Structure-Guided Directed Evolution of Highly Selective P450-Based Magnetic Resonance Imaging Sensors for Dopamine and Serotonin
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Jasanoff_Structure-guided.pdf
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Author(s)
Brustad, Eric M.
Lelyveld, Victor S.
Snow, Christopher D.
Crook, Nathan
Jung, Sang Taek
Martinez, Francisco M.
Scholl, Timothy J.
Arnold, Frances H.
Jasanoff, Alan Pradip
Date Issued
May 2012
Journal
Journal of Molecular Biology
Publisher
Elsevier
Citation
Brustad, Eric M., Victor S. Lelyveld, Christopher D. Snow, Nathan Crook, Sang Taek Jung, Francisco M. Martinez, Timothy J. Scholl, Alan Jasanoff, and Frances H. Arnold. “Structure-Guided Directed Evolution of Highly Selective P450-Based Magnetic Resonance Imaging Sensors for Dopamine and Serotonin.” Journal of Molecular Biology 422, no. 2 (September 2012): 245–262.
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Author's final manuscript
Abstract
New tools that allow dynamic visualization of molecular neural events are important for studying the basis of brain activity and disease. Sensors that permit ligand-sensitive magnetic resonance imaging (MRI) are useful reagents due to the noninvasive nature and good temporal and spatial resolution of MR methods. Paramagnetic metalloproteins can be effective MRI sensors due to the selectivity imparted by the protein active site and the ability to tune protein properties using techniques such as directed evolution. Here, we show that structure-guided directed evolution of the active site of the cytochrome P450‐BM3 heme domain produces highly selective MRI probes with submicromolar affinities for small molecules. We report a new, high‐affinity dopamine sensor as well as the first MRI reporter for serotonin, with which we demonstrate quantification of neurotransmitter release in vitro. We also present a detailed structural analysis of evolved cytochrome P450‐BM3 heme domain lineages to systematically dissect the molecular basis of neurotransmitter binding affinity, selectivity, and enhanced MRI contrast activity in these engineered proteins.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
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DOI of Published Version
https://doi.org/10.1016/j.jmb.2012.05.029
