Niermann T, Kirschner K
Abteilung Biophysikalische Chemie, University of Basel, Switzerland.
Protein Eng. 1991 Feb;4(3):359-70. doi: 10.1093/protein/4.3.359.
The information contained in aligned sets of homologous protein sequences should improve the score of secondary structure prediction. Seven different enzymes having the (beta/alpha)8 or TIM-barrel fold were used to optimize the prediction with regard to this class of enzymes. The alpha-helix, beta-strand and loop propensities of the Garnier-Osguthorpe-Robson method were averaged at aligned residue positions, leading to a significant improvement over the average score obtained from single sequences. The increased accuracy correlates with the average sequence variability of the aligned set. Further improvements were obtained by using the following averaged properties as weights for the averaged state propensities: amphipathic moment and alpha-helix; hydropathy and beta-strand; chain flexibility and loop. The clustering of conserved residues at the C-terminal ends of the beta-strands was used as an additional positive weight for beta-strand propensity and increased the prediction of otherwise unpredicted beta-strands decisively. The automatic weighted prediction method identifies greater than 95% of the secondary structure elements of the set of seven TIM-barrel enzymes.
同源蛋白质序列比对集中包含的信息应能提高二级结构预测的得分。使用了七种具有(β/α)8或TIM桶状折叠的不同酶来针对此类酶优化预测。在比对的残基位置对Garnier-Osguthorpe-Robson方法的α螺旋、β链和环倾向进行平均,相比于从单序列获得的平均得分有显著提高。准确性的提高与比对集的平均序列变异性相关。通过使用以下平均性质作为平均状态倾向的权重,进一步提高了预测效果:两亲矩和α螺旋;亲水性和β链;链柔性和环。β链C末端保守残基的聚类用作β链倾向的额外正权重,并决定性地增加了对原本无法预测的β链的预测。自动加权预测方法识别出了七种TIM桶状酶集合中超过95%的二级结构元件。