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Sökning: WFRF:(Nivón Lucas G)

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1.
  • Bjelic, Sinisa, et al. (författare)
  • Computational design of enone-binding proteins with catalytic activity for the Morita-Baylis-Hillman reaction
  • 2013
  • Ingår i: ACS Chemical Biology. - : American Chemical Society (ACS). - 1554-8929 .- 1554-8937. ; 8:4, s. 749-757
  • Tidskriftsartikel (refereegranskat)abstract
    • The Morita-Baylis-Hillman reaction forms a carbon-carbon bond between the α-carbon of a conjugated carbonyl compound and a carbon electrophile. The reaction mechanism involves Michael addition of a nucleophile catalyst at the carbonyl β-carbon, followed by bond formation with the electrophile and catalyst disassociation to release the product. We used Rosetta to design 48 proteins containing active sites predicted to carry out this mechanism, of which two show catalytic activity by mass spectrometry (MS). Substrate labeling measured by MS and site-directed mutagenesis experiments show that the designed active-site residues are responsible for activity, although rate acceleration over background is modest. To characterize the designed proteins, we developed a fluorescence-based screen for intermediate formation in cell lysates, carried out microsecond molecular dynamics simulations, and solved X-ray crystal structures. These data indicate a partially formed active site and suggest several clear avenues for designing more active catalysts.
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2.
  • Nivón, Lucas G, et al. (författare)
  • Automating human intuition for protein design
  • 2014
  • Ingår i: Proteins. - : Wiley. - 0887-3585 .- 1097-0134. ; 82:5, s. 858-866
  • Tidskriftsartikel (refereegranskat)abstract
    • In the design of new enzymes and binding proteins, human intuition is often used to modify computationally designed amino acid sequences prior to experimental characterization. The manual sequence changes involve both reversions of amino acid mutations back to the identity present in the parent scaffold and the introduction of residues making additional interactions with the binding partner or backing up first shell interactions. Automation of this manual sequence refinement process would allow more systematic evaluation and considerably reduce the amount of human designer effort involved. Here we introduce a benchmark for evaluating the ability of automated methods to recapitulate the sequence changes made to computer-generated models by human designers, and use it to assess alternative computational methods. We find the best performance for a greedy one-position-at-a-time optimization protocol that utilizes metrics (such as shape complementarity) and local refinement methods too computationally expensive for global Monte Carlo (MC) sequence optimization. This protocol should be broadly useful for improving the stability and function of designed binding proteins.
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