Computer-aided design of functional protein interactions View Full Text


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Article Info

DATE

2009-10-19

AUTHORS

Daniel J Mandell, Tanja Kortemme

ABSTRACT

Predictive methods for the computational design of proteins search for amino acid sequences adopting desired structures that perform specific functions. Typically, design of 'function' is formulated as engineering new and altered binding activities into proteins. Progress in the design of functional protein-protein interactions is directed toward engineering proteins to precisely control biological processes by specifically recognizing desired interaction partners while avoiding competitors. The field is aiming for strategies to harness recent advances in high-resolution computational modeling—particularly those exploiting protein conformational variability—to engineer new functions and incorporate many functional requirements simultaneously. More... »

PAGES

797-807

References to SciGraph publications

  • 2009-08. Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling in NATURE METHODS
  • 2007-06. Eris: an automated estimator of protein stability in NATURE METHODS
  • 2008-03-19. Kemp elimination catalysts by computational enzyme design in NATURE
  • 2006-03-22. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae in NATURE
  • 2006-06. Computational redesign of endonuclease DNA binding and cleavage specificity in NATURE
  • 2007-09-23. Computational design of antibody-affinity improvement beyond in vivo maturation in NATURE BIOTECHNOLOGY
  • 2002-12-02. Automated design of specificity in molecular recognition in NATURE STRUCTURAL & MOLECULAR BIOLOGY
  • 2004-03-21. Computational redesign of protein-protein interaction specificity in NATURE STRUCTURAL & MOLECULAR BIOLOGY
  • 2000-09. A chemical switch for inhibitor-sensitive alleles of any protein kinase in NATURE
  • 2002-06-24. Computer-aided design of a PDZ domain to recognize new target sequences in NATURE STRUCTURAL & MOLECULAR BIOLOGY
  • 1992-04. The dead-end elimination theorem and its use in protein side-chain positioning in NATURE
  • 1999-07. Rational design of a GCN4-derived mimetic of interleukin-4 in NATURE STRUCTURAL & MOLECULAR BIOLOGY
  • 2003-05. Computational design of receptor and sensor proteins with novel functions in NATURE
  • 2009-04. Design of protein-interaction specificity gives selective bZIP-binding peptides in NATURE
  • 2004-06-09. Evidence for dynamically organized modularity in the yeast protein–protein interaction network in NATURE
  • 2006-01-22. Proteome survey reveals modularity of the yeast cell machinery in NATURE
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nchembio.251

    DOI

    http://dx.doi.org/10.1038/nchembio.251

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1000087030

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/19841629


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