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Biomolecular electrostatics with con...
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Cooper Villagran, Christopher.
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Biomolecular electrostatics with continuum models: A boundary integral implementation and applications to biosensors.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Biomolecular electrostatics with continuum models: A boundary integral implementation and applications to biosensors./
作者:
Cooper Villagran, Christopher.
面頁冊數:
172 p.
附註:
Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.
Contained By:
Dissertation Abstracts International76-07B(E).
標題:
Biophysics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3684993
ISBN:
9781321605181
Biomolecular electrostatics with continuum models: A boundary integral implementation and applications to biosensors.
Cooper Villagran, Christopher.
Biomolecular electrostatics with continuum models: A boundary integral implementation and applications to biosensors.
- 172 p.
Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.
Thesis (Ph.D.)--Boston University, 2015.
The implicit-solvent model uses continuum electrostatic theory to represent the salt solution around dissolved biomolecules, leading to a coupled system of the Poisson-Boltzmann and Poisson equations. This thesis uses the implicit-solvent model to study solvation, binding and adsorption of proteins.
ISBN: 9781321605181Subjects--Topical Terms:
518360
Biophysics.
Biomolecular electrostatics with continuum models: A boundary integral implementation and applications to biosensors.
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Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.
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The implicit-solvent model uses continuum electrostatic theory to represent the salt solution around dissolved biomolecules, leading to a coupled system of the Poisson-Boltzmann and Poisson equations. This thesis uses the implicit-solvent model to study solvation, binding and adsorption of proteins.
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We developed an implicit-solvent model solver that uses the boundary element method (BEM), called PyGBe. BEM numerically solves integral equations along the biomolecule-solvent interface only, therefore, it does not need to discretize the entire domain. PyGBe accelerates the BEM with a treecode algorithm and runs on graphic processing units. We performed extensive verification and validation of the code, comparing it with experimental observations, analytical solutions, and other numerical tools. Our results suggest that a BEM approach is more appropriate than volumetric based methods, like finite-difference or finite-element, for high accuracy calculations. We also discussed the effect of features like solvent-filled cavities and Stern layers in the implicit-solvent model, and realized that they become relevant in binding energy calculations.
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The application that drove this work was nano-scale biosensors---devices designed to detect biomolecules. Biosensors are built with a functionalized layer of ligand molecules, to which the target molecule binds when it is detected. With our code, we performed a study of the orientation of proteins near charged surfaces, and investigated the ideal conditions for ligand molecule adsorption. Using immunoglobulin G as a test case, we found out that low salt concentration in the solvent and high positive surface charge density leads to favorable orientations of the ligand molecule for biosensing applications.
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We also studied the plasmonic response of localized surface plasmon resonance (LSPR) biosensors. LSPR biosensors monitor the plasmon resonance frequency of metallic nanoparticles, which shifts when a target molecule binds to a ligand molecule. Electrostatics is a valid approximation to the LSPR biosensor optical phenomenon in the long-wavelength limit, and BEM was able to reproduce the shift in the plasmon resonance frequency as proteins approach the nanoparticle.
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