Literature DB >> 12468711

Protein design is NP-hard.

Niles A Pierce1, Erik Winfree.   

Abstract

Biologists working in the area of computational protein design have never doubted the seriousness of the algorithmic challenges that face them in attempting in silico sequence selection. It turns out that in the language of the computer science community, this discrete optimization problem is NP-hard. The purpose of this paper is to explain the context of this observation, to provide a simple illustrative proof and to discuss the implications for future progress on algorithms for computational protein design.

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Year:  2002        PMID: 12468711     DOI: 10.1093/protein/15.10.779

Source DB:  PubMed          Journal:  Protein Eng        ISSN: 0269-2139


  60 in total

1.  Optimization of van der Waals energy for protein side-chain placement and design.

Authors:  Amr Fahmy; Gerhard Wagner
Journal:  Biophys J       Date:  2011-10-05       Impact factor: 4.033

2.  A Bayesian approach for determining protein side-chain rotamer conformations using unassigned NOE data.

Authors:  Jianyang Zeng; Kyle E Roberts; Pei Zhou; Bruce Randall Donald
Journal:  J Comput Biol       Date:  2011-10-04       Impact factor: 1.479

3.  Combinatorial methods for small-molecule placement in computational enzyme design.

Authors:  Jonathan Kyle Lassila; Heidi K Privett; Benjamin D Allen; Stephen L Mayo
Journal:  Proc Natl Acad Sci U S A       Date:  2006-10-30       Impact factor: 11.205

4.  Toward full-sequence de novo protein design with flexible templates for human beta-defensin-2.

Authors:  Ho Ki Fung; Christodoulos A Floudas; Martin S Taylor; Li Zhang; Dimitrios Morikis
Journal:  Biophys J       Date:  2007-09-07       Impact factor: 4.033

5.  Genetic algorithms as a tool for helix design--computational and experimental studies on prion protein helix 1.

Authors:  Jan Ziegler; Stephan Schwarzinger
Journal:  J Comput Aided Mol Des       Date:  2006-03-16       Impact factor: 3.686

6.  IRECS: a new algorithm for the selection of most probable ensembles of side-chain conformations in protein models.

Authors:  Christoph Hartmann; Iris Antes; Thomas Lengauer
Journal:  Protein Sci       Date:  2007-06-13       Impact factor: 6.725

7.  Adapting Poisson-Boltzmann to the self-consistent mean field theory: application to protein side-chain modeling.

Authors:  Patrice Koehl; Henri Orland; Marc Delarue
Journal:  J Chem Phys       Date:  2011-08-07       Impact factor: 3.488

8.  Optimization of combinatorial mutagenesis.

Authors:  Andrew S Parker; Karl E Griswold; Chris Bailey-Kellogg
Journal:  J Comput Biol       Date:  2011-09-16       Impact factor: 1.479

9.  Scientific benchmarks for guiding macromolecular energy function improvement.

Authors:  Andrew Leaver-Fay; Matthew J O'Meara; Mike Tyka; Ron Jacak; Yifan Song; Elizabeth H Kellogg; James Thompson; Ian W Davis; Roland A Pache; Sergey Lyskov; Jeffrey J Gray; Tanja Kortemme; Jane S Richardson; James J Havranek; Jack Snoeyink; David Baker; Brian Kuhlman
Journal:  Methods Enzymol       Date:  2013       Impact factor: 1.600

10.  Algorithm for backrub motions in protein design.

Authors:  Ivelin Georgiev; Daniel Keedy; Jane S Richardson; David C Richardson; Bruce R Donald
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

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