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The Origin of Minus-end Directionality and Mechanochemistry of Ncd Motors

Overview of attention for article published in PLoS Computational Biology, November 2012
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Title
The Origin of Minus-end Directionality and Mechanochemistry of Ncd Motors
Published in
PLoS Computational Biology, November 2012
DOI 10.1371/journal.pcbi.1002783
Pubmed ID
Authors

Biman Jana, Changbong Hyeon, José N. Onuchic

Abstract

Adaptation of molecular structure to the ligand chemistry and interaction with the cytoskeletal filament are key to understanding the mechanochemistry of molecular motors. Despite the striking structural similarity with kinesin-1, which moves towards plus-end, Ncd motors exhibit minus-end directionality on microtubules (MTs). Here, by employing a structure-based model of protein folding, we show that a simple repositioning of the neck-helix makes the dynamics of Ncd non-processive and minus-end directed as opposed to kinesin-1. Our computational model shows that Ncd in solution can have both symmetric and asymmetric conformations with disparate ADP binding affinity, also revealing that there is a strong correlation between distortion of motor head and decrease in ADP binding affinity in the asymmetric state. The nucleotide (NT) free-ADP (φ-ADP) state bound to MTs favors the symmetric conformation whose coiled-coil stalk points to the plus-end. Upon ATP binding, an enhanced flexibility near the head-neck junction region, which we have identified as the important structural element for directional motility, leads to reorienting the coiled-coil stalk towards the minus-end by stabilizing the asymmetric conformation. The minus-end directionality of the Ncd motor is a remarkable example that demonstrates how motor proteins in the kinesin superfamily diversify their functions by simply rearranging the structural elements peripheral to the catalytic motor head domain.

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Geographical breakdown

Country Count As %
Netherlands 1 3%
Unknown 36 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 32%
Researcher 4 11%
Professor > Associate Professor 4 11%
Student > Master 4 11%
Professor 3 8%
Other 5 14%
Unknown 5 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 38%
Physics and Astronomy 5 14%
Chemistry 5 14%
Biochemistry, Genetics and Molecular Biology 4 11%
Computer Science 1 3%
Other 2 5%
Unknown 6 16%