Levin J M, Garnier J
Laboratoire de Biochimie physique, INRA, Université de Paris Sud, Orsay, France.
Biochim Biophys Acta. 1988 Aug 10;955(3):283-95. doi: 10.1016/0167-4838(88)90206-3.
This report describes an optimised version of a secondary structure prediction method based on local homologies, using a new data base. A 63% prediction accuracy, for three states, was obtained after elimination of the protein to be predicted and all proteins with a percentage identity greater than 22% from the data base. This corresponds to a 5% increase in accuracy on the original method (Levin et al. FEBS Lett. 205 (1986) 303-308). The flexibility of the method to the incorporation of information extraneous to the prediction was demonstrated by the prediction of the homologous proteins in the data base. Using the percentage identity with the protein to be predicted, to weight the relative importance of each protein, for all proteins with a percentage identity greater than 30%, the mean correct prediction per chain was 87%. As a result this algorithm can be used during the molecular modelling process, both to give an idea of the structural similarity between two proteins and as an aid in the determination of the best alignment. Incorporation of the result of a protein folding type assignment based on the global amino-acid composition increased the overall prediction to 66%.
本报告描述了一种基于局部同源性的二级结构预测方法的优化版本，该方法使用了一个新的数据库。在从数据库中剔除待预测蛋白质以及所有同源性百分比大于22%的蛋白质后，对于三种状态获得了63%的预测准确率。这比原始方法（Levin等人，《欧洲生物化学学会联合会快报》205 (1986) 303 - 308）的准确率提高了5%。通过对数据库中同源蛋白质的预测，证明了该方法对纳入预测无关信息的灵活性。对于所有同源性百分比大于30%的蛋白质，使用与待预测蛋白质的同源性百分比来权衡每种蛋白质的相对重要性，每条链的平均正确预测率为87%。因此，该算法可用于分子建模过程，既可以了解两种蛋白质之间的结构相似性，也有助于确定最佳比对。基于全局氨基酸组成的蛋白质折叠类型分配结果的纳入将总体预测提高到了66%。
