Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment
Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment
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DOI：
10.1093/bioinformatics/bth044
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发表时间：
2004-05-01
期刊：
影响因子：
5.8
通讯作者：
Skolnick, J
中科院分区：
文献类型：
--
作者：
Arakaki, AK;Zhang, Y;Skolnick, J
动机：几种蛋白质功能预测方法采用在生物相关位点的三维（3D）描述符中捕获的结构特征。这些方法应用于高分辨率结构是成功的，但它们在低分辨率预测结构中的检测能力仅在少数情况下进行了测试。结果：基于从公共数据库中自动提取的功能和结构信息，开发了一种自动生成3D功能描述符库的方法，用于基于结构的酶活性位点预测（自动功能模板，共593个，用于162种不同的酶），并使用诱饵结构进行了评估。通过分析从酶的天然结构中得到的不同质量的诱饵，对预测结构的适用性进行了研究。对于35%的诱饵结构，我们的方法可以识别出与原始结构有3-4埃坐标均方根偏差的模型中的活性位点，这是使用最先进的蛋白质结构预测算法可以达到的质量。
Motivation: Several protein function prediction methods employ structural features captured in three-dimensional (3D) descriptors of biologically relevant sites. These methods are successful when applied to high-resolution structures, but their detection ability in lower resolution predicted structures has only been tested for a few cases.Results: A method that automatically generates a library of 3D functional descriptors for the structure-based prediction of enzyme active sites (automated functional templates, 593 in total for 162 different enzymes), based on functional and structural information automatically extracted from public databases, has been developed and evaluated using decoy structures. The applicability to predicted structures was investigated by analyzing decoys of varying quality, derived from enzyme native structures. For 35% of decoy structures, our method identifies the active site in models having 3-4 Angstrom coordinate root mean square deviation from the native structure, a quality that is reachable using state of the art protein structure prediction algorithms.