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Collective Dynamics Underlying Allosteric Transitions in Hemoglobin

Overview of attention for article published in PLoS Computational Biology, September 2013
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Title
Collective Dynamics Underlying Allosteric Transitions in Hemoglobin
Published in
PLoS Computational Biology, September 2013
DOI 10.1371/journal.pcbi.1003232
Pubmed ID
Authors

Martin D. Vesper, Bert L. de Groot

Abstract

Hemoglobin is the prototypic allosteric protein. Still, its molecular allosteric mechanism is not fully understood. To elucidate the mechanism of cooperativity on an atomistic level, we developed a novel computational technique to analyse the coupling of tertiary and quaternary motions. From Molecular Dynamics simulations showing spontaneous quaternary transitions, we separated the transition trajectories into two orthogonal sets of motions: one consisting of intra-chain motions only (referred to as tertiary-only) and one consisting of global inter-chain motions only (referred to as quaternary-only). The two underlying subspaces are orthogonal by construction and their direct sum is the space of full motions. Using Functional Mode Analysis, we were able to identify a collective coordinate within the tertiary-only subspace that is correlated to the most dominant motion within the quaternary-only motions, hence providing direct insight into the allosteric coupling mechanism between tertiary and quaternary conformation changes. This coupling-motion is substantially different from tertiary structure changes between the crystallographic structures of the T- and R-state. We found that hemoglobin's allosteric mechanism of communication between subunits is equally based on hydrogen bonds and steric interactions. In addition, we were able to affect the T-to-R transition rates by choosing different histidine protonation states, thereby providing a possible atomistic explanation for the Bohr effect.

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Geographical breakdown

Country Count As %
Czechia 1 3%
Germany 1 3%
Italy 1 3%
Unknown 36 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 10 26%
Student > Doctoral Student 3 8%
Student > Postgraduate 3 8%
Student > Master 3 8%
Other 6 15%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 36%
Chemistry 9 23%
Biochemistry, Genetics and Molecular Biology 5 13%
Physics and Astronomy 2 5%
Computer Science 1 3%
Other 2 5%
Unknown 6 15%