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Computational Modeling of Peptide-Protein Binding


Abstract Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best character... (more)
Created Date 2010
Contributor Emery, Jack Scott (Author) / Pizziconi, Vincent B (Advisor) / Woodbury, Neal W (Advisor) / Guilbeau, Eric J (Committee member) / Stafford, Phillip (Committee member) / Taylor, Thomas (Committee member) / Towe, Bruce C (Committee member) / Arizona State University (Publisher)
Subject Biomedical Engineering / Bioinformatics / Biophysics / affinity ligands / molecular modeling / PDB / peptide-protein interfaces / peptides
Type Doctoral Dissertation
Extent 267 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Ph.D. Bioengineering 2010
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis