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

我们使用我们最近开发的描述蛋白质稳定性的自由能函数来预测蛋白质的结构，该函数的重点是溶剂化热力学。该功能结合了目前最可靠的采样方法，即片段拼装(FA)和比较建模(CM)。这一预测使用了11种可以获得高分辨率晶体结构的小蛋白进行了验证。对于所有病例，都成功地获得了平均Cα均方差为2.0A的较精确的模型。通过对本征结构进行粗粒度简正模分析的穷举采样表明，我们的函数与RMSDs&lt；3.0a呈线性相关。这些结果表明，该函数对蛋白质结构的预测是相当可靠的，但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.