Tanaka S, Scheraga H A
Macromolecules. 1976 Sep-Oct;9(5):812-33. doi: 10.1021/ma60053a024.
One-dimensional short-range interaction models for specific-sequence copolymers of amino acids are being developed in this series of papers. In this paper, our earlier three-state model [involving helical (h), extended (epsilon), and coil (or other) (c) states] is extended to a four-state model by preserving the h and epsilon states, introducing the chain-reversal state (R and S), and redefining the c state. This model involves six parameters (wh, vh, vepsilon, vR, vS, and uc) and requires a 6 X 6 statistical weight matrix. A nearest-neighbor approximation of the four-state model is also formulated; it requires a 5 X 5 matrix, involving the same six parameters. By expressing the statistical weights relative to that of the epsilon state, only five parameters (wh, vh, vR, vS, and uc) are required in both the 6 X 6 and 5 X 5 matrices. The statistical weights for the four-state model are evaluated from the atomic coordinates of the x-ray structures of 26 native proteins. These statistical weights, and the four-state model, are used to develop a procedure to predict the backbone conformations of proteins. Since the prediction of helical and extended conformations is carried out by the procedure described in papers 1-3 of this series, we focus particular attention on chain-reversal conformations in this paper. The conformational-sequence probabilities of finding a residue in h, epsilon, R, S, or c states, and of finding two consecutive residues in a chain-reversal conformation, defined as relative values with respect to their average values over the whole molecule, are calculated for 23 proteins. By comparing these conformational-sequence probabilities to experimental X-ray observations, it was found that, in addition to the prediction of helical and extended conformations (reported in paper 3), 219 chain-reversal regions out of 372 observed by x-ray diffraction studies of 23 proteins were predicted correctly. These results suggest that the assumption of the dominance of short-range interactions in determining chain-reversal (as well as helical or extended) conformations in proteins, on which the predictive scheme is based, is a reasonable one. Finally, in the Appendix, the property of asymmetric nucleation of helical sequences is introduced into the (nearest-neighbor) four-state model.
在这一系列论文中，正在开发用于氨基酸特定序列共聚物的一维短程相互作用模型。在本文中，我们早期的三态模型（涉及螺旋态（h）、伸展态（ε）和无规线团态（或其他）（c））通过保留h态和ε态、引入链反转态（R和S）并重新定义c态扩展为四态模型。该模型涉及六个参数（wh、vh、vepsilon、vR、vS和uc），并需要一个6×6的统计权重矩阵。还构建了四态模型的最近邻近似；它需要一个5×5的矩阵，包含相同的六个参数。通过相对于ε态的统计权重来表示，6×6和5×5矩阵都只需要五个参数（wh、vh、vR、vS和uc）。四态模型的统计权重是根据26种天然蛋白质的X射线结构的原子坐标评估得到的。这些统计权重以及四态模型被用于开发一种预测蛋白质主链构象的方法。由于螺旋态和伸展态构象的预测是通过本系列论文1 - 3中描述的方法进行的，所以在本文中我们特别关注链反转构象。对于23种蛋白质，计算了在h、ε、R、S或c态中找到一个残基的构象 - 序列概率，以及在链反转构象中找到两个连续残基的概率，这些概率被定义为相对于整个分子平均值的相对值。通过将这些构象 - 序列概率与实验X射线观测结果进行比较，发现除了螺旋态和伸展态构象的预测（在论文3中报道）之外，在对23种蛋白质的X射线衍射研究中观察到的372个链反转区域中有219个被正确预测。这些结果表明，预测方案所基于的关于短程相互作用在决定蛋白质链反转（以及螺旋态或伸展态）构象中起主导作用的假设是合理的。最后，在附录中，将螺旋序列的不对称成核性质引入到（最近邻）四态模型中。
