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首页> 外文期刊>Medicinal Chemistry Research >Prediction of the binding affinities of adenosine A2A receptor antagonists based on the heuristic method and support vector machine
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Prediction of the binding affinities of adenosine A2A receptor antagonists based on the heuristic method and support vector machine

机译:基于启发式方法和支持向量机的腺苷A 2A 受体拮抗剂的结合亲和力预测

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Support vector machine (SVM) was used to develop a nonlinear quantitative structure–activity relationship (QSAR) model for the prediction of the activities of the adenosine A2A receptor antagonists. Six molecular descriptors selected by the heuristic method (HM) in CODESSA were used as inputs for SVM. The results obtained by SVM were compared with those obtained by HM. The mean squared errors (MSEs) for the training set given by HM and SVM are 0.08 and 0.05, respectively, which shows the performance of SVM model is better than that of the HM model.
机译:利用支持向量机(SVM)建立了非线性定量构效关系(QSAR)模型,用于预测腺苷A 2A 受体拮抗剂的活性。通过CODESSA中的启发式方法(HM)选择的六个分子描述符用作SVM的输入。将SVM获得的结果与HM获得的结果进行比较。 HM和SVM给出的训练集的均方误差(MSE)分别为0.08和0.05,这表明SVM模型的性能优于HM模型。

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    《Medicinal Chemistry Research 》 |2011年第8期| p.1220-1228| 共9页
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