Protein design on computers. Five new proteins: Shpilka, grendel, fingerclasp, leather, and aida

@article{Sander1992ProteinDO,
  title={Protein design on computers. Five new proteins: Shpilka, grendel, fingerclasp, leather, and aida},
  author={Chris Sander and Gerrit Vriend and Fernando Bazan and Amnon Horovitz and Haruki Nakamura and Luis Ribas and Alexei V. Finkelstein and Andrew Lockhart and Rainer Merkl and L. Jeanne Perry and Stephen C Emery and Christine Gaboriaud and Cara B. Marks and John Moult and Christophe L. M. J. Verlinde and Mark Eberhard and Arne Elofsson and Tim J. P. Hubbard and Lynne Regan and Jay Banks and Roberto Jappelli and Arthur M. Lesk and Anna Tramontano},
  journal={Proteins: Structure},
  year={1992},
  volume={12}
}
What is the current state of the art in protein design? This question was approached in a recent two‐week protein design workshop sponsored by EMBO and held at the EMBL in Heidelberg. The goals were to test available design tools and to explore new design strategies. Five novel proteins were designed: Shpilka, a sandwich of two four‐stranded β‐sheets, a scaffold on which to explore variations in loop topology; Grendel, a four‐helical membrane anchor, ready for fusion to water‐soluble functional… 
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23 Citations
Background Citations
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Methods Citations
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23 Citations

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Citation Type

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template.
De novo design and creation of a stable artificial protein.
New strategies in protein design.
A cluster-DEE-based strategy to empower protein design
Towards meeting the paracelsus challenge: The design, synthesis, and characterization of paracelsin‐43, an α‐helical protein with over 50% sequence identity to an all‐β protein
TLDR
The design, synthesis, and characterization of a helical protein, whose sequence is 50% identical to that of an all‐β protein, is presented, which represents a significant step toward meeting the Paracelsus Challenge.
A quantitative methodology for the de novo design of proteins
TLDR
A general quantitative methodology for designing proteins de novo, which automatically produces sequences for any given plausible protein structure, which is likely to be capable of successfully designing new proteins and yielding fundamental insights about the determinants of protein structure.
De novo protein design using pairwise potentials and a genetic algorithm
  • David T. Jones
  • Biology
    Protein science : a publication of the Protein Society
  • 1994
TLDR
A simple method is described for designing an amino acid sequence to fit a given 3‐dimensional structure through a genetic algorithm, whereby the sequence is optimized by a stochastic search in the style of natural selection.
JONES algorithm De novo protein design using pairwise potentials and a genetic
TLDR
A simple method is described for designing an amino acid sequence to fit a given 3-dimensional structure through a genetic algorithm, whereby the sequence is optimized by a stochastic search in the style of natural selection.
Protein Design by Optimization of a Sequence-Structure Quality Function
TLDR
Two optimization algorithms are presented: one provides an exact optimization while the other uses a combinatorial technique for comparatively rapid results, suitable for massively parallel computers.
Computer modeling and folding of four‐helix bundles
TLDR
From these studies, a general set of rules is extracted which should aid in the further design of more detailed protein models adequate to more fully investigate the protein folding problem.
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