Predictive energy landscapes for folding α-helical transmembrane proteins
Identifieur interne : 000190 ( Main/Merge ); précédent : 000189; suivant : 000191Predictive energy landscapes for folding α-helical transmembrane proteins
Auteurs : Bobby L. Kim ; Nicholas P. Schafer ; Peter G. WolynesSource :
- Proceedings of the National Academy of Sciences of the United States of America [ 0027-8424 ] ; 2014.
Abstract
The understanding of how membrane proteins fold pales in comparison with the understanding of globular protein folding. This discrepancy is partly due to the fact that membrane proteins are difficult to work with experimentally. In turn, the lack of high-quality experimental data has caused modeling of membrane proteins to lag behind. Also, the extent to which the translocon assists transmembrane domains in folding is unclear. The number of experimentally determined membrane protein structures has recently increased, and we may now be at the stage where it has become possible to derive transferable simulation models for studying transmembrane protein folding. We describe the optimization of one such model and its application to predicting helical packings within the native topology.
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DOI: 10.1073/pnas.1410529111
PubMed: 25030446
PubMed Central: 4121805
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