Weng Z, Vajda S, Delisi C
Department of Biomedical Engineering, Boston University, Massachusetts 02215, USA.
Protein Sci. 1996 Apr;5(4):614-26. doi: 10.1002/pro.5560050406.
A long sought goal in the physical chemistry of macromolecular structure, and one directly relevant to understanding the molecular basis of biological recognition, is predicting the geometry of bimolecular complexes from the geometries of their free monomers. Even when the monomers remain relatively unchanged by complex formation, prediction has been difficult because the free energies of alternative conformations of the complex have been difficult to evaluate quickly and accurately. This has forced the use of incomplete target functions, which typically do no better than to provide tens of possible complexes with no way of choosing between them. Here we present a general framework for empirical free energy evaluation and report calculations, based on a relatively complete and easily executable free energy function, that indicate that the structures of complexes can be predicted accurately from the structures of monomers, including close sequence homologues. The calculations also suggest that the binding free energies themselves may be predicted with reasonable accuracy. The method is compared to an alternative formulation that has also been applied recently to the same data set. Both approaches promise to open new opportunities in macromolecular design and specificity modification.
高分子结构物理化学中一个长期追求的目标,也是与理解生物识别分子基础直接相关的一个目标,是从其游离单体的几何结构预测双分子复合物的几何结构。即使单体在形成复合物时相对不变,预测也一直很困难,因为复合物的替代构象的自由能很难快速准确地评估。这就迫使人们使用不完整的目标函数,而这些函数通常只能提供几十种可能的复合物,却没有办法在它们之间进行选择。在此,我们提出了一个用于经验自由能评估的通用框架,并报告了基于一个相对完整且易于执行的自由能函数的计算结果,这些结果表明可以从单体的结构,包括紧密的序列同源物,准确预测复合物的结构。计算还表明,结合自由能本身也可以以合理的准确度进行预测。该方法与最近也应用于同一数据集的另一种公式化方法进行了比较。这两种方法都有望在高分子设计和特异性修饰方面开辟新的机会。