Title |
Sampling Realistic Protein Conformations Using Local Structural Bias
|
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Published in |
PLoS Computational Biology, September 2006
|
DOI | 10.1371/journal.pcbi.0020131 |
Pubmed ID | |
Authors |
Thomas Hamelryck, John T Kent, Anders Krogh |
Abstract |
The prediction of protein structure from sequence remains a major unsolved problem in biology. The most successful protein structure prediction methods make use of a divide-and-conquer strategy to attack the problem: a conformational sampling method generates plausible candidate structures, which are subsequently accepted or rejected using an energy function. Conceptually, this often corresponds to separating local structural bias from the long-range interactions that stabilize the compact, native state. However, sampling protein conformations that are compatible with the local structural bias encoded in a given protein sequence is a long-standing open problem, especially in continuous space. We describe an elegant and mathematically rigorous method to do this, and show that it readily generates native-like protein conformations simply by enforcing compactness. Our results have far-reaching implications for protein structure prediction, determination, simulation, and design. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 6 | 6% |
Canada | 3 | 3% |
United Kingdom | 3 | 3% |
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Switzerland | 1 | 1% |
India | 1 | 1% |
Italy | 1 | 1% |
Colombia | 1 | 1% |
Belgium | 1 | 1% |
Other | 3 | 3% |
Unknown | 77 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 32 | 32% |
Researcher | 19 | 19% |
Student > Master | 13 | 13% |
Other | 6 | 6% |
Professor > Associate Professor | 5 | 5% |
Other | 15 | 15% |
Unknown | 9 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 39 | 39% |
Computer Science | 14 | 14% |
Chemistry | 8 | 8% |
Biochemistry, Genetics and Molecular Biology | 8 | 8% |
Engineering | 7 | 7% |
Other | 12 | 12% |
Unknown | 11 | 11% |