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K-Fold: a tool for the prediction of the protein folding kinetic order and rate

机译:K-Fold:用于预测蛋白质折叠动力学顺序和速率的工具

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K-Fold is a tool for the automatic prediction of the protein folding kinetic order and rate. The tool is based on a support vector machine (SVM) that was trained on a data set of 63 proteins, whose 3D structure and folding mechanism are known from experiments already described in the literature. The method predicts whether a protein of known atomic structure folds according to a two-state or a multi-state kinetics and correctly classifies 81% of the folding mechanisms when tested over the training set of the 63 proteins. It also predicts as a further option the logarithm of the folding rate. To the best of our knowledge, the tool discriminates for the first time whether a protein is characterized by a two state or a multiple state kinetics, during the folding process, and concomitantly estimates also the value of the constant rate of the process. When used to predict the logarithm of the folding rate, K-Fold scores with a correlation value to the experimental data of 0.74 (with a SE of 1.2).
机译:K-Fold是用于自动预测蛋白质折叠动力学顺序和速率的工具。该工具基于在63种蛋白质的数据集上训练的支持向量机(SVM),其3D结构和折叠机制可从文献中已经描述的实验中获知。该方法预测已知原子结构的蛋白质是根据两种状态还是多态动力学折叠,并在63种蛋白质的训练集上进行测试时正确分类了81%的折叠机制。它还可以预测折叠率的对数作为进一步的选择。据我们所知,该工具首次在折叠过程中区分蛋白质是处于两种状态还是多种状态的动力学特征,并随之估算出恒定速率的值。当用于预测折叠率的对数时,K-Fold得分与实验数据为0.74(SE为1.2)具有相关性。

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