Comparação de redes de interação de resíduos (RINs) como uma forma de avaliar a variação conformacional de proteínas

Abstract

Changes in the amino acid sequence may result in alterations in the three-dimensional protein structure, which may lead to partial or complete loss of function. One way to represent the chemical interactions between all amino acids in a protein is through the construction of residue interaction networks (RINs). In RINs, a graph represents the protein 3D structure, with the nodes as amino acid residues, and the edges as the physicochemical interactions between amino acids. We hypothesize that the comparison between RINs of the same protein in different conformations can be used to evaluate the effects of mutations and polymorphisms, as well as for the analysis and validation of theoretical protein models. Therefore, the present work aimed to build a tool to compare different RINs for a protein and to use such data to estimate conformational differences between proteins and also validate models generated by homology modeling. RINs were created using the RING 2.0 (Residue Interaction Network Generator) program. The tool developed for this purpose, called Comparator of Residue Interaction Networks (CoRINs), compares all RIN nodes generated from different structure files (PDBs) of the same protein, taking into account position, chain and residue, as well as their interactions with the other amino acids. The tool also presents a plot that estimates the variation of interactions formed by each residue, which we propose as an estimate for the conformational alterations of that protein site, from a set of compared PDBs. As a possible application for this tool, we used a dataset with oncogenes and tumor suppressor genes with their respective reported mutations mapped according to the connectivity deviation of each residue. Then we retrieved the different conformations for each resulting protein from a bank of structural conformers and constructed the RINs using the software RING 2.0 and compared them with CoRINs. The results show that mutations occurring in the tested oncogenes are more likely to occur in protein sites with a more significant deviation in the mean number of chemical interactions. Additionally, most of these genes’ mutations annotated as pathogenic and associated with clinical cancer cases occurred at sites with the most significant changes in chemical and physical interactions. These results demonstrate that the CoRINs tool can be useful in identifying non-covalent interactions essential for protein structure maintenance and in evolutionary studies, such as in the maintenance of homologous proteins function with high sequence divergence, as well as for the comparison and validation of theoretical structural models.