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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

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.

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    Date Created
    • 2010
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  • Text
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    • Partial requirement for: Ph.D., Arizona State University, 2010
      Note type
      thesis
    • Includes bibliographical references (p. 227-250)
      Note type
      bibliography
    • Field of study: Bioengineering

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    Jack Scott Emery

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