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Designing Solvent-Based Order Parameters for Characterizing Binding of Surfaces With Different Hydrophobicity Using Molecular Dynamics Simulations Jun Lu

Dissertations & Theses @ University of Pennsylvania Available online

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Format:
Book
Thesis/Dissertation
Author/Creator:
Lu, Jun, author.
Contributor:
University of Pennsylvania. Chemical and Biomolecular Engineering., degree granting institution.
Language:
English
Subjects (All):
0202.
0537.
0542.
0791.
Local Subjects:
0202.
0537.
0542.
0791.
Physical Description:
1 electronic resource (58 pages)
Contained In:
Dissertations Abstracts International 87-08B
Place of Publication:
Ann Arbor : ProQuest Dissertations and Theses, 2025
Language Note:
English
Summary:
Life is dependent on water: most self-assembly and binding processes of biomolecules take place in water. Water-mediated interactions are an essential driving force behind these processes, which is largely affected by the hydrophobicity of the binding surfaces. As many biomolecular binding interfaces are amphiphilic, the hydrophobic interactions are largely affected by polar and charged groups near hydrophobic binding domains. Therefore, the study of interactions between hydrophobic surfaces and hydrophilic surfaces are of great importance. We find that on the two extremes: purely hydrophobic and hydrophilic systems, traditional sampling approaches in molecular dynamics (MD) simulations become ineffective for different reasons. Here, we study the binding of surfaces with different hydrophobicity using the MD approach with specifically designed solvent-based order parameters to control. By sensibly choosing order parameter sets from 1. Separation distance, 2. Solvent coordinates, and 3. Electrostatic energy to control, sampling pathologies can be mostly solved and the thermodynamics of binding of surfaces with different hydrophobicity can be studied
Notes:
Advisors: Patel, Amish J. Committee members: Riggleman, Robert A.; Sinno, Talid R.; Saven, Jeffery G.
Source: Dissertations Abstracts International, Volume: 87-08, Section: B.
Ph.D. University of Pennsylvania 2025
Vendor supplied data
Local Notes:
School code: 0175
ISBN:
9798276002026
Access Restriction:
Restricted for use by site license

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