TY - JOUR
T1 - Extensive exploration of conformational space improves Rosetta results for short protein domains.
AU - Li, Yaohang
AU - Bordner, Andrew J.
AU - Tian, Yuan
AU - Tao, Xiuping
AU - Gorin, Andrey A.
PY - 2008
Y1 - 2008
N2 - With some simplifications, computational protein folding can be understood as an optimization problem of a potential energy function on a variable space consisting of all conformation for a given protein molecule. It is well known that realistic energy potentials are very "rough" functions, when expressed in the standard variables, and the folding trajectories can be easily trapped in multiple local minima. We have integrated our variation of Parallel Tempering optimization into the protein folding program Rosetta in order to improve its capability to overcome energy barriers and estimate how such improvement will influence the quality of the folded protein domains. Here we report that (1) Parallel Tempering Rosetta (PTR) is significantly better in the exploration of protein structures than previous implementations of the program; (2) systematic improvements are observed across a large benchmark set in the parameters that are normally followed to estimate robustness of the folding; (3) these improvements are most dramatic in the subset of the shortest domains, where high-quality structures have been obtained for >75% of all tested sequences. Further analysis of the results will improve our understanding of protein conformational space and lead to new improvements in the protein folding methodology, while the current PTR implementation should be very efficient for short (up to approximately 80 a.a.) protein domains and therefore may find practical application in system biology studies.
AB - With some simplifications, computational protein folding can be understood as an optimization problem of a potential energy function on a variable space consisting of all conformation for a given protein molecule. It is well known that realistic energy potentials are very "rough" functions, when expressed in the standard variables, and the folding trajectories can be easily trapped in multiple local minima. We have integrated our variation of Parallel Tempering optimization into the protein folding program Rosetta in order to improve its capability to overcome energy barriers and estimate how such improvement will influence the quality of the folded protein domains. Here we report that (1) Parallel Tempering Rosetta (PTR) is significantly better in the exploration of protein structures than previous implementations of the program; (2) systematic improvements are observed across a large benchmark set in the parameters that are normally followed to estimate robustness of the folding; (3) these improvements are most dramatic in the subset of the shortest domains, where high-quality structures have been obtained for >75% of all tested sequences. Further analysis of the results will improve our understanding of protein conformational space and lead to new improvements in the protein folding methodology, while the current PTR implementation should be very efficient for short (up to approximately 80 a.a.) protein domains and therefore may find practical application in system biology studies.
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U2 - 10.1142/9781848162648_0018
DO - 10.1142/9781848162648_0018
M3 - Article
C2 - 19642281
AN - SCOPUS:69249244205
SN - 1752-7791
VL - 7
SP - 203
EP - 209
JO - Computational systems bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference
JF - Computational systems bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference
ER -