Biomolecular Recognition of Crystal Defects: A Diffuse-Selection Approach

Authors

  • A. K. Sinensky,

    1. Department of Materials Science and Engineering, Division of Biological Engineering, Massachusetts Institute of Technology, 16-244, 77 Massachusetts Ave., Cambridge, MA 02139, USA
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  • A. M. Belcher

    1. Department of Materials Science and Engineering, Division of Biological Engineering, Massachusetts Institute of Technology, 16-244, 77 Massachusetts Ave., Cambridge, MA 02139, USA
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  • We thank the Kimerling group, including Jifeng Liu and David Danielson, for assistance in substrate preparation. We thank Steve Kottman for assistance with structural Monte Carlo simulations. AKS thanks the Dept. of Homeland Security for fellowship support. This work was supported by the Army Research Office Institute of Collaborative Biotechnology. Supporting Information is available online from Wiley InterScience or from the author.

Abstract

original image

Phage display has been used to find an amino acid sequence that shows binding affinity for surface defects in germanium. A general approach called “diffuse selection” is employed to find consensus peptide sequences (see figure) demonstrating binding specificity for highly defective crystal surfaces versus non-defective crystal surfaces. This approach may be useful for selecting semiconductors with specific doping profiles from diffuse targets with large competing backgrounds.

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