algorithm to calculate effective energies between the residues, validating the approach both back-calculating interaction energies in a model system, and predicting the free energies associated to mutations in real systems. Making use of these effective energies, we study the networks of interactions which stabilizes the native conformation of some well--studied proteins, showing that it display different properties than the associated contact network.

References in corpus (1)

• Identification of direct residue contacts in protein-protein interaction by message passing

Cited by in corpus (9)

• Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1
• Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences
• Improving contact prediction along three dimensions
• Benchmarking inverse statistical approaches for protein structure and design with exactly solvable models
• Statistical physics of interacting proteins: impact of dataset size and quality assessed in synthetic sequences
• Comparing spatial networks: A 'one size fits all' efficiency-driven approach
• Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale
• A method for partitioning the information contained in a protein sequence between its structure and function
• Capturing coevolutionary signals in repeat proteins