Bordoli Lorenza, Kiefer Florian, Schwede Torsten
Biozentrum University of Basel, Basel, Switzerland.
Proteins. 2007;69 Suppl 8:129-36. doi: 10.1002/prot.21671.
Intrinsically unstructured regions in proteins have been associated with numerous important biological cellular functions. As measuring native disorder experimentally is technically challenging, computational methods for prediction of disordered regions in a protein have gained much interest in recent years. As part of the seventh Critical Assessment of Techniques for Protein Structure Prediction (CASP7), we have assessed 19 methods for disorder prediction based on their results for 96 target proteins. Prediction accuracy was assessed using detailed numerical comparison between the predicted disorder and the experimental structures. On average, methods participating in CASP7 have improved accuracy in comparison to the previous assessment in CASP6. Overall, however, no improvement over the best methods in CASP6 was observed in CASP7. Significant differences between different prediction methods were identified with regard to their sensitivity and specificity in correctly predicting ordered and disordered residues based on a protein target sequence, which is of relevance for practical applications of these computational tools.
蛋白质中的内在无序区域与众多重要的生物细胞功能相关联。由于通过实验测量天然无序状态在技术上具有挑战性,近年来用于预测蛋白质中无序区域的计算方法备受关注。作为第七届蛋白质结构预测技术关键评估(CASP7)的一部分,我们基于96个目标蛋白质的结果评估了19种无序预测方法。通过将预测的无序状态与实验结构进行详细的数值比较来评估预测准确性。平均而言,与CASP6中的先前评估相比,参与CASP7的方法提高了准确性。然而,总体而言,在CASP7中未观察到比CASP6中的最佳方法有改进。基于蛋白质目标序列正确预测有序和无序残基时,不同预测方法在敏感性和特异性方面存在显著差异,这与这些计算工具的实际应用相关。