Ghosh Kingshuk, Dill Ken A
Department of Physics, University of Denver, Denver, CO 80209, USA.
Proc Natl Acad Sci U S A. 2009 Jun 30;106(26):10649-54. doi: 10.1073/pnas.0903995106. Epub 2009 Jun 17.
New amino acid sequences of proteins are being learned at a rapid rate, thanks to modern genomics. The native structures and functions of those proteins can often be inferred using bioinformatics methods. We show here that it is also possible to infer the stabilities and thermal folding properties of proteins, given only simple genomics information: the chain length and the numbers of charged side chains. In particular, our model predicts DeltaH(T), DeltaS(T), DeltaC(p), and DeltaF(T)--the folding enthalpy, entropy, heat capacity, and free energy--as functions of temperature T; the denaturant m values in guanidine and urea; the pH-temperature-salt phase diagrams, and the energy of confinement F(s) of the protein inside a cavity of radius s. All combinations of these phase equilibria can also then be computed from that information. As one illustration, we compute the pH and salt conditions that would denature a protein inside a small confined cavity. Because the model is analytical, it is computationally efficient enough that it could be used to automatically annotate whole proteomes with protein stability information.
借助现代基因组学,蛋白质新的氨基酸序列正以很快的速度被了解。利用生物信息学方法常常可以推断出这些蛋白质的天然结构和功能。我们在此表明,仅给出简单的基因组学信息:链长和带电侧链的数量,就有可能推断出蛋白质的稳定性和热折叠特性。特别是,我们的模型预测了ΔH(T)、ΔS(T)、ΔC(p)和ΔF(T)——折叠焓、熵、热容和自由能——作为温度T的函数;在胍和尿素中的变性剂m值;pH - 温度 - 盐相图,以及蛋白质在半径为s的腔内的受限能量F(s)。然后,所有这些相平衡的组合也都可以根据该信息计算出来。作为一个示例,我们计算了在小的受限腔内使蛋白质变性的pH和盐条件。由于该模型是解析性的,其计算效率足够高,以至于可用于用蛋白质稳定性信息自动注释整个蛋白质组。