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Understanding T-Cell Receptor Signal...

White, William Louis,

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Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design // William Louis White.
Author:	White, William Louis,
Description:	1 electronic resource (67 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
Contained By:	Dissertations Abstracts International86-01B.
Subject:	Bioengineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31294680
ISBN:	9798383282915

Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design /
White, William Louis,

Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design /William Louis White. - 1 electronic resource (67 pages)

Source: Dissertations Abstracts International, Volume: 86-01, Section: B.

In order to successfully defend the host from a wide range of pathogens and cancer, T-cells must be able to recognize these threats while ignoring healthy tissues. If T-cell threat recognition is not properly calibrated, pathologies such as autoimmunity or immune deficiency can arise. The mechanisms that control T-cell recognition and activation can be broadly divided into two categories: the structural mechanism by which T-cell receptors (TCRs) can bind specifically to foreign peptides presented on the major histocompatibility complex (pMHC) but not self-pMHCs, and the biochemical mechanism by which TCR binding events are translated into T-cell activation. Here, I describe two projects that are together focused on developing tools and models to better understand each of these critical aspects of T-cell function. First, I developed a de-novo designed stabilizing domain which allows MHCs to be expressed solubly in E. coli, allowing much faster and easier production of pMHC reagents for a variety of applications in the study of pMHC-TCR interactions. Second, I developed a model of early T-cell signaling steps which explains several important aspects of TCR signaling through the clustering dynamics of signaling molecules. In combination, these two projects provide important tools and insights in the study of T-cell antigen recognition and selectivity.

English

ISBN: 9798383282915Subjects--Topical Terms:

657580
Bioengineering.
Subjects--Index Terms:

Cell signaling

Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design /
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245 1 0 $a Understanding T-Cell Receptor Signaling Through Computational Modeling and De-novo Protein Design / $c William Louis White.
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500 $a Includes supplementary digital materials.
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502 $b Ph.D. $c University of Washington $d 2024.
520 $a In order to successfully defend the host from a wide range of pathogens and cancer, T-cells must be able to recognize these threats while ignoring healthy tissues. If T-cell threat recognition is not properly calibrated, pathologies such as autoimmunity or immune deficiency can arise. The mechanisms that control T-cell recognition and activation can be broadly divided into two categories: the structural mechanism by which T-cell receptors (TCRs) can bind specifically to foreign peptides presented on the major histocompatibility complex (pMHC) but not self-pMHCs, and the biochemical mechanism by which TCR binding events are translated into T-cell activation. Here, I describe two projects that are together focused on developing tools and models to better understand each of these critical aspects of T-cell function. First, I developed a de-novo designed stabilizing domain which allows MHCs to be expressed solubly in E. coli, allowing much faster and easier production of pMHC reagents for a variety of applications in the study of pMHC-TCR interactions. Second, I developed a model of early T-cell signaling steps which explains several important aspects of TCR signaling through the clustering dynamics of signaling molecules. In combination, these two projects provide important tools and insights in the study of T-cell antigen recognition and selectivity.
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590 $a School code: 0250
650 4 $a Bioengineering. $3 657580
650 4 $a Biochemistry. $3 518028
650 4 $a Immunology. $3 611031
650 4 $a Microbiology. $3 536250
650 4 $a Cellular biology. $3 3172791
653 $a Cell signaling
653 $a Clustering
653 $a MHC
653 $a Protein design
653 $a Soluble MHC
653 $a T-cell receptor
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690 $a 0487
690 $a 0982
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720 1 $a Kueh, Hao Yuan $e degree supervisor.
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