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Toward the Rational Design of Fluorescent Proteins: Elucidating the Photodynamics of the GFP Chromophore in Various Environments- [electronic resource]
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
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:641311
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