![]() ![]() The dCNA path analysis method is general and can be easily applied to diverse allosteric systems. Our results are robust against small variations of parameters and details of the network construction. We also observed that the fine-tuning of allosteric coupling depends on the strength of effector binding. Interestingly, different binding processes in the thermodynamic cycle generally use a similar group of residues in defining the allosteric communication pathways, with some residues being more specific to a certain binding process. Using the dCNA path analysis along with conventional analyses, we gain several new biological insights into IGPS. By contrast, some of the most important allosteric residues are not captured using methods that do not consider conformational changes, such as those that solely rely on examining the individual bound or unbound state of the protein. The method identifies key experimentally verified allosteric residues in imidazole glycerol phosphate synthase (IGPS), a well-studied allosteric protein system. VMD makes extensive use of multi-core processors and GPU acceleration to speed up computationally demanding analysis and visualization tasks including key structure and trajectory analysis features, interactive molecular dynamics, and high-quality ray tracing of molecular scenes. The method implements the suboptimal path analysis in the framework of the difference contact network analysis or dCNA. ![]() Conformational changes are modeled explicitly since they modulate the network of residue-residue interactions, which could propagate allosteric signals between two or more distal sites. ![]() We introduce a computational method to elucidate allosteric communication pathways, comprising critical allosteric residues, in biomolecules by taking advantage of conformational changes during a functional process. A prerequisite for allostery is a flexible biomolecule within which two distal sites can communicate via concerted or sequential conformational changes. Allosteric regulation plays a central role in orchestrating diverse cellular processes. ![]()
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