STATISTICAL MECHANICS OF PROTEIN FOLDING

蛋白质折叠的统计力学已经提出了许多理论，通常来自结构较少的系统，如随机杂聚物，扩散成核，随机能量或自旋玻璃的理论。虽然这些方法确实捕捉到了真实的蛋白质物理化学的一些重要特征，如折叠的协同性和从无规卷曲状态快速折叠，但它们的推导需要对多肽的平均行为做出一些广泛的假设。事实上，具有生物相关性的蛋白质由明显非常罕见的、中等长度的氨基酸序列组成，这些氨基酸序列允许链快速折叠成独特的复杂天然构象，这在很大程度上取决于序列。这表明，集中在长链杂聚物的平均性能的理论可能是过度概括和忽视的重要特征，罕见的序列折叠罕见的构象。另一方面，无论是自然界还是计算机都没有足够的时间来彻底探索即使是小蛋白质的所有构象和所有序列。这里的想法是通过减少链长、每个残基的构象状态数和氨基酸类型的选择，直到所有序列和所有构象都可以被详尽地枚举，来简化多肽的其他现实表示。通过在计算上可行的范围内改变这些参数，可以检测一般结论并外推到对应于真实的蛋白质的参数值。由于这个模型与大多数理论如此不同，它能够测试他们关于蛋白质折叠的假设和结论，例如能量景观的性质和描述向天然状态发展的顺序参数。需要解决的问题包括：是否有一个通用的方法来描述所有蛋白质的折叠，或者一些蛋白质通过一个可识别的途径进行折叠，而另一些蛋白质则有无数的途径？这个模型能否再现和解释目前关于某些特定蛋白质折叠机制和中间体的实验结果？

Many theories have been proposed for the statistical mechanics of protein folding, typically derived from theories for less structured systems, such as random heteropolymers, diffusion-nucleation, random energies, or spin glasses. While these have certainly captured some important features of the physical chemistry of real proteins, such as cooperativity of folding and rapid folding from the random coil state, their derivation requires making some broad assumptions about the average behavior of polypeptides. In fact, the proteins of biological relevance consists of apparently very rare, moderately long amino acid sequences that permit the chain to fold rapidly- to a unique complicated native conformation, which depends greatly on the sequence. This suggests that theories focussing on average properties of long-chain heteropolymers may be over-generalizing and neglecting the important features of rare sequences folding to rare conformations. On the other hand, neither nature nor computer has sufficient time to exhaustively explore all conformations and all sequences for even small proteins. The idea here is to simply an otherwise realistic representation of polypeptides by reducing chain length, number of conformation states per residue, and choices of amino acid types until all sequences and all conformations can be exhaustively enumerated. By varying these parameters in the computationally feasible range, general conclusions can be detected and extrapolated to parameter values corresponding to real proteins. Since this model is so different from most theories, it is able to test their assumptions and conclusions about protein folding, such as the nature of the energy landscape and order parameters to describe the progress toward the native state. Questions to be addressed include: is there a general way to describe the folding of all proteins, or do some proceed by a recognizable pathway while others have innumerable routes? Can this model reproduce and explain the currently available experimental results on folding mechanisms and intermediates for certain particular proteins.