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Toward the Rational Design of Fluorescent Proteins: Elucidating the Photodynamics of the GFP Chromophore in Various Environments- [electronic resource]
ข้อมูลเนื้อหา
Toward the Rational Design of Fluorescent Proteins: Elucidating the Photodynamics of the GFP Chromophore in Various Environments- [electronic resource]
자료유형  
 학위논문
Control Number  
0016933807
International Standard Book Number  
9798380264631
Dewey Decimal Classification Number  
616
Main Entry-Personal Name  
Jones, Chey Marcel.
Publication, Distribution, etc. (Imprint  
[S.l.] : Stanford University., 2022
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2022
Physical Description  
1 online resource(266 p.)
General Note  
Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
General Note  
Advisor: Boxer, Steven G.;Markland, Thomas E.;Martinez, Todd.
Dissertation Note  
Thesis (Ph.D.)--Stanford University, 2022.
Restrictions on Access Note  
This item must not be sold to any third party vendors.
Summary, Etc.  
요약The green fluorescent protein (GFP) has revolutionized the fields of chemistry and biology. Due to their ability to highlight protein dynamics in living organisms, GFP and GFP-like proteins have emerged as ubiquitous tools in biological imaging. The versatility of GFP has inspired a rainbow-like palette of fluorescent reporters; however, the creation of novel GFP variants is often imprecise and inefficient. Using molecular dynamics simulations, I unravel the intricate steric and electronic factors responsible for the performance of these fluorescent proteins. Across many systems (i.e., gas phase, water, and GFP/Dronpa2 scaffolds), I study the photodynamics of the GFP chromophore. Changes to the chromophore's intrinsic properties (e.g.fluorescence propensity, photoisomerization quantum yield, etc.) are monitored as the molecule occupies various condensed phase systems. Applying this knowledge, I have developed a computational workflow that can (1) generate structures for tens of thousands of GFP mutants and (2) characterize these mutants using steric and electronic features. This structural data is coupled with machine learning models to identify important interactions within the system and inspire the creation of novel GFP reporters.
Subject Added Entry-Topical Term  
Cancer.
Subject Added Entry-Topical Term  
Software.
Subject Added Entry-Topical Term  
Biochemistry.
Subject Added Entry-Topical Term  
Mutation.
Subject Added Entry-Topical Term  
Microscopy.
Subject Added Entry-Topical Term  
Chemistry.
Subject Added Entry-Topical Term  
Amino acids.
Subject Added Entry-Topical Term  
E coli.
Subject Added Entry-Topical Term  
Energy.
Subject Added Entry-Topical Term  
Mutagenesis.
Subject Added Entry-Topical Term  
Genetics.
Added Entry-Corporate Name  
Stanford University.
Host Item Entry  
Dissertations Abstracts International. 85-03B.
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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Control Number  
joongbu:641311
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