Samudrala R, Huang E S, Koehl P, Levitt M
Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Protein Eng. 2000 Jul;13(7):453-7. doi: 10.1093/protein/13.7.453.
Is there value in constructing side chains while searching protein conformational space during an ab initio simulation? If so, what is the most computationally efficient method for constructing these side chains? To answer these questions, four published approaches were used to construct side chain conformations on a range of near-native main chains generated by ab initio protein structure prediction methods. The accuracy of these approaches was compared with a naive approach that selects the most frequently observed rotamer for a given amino acid to construct side chains. An all-atom conditional probability discriminatory function is useful at selecting conformations with overall low all-atom root mean square deviation (r.m.s.d.) and the discrimination improves on sets that are closer to the native conformation. In addition, the naive approach performs as well as more sophisticated methods in terms of the percentage of chi(1) angles built accurately and the all-atom r. m.s.d., between the native and near-native conformations. The results suggest that the naive method would be extremely useful for fast and efficient side chain construction on vast numbers of conformations for ab initio prediction of protein structure.
在从头算模拟中搜索蛋白质构象空间时构建侧链有价值吗？如果有，构建这些侧链的计算效率最高的方法是什么？为了回答这些问题，我们使用了四种已发表的方法，在一系列由从头算蛋白质结构预测方法生成的近天然主链上构建侧链构象。将这些方法的准确性与一种简单方法进行了比较，该简单方法为给定氨基酸选择最常观察到的旋转异构体来构建侧链。全原子条件概率判别函数在选择具有总体低全原子均方根偏差（r.m.s.d.）的构象时很有用，并且在更接近天然构象的集合上判别能力有所提高。此外，就准确构建的χ(1)角的百分比以及天然构象和近天然构象之间的全原子r.m.s.d.而言，简单方法与更复杂的方法表现相当。结果表明，该简单方法对于在大量构象上进行快速高效的侧链构建以进行蛋白质结构的从头算预测将非常有用。
