Lazaridis T, Karplus M
Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford St, Cambridge, MA, 02138, USA.
J Mol Biol. 1999 May 7;288(3):477-87. doi: 10.1006/jmbi.1999.2685.
An essential requirement for theoretical protein structure prediction is an energy function that can discriminate the native from non-native protein conformations. To date most of the energy functions used for this purpose have been extracted from a statistical analysis of the protein structure database, without explicit reference to the physical interactions responsible for protein stability. The use of the statistical functions has been supported by the widespread belief that they are superior for such discrimination to physics-based energy functions. An effective energy function which combined the CHARMM vacuum potential with a Gaussian model for the solvation free energy is tested for its ability to discriminate the native structure of a protein from misfolded conformations; the results are compared with those obtained with the vacuum CHARMM potential. The test is performed on several sets of misfolded structures prepared by others, including sets of about 650 good decoys for six proteins, as well as on misfolded structures of chymotrypsin inhibitor 2. The vacuum CHARMM potential is successful in most cases when energy minimized conformations are considered, but fails when applied to structures relaxed by molecular dynamics. With the effective energy function the native state is always more stable than grossly misfolded conformations both in energy minimized and molecular dynamics-relaxed structures. The present results suggest that molecular mechanics (physics-based) energy functions, complemented by a simple model for the solvation free energy, should be tested for use in the inverse folding problem, and supports their use in studies of the effective energy surface of proteins in solution. Moreover, the study suggests that the belief in the superiority of statistical functions for these purposes may be ill founded.
理论蛋白质结构预测的一个基本要求是要有一个能区分天然蛋白质构象和非天然蛋白质构象的能量函数。迄今为止，用于此目的的大多数能量函数都是从蛋白质结构数据库的统计分析中提取的，没有明确提及导致蛋白质稳定性的物理相互作用。统计函数的使用得到了广泛认可，人们普遍认为它们在这种区分方面比基于物理的能量函数更优越。测试了一种将CHARMM真空势与溶剂化自由能的高斯模型相结合的有效能量函数区分蛋白质天然结构与错误折叠构象的能力；并将结果与使用真空CHARMM势得到的结果进行了比较。测试是在其他人制备的几组错误折叠结构上进行的，包括针对六种蛋白质的约650个良好诱饵集，以及胰凝乳蛋白酶抑制剂2的错误折叠结构。当考虑能量最小化构象时，真空CHARMM势在大多数情况下是成功的，但应用于通过分子动力学松弛的结构时则失败。使用有效能量函数时，在能量最小化结构和分子动力学松弛结构中，天然状态总是比严重错误折叠的构象更稳定。目前的结果表明，分子力学（基于物理的）能量函数，辅以简单的溶剂化自由能模型，应该在逆折叠问题中进行测试，并支持它们用于研究溶液中蛋白质的有效能量表面。此外，该研究表明，认为统计函数在此类目的上具有优越性的观点可能没有根据。
