All-atom chain-building by optimizing MODELLER energy function using conformational space annealing
All-atom chain-building by optimizing MODELLER energy function using conformational space annealing
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DOI：
10.1002/prot.22312
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发表时间：
2009-06-01
影响因子：
2.9
通讯作者：
Lee, Jooyoung
中科院分区：
文献类型：
--
作者：
Joo, Keehyoung;Lee, Jinwoo;Lee, Jooyoung
我们已经研究了严格优化的MODELLER能量函数可能改善蛋白质全原子链建设的效果。为此，我们采用了全局优化方法称为构象空间退火（CSA）的标准MODELLER程序，以实现更好的能量优化比MODELLER提供。该方法，我们称之为MODELLERCSA，在两个基准集进行测试。第一个是取自HOW STRAD多重比对集的298种蛋白质。通过简单地优化MODELLER能量函数，我们观察到侧链建模的显著改善，其中MODELLERCSA与标准MODELLER建模相比，对chi（1）（chi（1）+ chi（2））准确性提供了约10.7%（14.5%）的改善。骨干精度的改进MODELLERCSA被证明是不太突出的，和类似的改进可以通过简单地生成许多标准MODELLER模型，并选择最低的能量模型。然而，MODELLERCSA的侧链建模准确性水平无法通过广泛的MODELLER策略，SCWRL3的侧链重塑或复制未突变的旋转异构体来匹配。同样的程序成功地应用于100 CASP7模板库建模域在预测季节在一个盲目的方式，结果包括在这里进行比较。从这项研究中，我们观察到MODELLER能量和侧链准确度之间有很好的相关性。我们的研究结果表明，当一个目标蛋白质和它的模板之间提供了一个良好的对齐，彻底优化的MODELLER能量函数导致准确的全原子模型。
We have investigated the effect of rigorous optimization of the MODELLER energy function for possible improvement in protein all-atom chain-building. For this we applied the global optimization method called conformational space annealing (CSA) to the standard MODELLER procedure to achieve better energy optimization than what MODELLER provides. The method, which we call MODELLERCSA, is tested on two benchmark sets. The first is the 298 proteins taken from the HOW STRAD multiple alignment set. By simply optimizing the MODELLER energy function, we observe significant improvement in side-chain modeling, where MODELLERCSA provides about 10.7% (14.5%) improvement for chi(1) (chi(1) + chi(2)) accuracy compared to the standard MODELLER modeling. The improvement of backbone accuracy by MODELLERCSA is shown to be less prominent, and a similar improvement can be achieved by simply generating many standard MODELLER models and selecting lowest energy models. However, the level of side-chain modeling accuracy by MODELLERCSA could not be matched either by extensive MODELLER strategies, side-chain remodeling by SCWRL3, or copying unmutated rotamers. The identical procedure was successfully applied to 100 CASP7 template base modeling domains during the prediction season in a blind fashion, and the results are included here for comparinson. From this study, we observe a good correlation between the MODELLER energy and the side-chain accuracy. Our findings indicate that, when a good alignment between a target protein and its templates is provided, thorough optimization of the MODELLER energy function leads to accurate all-atom models.