ArticleProteins2025
Exploring the Hemoglobin T to R2 Path Using Gaussian Elastic Network Correlation Map Distance.
Article in Proteins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Proteins are dynamic and undergo conformational changes. These changes may affect the motions executed by different regions of the proteins and are reflected in the motion correlation map. A method to accurately measure these changes is presented and exemplified on a set of tetrameric Hemoglobin structures. Using the Gaussian Network Model, the motion correlation map of each structure is calculated. The root of the square differences between the elements of the map of different structures is used to calculate their distance. Using this novel distance, the path between the T and R2 states is calculated. The intermediates along the path show gradual inter and intradimer correlation changes. The correlation of each subunit with the other in the same dimer becomes increasingly positive upon the T → R2 transition. Meanwhile, the interdomain correlation, as seen from the interface (α1β2 / β1α2), becomes increasingly negative. In addition, these distances are used to cluster the Hb structures. The newly suggested distance does not correlate with structure-based distances and offers a new way to explore the conformational space of proteins.
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