Sampling realistic protein conformations using local structural bias

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 ar...

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Bibliographic Details
Published in:PLoS computational biology 2006-09, Vol.2 (9), p.e131-e131
Main Authors: Hamelryck, Thomas, Kent, John T, Krogh, Anders
Format: Article
Language:English
Subjects:
Amino Acid Sequence
Analysis
Bioinformatics
Bioinformatics - Computational Biology
Computational Biology
Computer Simulation
Conformational Sampling
Directional Statistics
Levinthal Paradox
Local Structural Bias
Markov analysis
Models, Molecular
Probabilistic Model
Probability
Protein Structure, Secondary
Protein Structure, Tertiary
Proteins
Proteins - chemistry
Structure
Studies
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Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.0020131