Developing a method for predicting protein structure based on physical chemistry of liquid

我们预测蛋白质的结构，使用我们最近开发的自由能函数描述蛋白质的稳定性，这是集中在溶剂化热力学。该功能与目前最可靠的采样方法相结合，即。例如，片段组装（FA）和比较建模（CM）。使用11个小蛋白质的高分辨率晶体结构进行了测试的预测。相当准确的模型，平均Cα均方根偏差（RMSD）~ 2。所有病例均成功获得0 A。通过对天然结构周围的粗粒度正态模式分析的穷举采样表明，我们的函数具有RMSDs<3的线性相关性。0A.这些结果表明，该函数对于蛋白质结构预测是相当可靠的，而采样方法仍然是其主要限制因素之一。

We predicted protein structure using our recently developed free energy function for describing protein stability, which was focused on solvation thermodynamics. The function is combined with the current most reliable sampling methods, i. e., fragment assembly(FA) and comparative modeling(CM). The prediction was tested using 11 small proteins for which high-resolution crystal structures were available. Fairly accurate models with average Cαroot mean square deviation(RMSD)~ 2. 0 A were successfully obtained for all cases. The exhaustive sampling by coarse-grained normal mode analysis around the native structures reveals that our function has a linear correlation with RMSDs<3. 0A. These results suggest that the function is quite reliable for the protein structure prediction while the sampling method remains one of the its major limiting factors in it.