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Anthony Ivetac
Researcher at University of California, San Diego
Publications - 24
Citations - 1765
Anthony Ivetac is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 16, co-authored 17 publications receiving 1585 citations. Previous affiliations of Anthony Ivetac include University of Oxford.
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Journal ArticleDOI
A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin
Luz Irina A. Calderón Villalobos,Sarah Lee,César Augusto F. de Oliveira,Anthony Ivetac,Wolfgang Brandt,Lynne Armitage,Laura B. Sheard,Xu Tan,Xu Tan,Geraint Parry,Geraint Parry,Haibin Mao,Ning Zheng,Richard M. Napier,Stefan Kepinski,Mark Estelle +15 more
TL;DR: It is demonstrated that the AFB5-Aux/IAA co-receptor selectively binds the auxinic herbicide picloram, which broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response.
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Coarse-grained molecular dynamics simulations of membrane proteins and peptides
TL;DR: The utility of CG-MD simulations for studies of membrane/protein interactions is demonstrated, including to the bacterial sugar transporter LacY and a number of membrane peptides and proteins used to characterize their interactions with lipid bilayers.
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Coarse-grained MD simulations of membrane protein-bilayer self-assembly.
TL;DR: A coarse-grained molecular dynamics approach to lipid bilayer self-assembly around membrane proteins is presented and it is demonstrated that this method can be used to predict accurately the protein position in the bilayer for membrane proteins with a range of different sizes and architectures.
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Mapping the druggable allosteric space of G-protein coupled receptors: a fragment-based molecular dynamics approach.
TL;DR: This work maps the surfaces of the β1 (β1AR) and β2 (β2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites and uses the FTMAP algorithm to identify ‘hot spots’ with affinity for a variety of organic probe molecules corresponding to drug fragments.
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Predictive power of molecular dynamics receptor structures in virtual screening.
TL;DR: A critical analysis of the predictive power of MD snapshots to blind virtual screening by docking is presented, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations.