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LEAP:通过整合粗粒采样和优化能量评分,并结合主链和侧链的全原子精修,实现对蛋白质环构象的高精度预测。

LEAP: 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.

机构信息

Systems Immunology Laboratory, Immunology Frontier Research Center, Osaka University, Suita, Osaka, 565-0871, Japan.

出版信息

J Comput Chem. 2014 Feb 5;35(4):335-41. doi: 10.1002/jcc.23509. Epub 2013 Dec 10.

DOI:10.1002/jcc.23509
PMID:24327406
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4125323/
Abstract

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.

摘要

无先验知识(从头预测)预测蛋白质环构象是一个尚未解决的问题。其解决方案将对蛋白质同源性和基于模板的建模以及从头蛋白质结构预测产生重大影响。在这里,我们开发了一种粗粒度的、优化的评分函数,用于初始采样和循环诱饵的排序。然后,通过全原子能量评分函数对生成的诱饵进行进一步优化,并对其进行排序。最终的集成技术称为能量辅助协议的循环预测,对于 325 个 12 残基测试环,其中位数为 2.1Å均方根偏差(RMSD),对于 45 个 12 残基环,其来自结构预测技术关键评估(CASP)10 个靶蛋白的天然核心结构(骨架和侧链)的 RMSD 为 2.0Å。如果在没有靶环的情况下预测蛋白质核心中所有侧链构象,那么环预测的准确性仅略有降低(在 CASP 靶蛋白中 12 个残基环的 RMSD 中存在 0.2Å的差异)。获得的准确性比我们测试的其他方法提高了约 1Å RMSD 或更多。适用于 Linux 系统的可执行文件可在 http://sparks-lab.org 上供学术用户免费使用。

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