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Updated: Dec 14, 2025

Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
Published on: March 31, 2022
Residue interaction dynamics in Vaucheria aureochrome1 light-oxygen-voltage: Bridging theory and experiments
Anwesha Deb1, Rajdeep Kaur Grewal2, Soumen Roy2
1Department of Life Sciences, Presidency University, Kolkata, India.
Abstract:
Allosteric communication is the basis of signaling and information transfer. Collective interactions between amino acid residues, which are spatially distributed in the three dimensional structure of a protein molecule, form the basis of allosteric network. While the construction of residue interaction graphs (RIG) is based on static crystal structures of proteins, it is important to extract information on protein dynamics to understand allostery. Therefore, quantitative analysis of RIG based on the framework of differential network (DN), is immensely helpful in identifying key amino acid residue interactions within such communication pathways. While the simultaneous availability of protein structures from two different states is essential for DN, there are additional challenges. Crystallographic artifacts like nonbiological dimeric arrangements within the crystal lattice automatically influence the construction and eventually the interpretation of RIG. Therefore, experimental validation of predictions from the analyses of RIG is naturally scarce in the literature. Herein, we study the photo sensor domain of the signaling photoreceptor transcription factor, aureochrome1, to understand light-driven signaling. We perform direct experiments to verify the predictions from RIG using the machinery of DN. However, the agreement leaves scope for improvement. We then discuss the notion of quaternary structure alignment to obtain a biologically meaningful dimer. Thence, we reconstruct the RIG and reanalyze the modified structure. Results of these reanalyses render far superior agreement with experiments. Therefore, this notion of addressing crystallographic biases provides a fresh yet general approach for reconciliation of theory and experiments. It is applicable beyond the present case to all signaling proteins in general.
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