Understanding protein structural excursions using residue networks and implications on biological function

PhD;2023;Molecular Biophysics Unit

The information required for a protein structure to fold into the native conformation is encoded in its sequence. Studying protein structures help to understand their biological function. Molecular interactions between residues of the same protein and across interacting macromolecules are necessary for a protein to perform its function. The residues that are involved in protein function along with their interactions are known to be conserved during evolution. Non-covalent molecular interaction between the residues of a protein stabilise the protein structure in a given conformation. Based on the nature of these interactions there is variability and an inherent flexibility in protein structure. The residue-residue interactions making up the structure topology can be better studied with the help of structural networks that are a node edge representation of their internal connectivity. The concept of a protein structural network is to capture these inter-residue interactions mathematically such that they can be better studied and any change in these parameters can be quantified. This connectivity is crucial in understanding the mechanism of molecular functions performed by proteins. Employing structural networks, we have outlined the use of several network parameters and performed the comparison of graph spectra to determine how they vary across an ensemble of multiple conformers, when perturbations are introduced into the system such as transient associations and disease-causing mutations. The method of spectral comparison has been improved for better comparison across homologous proteins. The new metric quantifies the change in graphs even including those sites that are not well superposable across homologous proteins. It is validated as a beneficial tool to study the relationship between homologous proteins. The methods employed here also help in better understanding structure function relationships and have applications in drug.