I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.
I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.
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I-Mutant2.0：预测蛋白质序列或结构突变的稳定性变化。
DOI：
10.1093/nar/gki375
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发表时间：
2005-07-01
影响因子：
14.9
通讯作者：
Casadio, R
中科院分区：
文献类型：
--
作者：
Capriotti, E;Fariselli, P;Casadio, R
I-MuS 2.0是一个基于支持向量机（SVM）的工具，用于自动预测单点突变后蛋白质的稳定性变化。从蛋白质结构或更重要的是从蛋白质序列开始进行I-Mufficient 2.0预测。据我们所知，后一项任务是第一次利用的。该方法在来自ProTherm的数据集上进行了训练和测试，ProTherm是目前最全面的蛋白质在不同条件下突变时稳定性的自由能变化的热力学实验数据库。I-Muc 2.0既可用作预测突变后蛋白质稳定性变化的标志的分类器，又可用作预测相关ΔΔG值的回归估计器。作为一个分类器，I-Musimetry 2.0正确预测（交叉验证程序）80%或77%的数据集，这取决于结构或序列信息的使用，分别。当预测与突变相关的ΔΔG值时，当分别采用结构或序列信息时，预测值与预期值/实验值的相关性为0.71（标准误差为1.30 kcal/mol）和0.62（标准误差为1.45 kcal/mol）。我们的网络界面允许选择预测模式，这取决于蛋白质结构和/或序列的可用性。在后一种情况下，Web服务器只需要以原始格式粘贴蛋白质序列。因此，我们引入了I-Musister 2.0作为蛋白质设计的独特而有价值的助手，即使蛋白质结构尚未以原子分辨率已知。可用性：
I-Mutant2.0 is a support vector machine (SVM)-based tool for the automatic prediction of protein stability changes upon single point mutations. I-Mutant2.0 predictions are performed starting either from the protein structure or, more importantly, from the protein sequence. This latter task, to the best of our knowledge, is exploited for the first time. The method was trained and tested on a data set derived from ProTherm, which is presently the most comprehensive available database of thermodynamic experimental data of free energy changes of protein stability upon mutation under different conditions. I-Mutant2.0 can be used both as a classifier for predicting the sign of the protein stability change upon mutation and as a regression estimator for predicting the related ΔΔG values. Acting as a classifier, I-Mutant2.0 correctly predicts (with a cross-validation procedure) 80% or 77% of the data set, depending on the usage of structural or sequence information, respectively. When predicting ΔΔG values associated with mutations, the correlation of predicted with expected/experimental values is 0.71 (with a standard error of 1.30 kcal/mol) and 0.62 (with a standard error of 1.45 kcal/mol) when structural or sequence information are respectively adopted. Our web interface allows the selection of a predictive mode that depends on the availability of the protein structure and/or sequence. In this latter case, the web server requires only pasting of a protein sequence in a raw format. We therefore introduce I-Mutant2.0 as a unique and valuable helper for protein design, even when the protein structure is not yet known with atomic resolution. Availability: .
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影响因子：
5.6
作者：
Guerois, R;Nielsen, JE;Serrano, L
通讯作者：
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作者：
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通讯作者：
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作者：
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通讯作者：
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