• About
    • Login
    View Item 
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Institutional RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDepartmentThis CollectionBy Issue DateAuthorsTitlesSubjectsDepartment

    My Account

    LoginRegister

    Improving Protein-Small Molecule Structure Predictions with Ensemble Methods, or Using Computers to Guess How Tiny Things Fit Together

    Fu, Darwin Yu
    : https://etd.library.vanderbilt.edu/etd-08012018-164524
    http://hdl.handle.net/1803/13786
    : 2018-08-06

    Abstract

    Protein-small molecule structure prediction, or protein-ligand docking, is a computational method for modeling how binding partners will interaction on an atomic level. Accurate prediction of protein-small molecule interactions is an important step in the structure based drug discovery pipeline. Biological molecules are flexible and adopt different conformational shapes when binding with small molecules. Capturing this flexibility while maintaining computational efficiency is a critical challenge for docking software. This research developed novel methods within the Rosetta Macromolecular Modeling Suite to consider structural ensembles of proteins and small molecules during docking. The additional structural information is complemented with experimental structure-activity relationship data, which previously was only considered retroactively. The new ensemble docking methods was applied in collaboration to targets of pharmaceutical interest including metabotropic glutamate receptors, protease-activated receptors, and STAT proteins.
    Show full item record

    Files in this item

    Icon
    Name:
    DarwinYFu_Thesis_Submit.pdf
    Size:
    7.414Mb
    Format:
    PDF
    View/Open

    This item appears in the following collection(s):

    • Electronic Theses and Dissertations

    Connect with Vanderbilt Libraries

    Your Vanderbilt

    • Alumni
    • Current Students
    • Faculty & Staff
    • International Students
    • Media
    • Parents & Family
    • Prospective Students
    • Researchers
    • Sports Fans
    • Visitors & Neighbors

    Support the Jean and Alexander Heard Libraries

    Support the Library...Give Now

    Gifts to the Libraries support the learning and research needs of the entire Vanderbilt community. Learn more about giving to the Libraries.

    Become a Friend of the Libraries

    Quick Links

    • Hours
    • About
    • Employment
    • Staff Directory
    • Accessibility Services
    • Contact
    • Vanderbilt Home
    • Privacy Policy