Matching Items (391)
ContributorsWard, Geoffrey Harris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-18
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Description
ABSTRACT

Transition metals have been extensively employed to address various challenges

related to catalytic organic transformations, small molecule activation, and energy storage

over the last few decades. Inspired by recent catalytic advances mediated by redox noninnocent

pyridine diimine (PDI) and α-diimine (DI) ligand supported transition metals,

our group has designed new PDI and DI ligands

ABSTRACT

Transition metals have been extensively employed to address various challenges

related to catalytic organic transformations, small molecule activation, and energy storage

over the last few decades. Inspired by recent catalytic advances mediated by redox noninnocent

pyridine diimine (PDI) and α-diimine (DI) ligand supported transition metals,

our group has designed new PDI and DI ligands by modifying the imine substituents to

feature donor atoms. My doctoral research is focused on the development of PDI and DI

ligand supported low valent first row metal complexes (Mn, Fe, Co) and their application

in bond activation reactions and the hydrofunctionalization of unsaturated bonds.

First two chapters of this dissertation are centered on the synthesis and

application of redox non-innocent ligand supported low valent iron complexes. Notably,

reduction of a DI-based iron dibromide led to the formation of a low valent iron

dinitrogen compound. This compound was found to undergo a sequential C-H and C-P

bond activation processes upon heating to form a dimeric compound. The plausible

mechanism for dimer formation is also described here.

Inspired by the excellent carbonyl hydrosilylation activity of our previously

reported Mn catalyst, (Ph2PPrPDI)Mn, attempts were made to synthesize second generation

Mn catalyst, which is described in the third chapter. Reduction of (PyEtPDI)MnCl2

furnished a deprotonated backbone methyl group containing Mn compound

[(PyEtPDEA)Mn] whereas reduction of (Ph2PEtPDI)MnCl2 produced a dimeric compound,

[(Ph2PEtPDI)Mn]2. Both compounds were characterized by NMR spectroscopy and XRD

analysis. Hydrosilylation of aldehydes and ketones have been studied using

[(PyEtPDEA)Mn] as a pre-catalyst. Similarly, 14 different aldehydes and 6 different

ii

formates were successfully hydrosilylated using [(Ph2PEtPDI)Mn]2 as a pre-catalyst.

Encouraged by the limited number of cobalt catalysts for nitrile hydroboration, we

sought to develop a cobalt catalyst that is active for hydroboration under mild conditions,

which is discussed in the last chapter. Treatment of (PyEtPDI)CoCl2 with excess NaEt3BH

furnished a diamagnetic Co(I) complex [(PyEtPDIH)Co], which exhibits a reduced imine

functionality. Having this compound characterized, a broad substrate scope for both

nitriles and imines have been investigated. The operative mechanism for nitrile

dihydroboration has been investigated based on the outcomes of a series of stoichiometric

reactions using NMR spectroscopy.
ContributorsGhosh, Chandrani (Author) / Trovitch, Ryan J. (Thesis advisor) / Seo, Don (Committee member) / Moore, Ana (Committee member) / Arizona State University (Publisher)
Created2018
ContributorsBolari, John (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-04
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Description
Bexarotene (Targretin®) is an FDA approved drug used to treat cutaneous T-cell lymphoma (CTCL), as well as off-label treatments for various cancers and neurodegenerative diseases. Previous research has indicated that bexarotene has a specific affinity for retinoid X receptors (RXR), which allows bexarotene to act as a ligand-activated-transcription factor

Bexarotene (Targretin®) is an FDA approved drug used to treat cutaneous T-cell lymphoma (CTCL), as well as off-label treatments for various cancers and neurodegenerative diseases. Previous research has indicated that bexarotene has a specific affinity for retinoid X receptors (RXR), which allows bexarotene to act as a ligand-activated-transcription factor and in return control cell differentiation and proliferation. Bexarotene targets RXR homodimerization to drive transcription of tumor suppressing genes; however, adverse reactions occur simultaneously when bound to other nuclear receptors. In this study, we used novel bexarotene analogs throughout 5 iterations synthesized in the laboratory of Dr. Wagner to test for their potency and ability to bind RXR. The aim of our study is to quantitatively measure RXR homodimerization driven by bexarotene analogs using a yeast two-hybrid system. Our results suggests there to be several compounds with higher protein activity than bexarotene, particularly in generations 3.0 and 5.0. This higher affinity for RXR homodimers may help scientists identify a compound that will minimize adverse effects and toxicity of bexarotene and serve as a better cancer treatment alternative.
ContributorsSeto, David Hua (Author) / Marshall, Pamela (Thesis director) / Wagner, Carl (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Natural Sciences (Contributor) / School of Social and Behavioral Sciences (Contributor)
Created2015-05
ContributorsOftedahl, Paul (Performer) / ASU Library. Music Library (Publisher)
Created2018-09-29
ContributorsMarshall, Kimberly (Performer) / Meszler, Alexander (Performer) / Yatso, Toby (Narrator) / ASU Library. Music Library (Publisher)
Created2018-09-16
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Description
Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein

Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best characterized by an ensemble of possible bound configurations rather than a single “lock and key” fit. A model incorporating these factors is proposed and evaluated. A comprehensive dataset of 3,924 peptide-protein interface structures was extracted from the Protein Data Bank (PDB) and descriptors were computed characterizing the geometry and energetics of each interface. The characteristics of these interfaces are shown to be generally consistent with the proposed model, and heuristics for design and selection of peptide ligands are derived. The curated and energy-minimized interface structure dataset and a relational database containing the detailed results of analysis and energy modeling are made publicly available via a web repository. A novel analytical technique based on the proposed theoretical model, Virtual Scanning Probe Mapping (VSPM), is implemented in software to analyze the interaction between a target protein of known structure and a peptide of specified sequence, producing a spatial map indicating the most likely peptide binding regions on the protein target. The resulting predictions are shown to be superior to those of two other published methods, and support the validity of the stochastic binding model.
ContributorsEmery, Jack Scott (Author) / Pizziconi, Vincent B (Thesis advisor) / Woodbury, Neal W (Thesis advisor) / Guilbeau, Eric J (Committee member) / Stafford, Phillip (Committee member) / Taylor, Thomas (Committee member) / Towe, Bruce C (Committee member) / Arizona State University (Publisher)
Created2010
ContributorsTaylor, Karen Stephens (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-21
ContributorsCramer, Craig (Performer) / ASU Library. Music Library (Publisher)
Created1997-02-16
ContributorsMarshall, Kimberly (Performer) / ASU Library. Music Library (Publisher)
Created2019-03-17