## Computational Complexity, Protein Structure Prediction, and the Levinthal Paradox (1994)

Venue: | Computational Complexity Protein Structure Prediction and the Levinthal Paradox |

Citations: | 19 - 0 self |

### BibTeX

@INPROCEEDINGS{Ngo94computationalcomplexity,,

author = {J. Thomas Ngo and Joe Marks and Martin Karplus},

title = {Computational Complexity, Protein Structure Prediction, and the Levinthal Paradox},

booktitle = {Computational Complexity Protein Structure Prediction and the Levinthal Paradox},

year = {1994},

pages = {433--506},

publisher = {Birkhauser}

}

### Years of Citing Articles

### OpenURL

### Abstract

The task of determining the globally optimal (minimum-energy) conformation of a protein given its potential-energy function is widely believed to require an amount of computer time that is exponential in the number of soft degrees of freedom in the protein. Conventional reasoning as to the exponential time complexity of this problem is fallacious---it is based solely on the size of the search space---and for some variants of the protein-structure prediction problem the conclusion is likely to be incorrect. Every problem in combinatorial optimization has an exponential number of candidate solutions, but many such problems can be solved by algorithms that do not require exponential time. We present a critical review of efforts to characterize rigorously the computational requirements of global potential-energy minimization for a polypeptide chain that has a unique energy minimum corresponding to the native structure of the protein. An argument by Crippen (1975) demonstrated that an algor...