Quality assessment of predicted protein models using energies calculated by the fragment molecular orbital method
Quality assessment of predicted protein models using energies calculated by the fragment molecular orbital method
复制标题
使用片段分子轨道法计算的能量对预测蛋白质模型进行质量评估
DOI：
10.1002/minf.201400108
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Shinichiro
中科院分区：
文献类型：
--
作者：
5. David Simonecini;Hiroya Nakata Koii Ogata;Shinichiro
直接从序列预测蛋白质结构是计算生物学中一个非常具有挑战性的问题。最成功的方法之一是采用随机构象采样来搜索经验导出的能量函数景观的全局能量最小状态。由于经验导出的能量函数中的误差，最低能量构象可能不是最佳模型。我们已经评估了使用碎片分子轨道方法（FMO能量）计算的能量来评估预测模型的质量及其在预测模型的集合中识别最佳模型的能力。利用GAMESS中的碎片分子轨道方法计算了预测模型的FMO能量。当对8个蛋白质靶点进行测试时，我们发现，当这些模型之间存在足够的多样性时，基于FMO能量的模型排名优于基于经验推导的能量。该模型多样性可以在FMO能量计算之前估计。我们的结果表明，FMO能量计算的碎片分子轨道方法是一个实用的和有前途的措施，评估蛋白质模型的质量和选择最好的蛋白质模型中产生的许多。
Protein structure prediction directly from sequences is a very challenging problem in computational biology. One of the most successful approaches employs stochastic conformational sampling to search an empirically derived energy function landscape for the global energy minimum state. Due to the errors in the empirically derived energy function, the lowest energy conformation may not be the best model. We have evaluated the use of energy calculated by the fragment molecular orbital method (FMO energy) to assess the quality of predicted models and its ability to identify the best model among an ensemble of predicted models. The fragment molecular orbital method implemented in GAMESS was used to calculate the FMO energy of predicted models. When tested on eight protein targets, we found that the model ranking based on FMO energies is better than that based on empirically derived energies when there is sufficient diversity among these models. This model diversity can be estimated prior to the FMO energy calculations. Our result demonstrates that the FMO energy calculated by the fragment molecular orbital method is a practical and promising measure for the assessment of protein model quality and the selection of the best protein model among many generated.