Subsets of slow dynamic modes reveal global information sources as allosteric sites
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Date
2022
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Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022.
Abstract
Allostery is a crucial biological regulation mechanism, and dynamic information flow offers a framework to characterize allosteric interactions in causal links. Here, using a novel application of the Transfer Entropy (TE) calculations based on the Gaussian Network Model (GNM), it has been demonstrated how the dissection of dynamic information into subsets of slow dynamic modes reveals various layers of multi-directional allosteric pathways that are intrinsic in a particular protein structure. The degree of collectivity (Col) in the information transfer of residues with their TE values (TECol score) in these subsets of slow modes identifies particular residues as potent effectors and global information sources having a strong dynamic capacity to collectively disseminate information to other residues in the protein structure. These information source residues are linked to known active and allosteric sites, as demonstrated by aspartate transcarbamoylase (ATCase), Na+ /K+ -adenosine triphosphatase (Na+ /K+ -ATPase), and human transient receptor potential melastatin 2 (TRPM2), along with a dataset of 20 proteins. These specific residues provide feasible binding sites for structure-based rational drug design since they together affect/control others and direct pathways of allosteric communication.