Allosteric regulation in biological systems is of considerable interest given the vast number of proteins that exhibit such behavior. Network models obtained from molecular dynamics simulations have been shown to be powerful tools for the analysis of allostery. In this work, different coarse-grain residue representations (nodes) are used together with a dynamical network model to investigate models of allosteric regulation. This model assumes that allosteric signals are dependent on positional correlations of protein substituents, as determined through molecular dynamics simulations, and uses correlated motion to generate a signaling weight between two given nodes. We examine four types of network models using different node representations in Cartesian coordinates: the (i) residue α-carbons, (ii) the side chain center of mass, (iii) the backbone center of mass, and the entire (iv) residue center of mass. All correlations are filtered by a dynamic contact map that defines the allowable interactions between nodes based on physical proximity. We apply the four models to imidazole glycerol phosphate synthase (IGPS), which provides a well-studied experimental framework in which allosteric communication is known to persist across disparate protein domains (e.g., a protein dimer interface). IGPS is modeled as a network of nodes and weighted edges. Optimal allosteric pathways are traced using the Floyd Warshall algorithm for weighted networks, and community analysis (a form of hierarchical clustering) is performed using the Girvan-Newman algorithm. Our results show that dynamical information encoded in the residue center of mass must be included in order to detect residues that are experimentally known to play a role in allosteric communication for IGPS. More broadly, this new method may be useful for predicting pathways of allosteric communication for any biomolecular system in atomic detail.
ASJC Scopus subject areas
- Computer Science Applications
- Physical and Theoretical Chemistry