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 |