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Computational studies of the metal-b...
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Amin, Elizabeth Ambrose.
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Computational studies of the metal-binding proteins stromelysin-1 and human serum transferrin: Protein modeling and inhibitor design.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Computational studies of the metal-binding proteins stromelysin-1 and human serum transferrin: Protein modeling and inhibitor design./
Author:
Amin, Elizabeth Ambrose.
Description:
214 p.
Notes:
Adviser: William J. Welsh.
Contained By:
Dissertation Abstracts International62-09B.
Subject:
Chemistry, Biochemistry. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3027140
ISBN:
0493393471
Computational studies of the metal-binding proteins stromelysin-1 and human serum transferrin: Protein modeling and inhibitor design.
Amin, Elizabeth Ambrose.
Computational studies of the metal-binding proteins stromelysin-1 and human serum transferrin: Protein modeling and inhibitor design.
- 214 p.
Adviser: William J. Welsh.
Thesis (Ph.D.)--University of Missouri - Saint Louis, 2002.
This study constitutes a detailed molecular modeling investigation of two metal-binding proteins: stromelysin-1 (MMP-3), a matrix metalloproteinase, and human serum transferrin. Matrix metalloproteinases (MMPs) comprise a family of zinc-binding enzymes responsible for connective tissue remodeling; they mediate the breakdown of extracellular matrix proteins such as collagen, gelatin and proteoglycan. MMPs have been identified in tissue surrounding invasive carcinoma, and directly enable tumor metastasis through proteolysis and blood vessel formation (angiogenesis). Degenerative and inflammatory diseases such as osteoarthritis also depend on MMPs to spread to unaffected tissue. These enzymes are therefore attractive targets for small-molecule synthetic inhibitors (MMPIs) which would serve as adjuncts to traditional treatments such as radiation and chemotherapy. Comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA), widely used 3D paradigms of quantitative structure-activity relationship (QSAR) models, are useful when the binding area is unknown or difficult to model, and are therefore well suited to MMPI design. Three highly predictive CoMFA models, and one predictive CoMSIA model, have been derived and applied to the design of a new series of nonpeptidic, thalidomide-based MMPIs which demonstrate high predicted biological activity against stromelysin-1 (MMP-3).
ISBN: 0493393471Subjects--Topical Terms:
1017722
Chemistry, Biochemistry.
Computational studies of the metal-binding proteins stromelysin-1 and human serum transferrin: Protein modeling and inhibitor design.
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214 p.
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Adviser: William J. Welsh.
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Source: Dissertation Abstracts International, Volume: 62-09, Section: B, page: 4006.
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Thesis (Ph.D.)--University of Missouri - Saint Louis, 2002.
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This study constitutes a detailed molecular modeling investigation of two metal-binding proteins: stromelysin-1 (MMP-3), a matrix metalloproteinase, and human serum transferrin. Matrix metalloproteinases (MMPs) comprise a family of zinc-binding enzymes responsible for connective tissue remodeling; they mediate the breakdown of extracellular matrix proteins such as collagen, gelatin and proteoglycan. MMPs have been identified in tissue surrounding invasive carcinoma, and directly enable tumor metastasis through proteolysis and blood vessel formation (angiogenesis). Degenerative and inflammatory diseases such as osteoarthritis also depend on MMPs to spread to unaffected tissue. These enzymes are therefore attractive targets for small-molecule synthetic inhibitors (MMPIs) which would serve as adjuncts to traditional treatments such as radiation and chemotherapy. Comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA), widely used 3D paradigms of quantitative structure-activity relationship (QSAR) models, are useful when the binding area is unknown or difficult to model, and are therefore well suited to MMPI design. Three highly predictive CoMFA models, and one predictive CoMSIA model, have been derived and applied to the design of a new series of nonpeptidic, thalidomide-based MMPIs which demonstrate high predicted biological activity against stromelysin-1 (MMP-3).
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Human serum transferrin (HST) is an approximately 80-kDa iron-binding glycoprotein responsible for transporting iron(III) cations from erythrocyte processing locations to tissues that require iron. HST is normally ∼30% saturated with Fe, but frequent blood transfusions can result in toxic iron overload, where HST becomes totally saturated and unable to remove excess iron from the bloodstream. The immediate therapeutic goal is to facilitate iron removal from HST in order to safely chelate and excrete it; this is complicated by the extremely slow iron release process. Certain anions selectively affect Fe release from HST and are believed to bind at one or more allosteric “KISAB” (kinetically significant anion-binding) sites. Probable KISAB sites have been identified and rank-ordered using a unique three-stage computational process incorporating energy grid calculations, molecular dynamics, and molecular mechanics.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3027140
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