Assessing model accuracy using the homology modeling automatically software
Assessing model accuracy using the homology modeling automatically software
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DOI：
10.1002/prot.21466
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发表时间：
2008-01-01
影响因子：
2.9
通讯作者：
Montelione, Gaetano T.
中科院分区：
文献类型：
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作者：
Bhattacharya, Aneerban;Wunderlich, Zeba;Montelione, Gaetano T.
同源建模是一种强大的技术，通过使用一个蛋白质的结构信息来预测同源蛋白质的结构，大大增加了实验结构确定的价值。我们先前已经描述了通过满足空间约束进行同源建模的方法（Li等人，Protein Sci 1997，6.956 -970）。Homology Modeling Automatically（HOMA）网站是一个新的工具，使用该方法基于靶蛋白与模板蛋白的序列比对和模板的结构坐标来预测靶蛋白的3D结构。用户将看到生成的模型，以及广泛的结构验证报告，该报告提供了对生成的同源性模型质量的关键评估。使用24组同源蛋白质评估和验证HOMA所采用的同源建模方法。使用HOMA，同源性模型生成的510个蛋白质，包括264个蛋白质建模与正确的折叠和246个建模与不正确的折叠。这些模型的精度进行了评估，通过叠加在相应的实验确定的结构。这些结果的一个子集进行了比较，使用其他几种自动同源建模方法的建模精度的平行研究。总的来说，HOMA提供了与其他最先进的同源性建模方法相似的预测精度。我们还提供了几个结构质量验证工具的评估与HOMA生成的同源性模型的准确性的评估。该研究表明，Verify 3D（Luthy等人，Nature 1992，356.83 -85）和ProsaII（Sippl，Proteins 1993，17.355 -362）在区分具有正确或不正确折叠的同源模型方面是最灵敏的。对于具有正确折叠的同源性模型，空间构象能（主要包括货车德瓦尔斯能）、MolProbity clashscore（Word等人，Protein Sci 2000，9：2251-2259）和PROTEINS G-因子（Laskowski等人，J Biomol NMR 1996;8：477-486）提供了用于评估准确性的灵敏且一致的方法，并且可以区分较高和较低准确性的同源性模型。如所附论文（Bhattacharya等人，随附的论文），这些分数的组合为HOMA生成的模型提供了区分低精度模型和高精度模型的基础。
Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997,6.956-970). The Homology Modeling Automatically (HOMA) web site, , is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992,356.83-85) and ProsaII (Sippl, Proteins 1993,17.355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000,9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.