Park B, Levitt M
Department of Structural Biology, Stanford School of Medicine, CA 94305, USA.
J Mol Biol. 1996 May 3;258(2):367-92. doi: 10.1006/jmbi.1996.0256.
This study generates ensembles of decoy or test structures for eight small proteins with a variety of different folds. Between 35,000 and 200,000 decoys were generated for each protein using our four-state off-lattice model together with a novel relaxation method. These give compact self-avoiding conformations each constrained to have native secondary structure. Ensembles of these decoy conformations were used to test the ability of several types of empirical contact, surface area and distance-dependent energy functions to distinguish between correct and incorrect conformations. These tests have shown that none of the functions is able to distinguish consistently either the X-ray conformation or the near-native conformations from others which are incorrect. Certain combinations of two of these energy functions were able, however, consistently to identify X-ray structures from amongst the decoy conformations. These same combinations are better also at identifying near-native conformations, consistently finding them with a hundred-fold higher frequency than chance. The fact that these combination energy functions perform better than generally accepted energy functions suggests their future use in folding simulations and perhaps threading predictions.
本研究为8种具有不同折叠方式的小蛋白质生成了诱饵结构或测试结构的集合。使用我们的四态非晶格模型和一种新颖的松弛方法，为每种蛋白质生成了35000至200000个诱饵结构。这些结构给出了紧凑的自回避构象，每个构象都被约束具有天然二级结构。这些诱饵构象的集合用于测试几种类型的经验接触、表面积和距离依赖能量函数区分正确和错误构象的能力。这些测试表明，没有一种函数能够始终如一地将X射线构象或近天然构象与其他错误构象区分开来。然而，这些能量函数中的两种特定组合能够始终如一地从诱饵构象中识别出X射线结构。这些相同的组合在识别近天然构象方面也更好，始终以比随机情况高百倍的频率找到它们。这些组合能量函数比普遍接受的能量函数表现更好，这一事实表明它们未来可用于折叠模拟以及可能的穿线预测。
