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231224s2014 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.23509
|2 doi
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|a pubmed24n0778.xml
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|a DE-627
|b ger
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|e rakwb
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|a eng
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| 100 |
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|a Liang, Shide
|e verfasserin
|4 aut
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| 245 |
1 |
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|a LEAP
|b highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains
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|c 2014
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 30.09.2014
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|a Date Revised 10.11.2023
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Copyright © 2013 Wiley Periodicals, Inc.
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|a Prediction of protein loop conformations without any prior knowledge (ab initio prediction) is an unsolved problem. Its solution will significantly impact protein homology and template-based modeling as well as ab initio protein-structure prediction. Here, we developed a coarse-grained, optimized scoring function for initial sampling and ranking of loop decoys. The resulting decoys are then further optimized in backbone and side-chain conformations and ranked by all-atom energy scoring functions. The final integrated technique called loop prediction by energy-assisted protocol achieved a median value of 2.1 Å root mean square deviation (RMSD) for 325 12-residue test loops and 2.0 Å RMSD for 45 12-residue loops from critical assessment of structure-prediction techniques (CASP) 10 target proteins with native core structures (backbone and side chains). If all side-chain conformations in protein cores were predicted in the absence of the target loop, loop-prediction accuracy only reduces slightly (0.2 Å difference in RMSD for 12-residue loops in the CASP target proteins). The accuracy obtained is about 1 Å RMSD or more improvement over other methods we tested. The executable file for a Linux system is freely available for academic users at http://sparks-lab.org
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|a Journal Article
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|a Research Support, N.I.H., Extramural
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a loop modeling • coarse-grained energy function • energy minimization • Monte Carlo simulation • force field development
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| 650 |
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|a Proteins
|2 NLM
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| 700 |
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|a Zhang, Chi
|e verfasserin
|4 aut
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| 700 |
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|a Zhou, Yaoqi
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 35(2014), 4 vom: 05. Feb., Seite 335-41
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
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|g volume:35
|g year:2014
|g number:4
|g day:05
|g month:02
|g pages:335-41
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|u http://dx.doi.org/10.1002/jcc.23509
|3 Volltext
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