Sampling Realistic Protein Conformations Using Local Structural Bias
Research output: Contribution to journal › Journal article › Research › peer-review
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.
Original language | English |
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Journal | PLoS ONE |
Volume | 2 |
Issue number | 9 |
Pages (from-to) | e131 |
ISSN | 1932-6203 |
DOIs | |
Publication status | Published - 2006 |
ID: 1100863