A hybrid of artificial intelligence simple and low computational cost QSAR was used. Approximately 90 pyridinylimidazole-based drug candidates with a range of potencies against p38R MAP kinase were investigated. To obtain more flexibility and effective capability of handling and processing information about the real world, in this case, the fuzzy set theory was introduced into the QSAR. An integration of multiple linear regression and artificial neural network with adaptive neuro-fuzzy inference systems (ANFIS) was developed to predict the inhibition activity. The algorithm of ANFIS was applied to identify the suitable variables and then to find the optimal descriptors. The gradient descent with momentum backpropagation ANN was used to establish the nonlinear multivariate relationships between the chemical structural parameters and biological response. A comparison between the result of the proposed linear and nonlinear regression showed the superiority of QSAR modeling by ANFIS-ANN method over the MLR. The results demonstrated that the ANFIS could be applied successfully as a feature selection. The appearance of Diam, Homo, and LogP descriptors in the model showed the importance of the steric, electronic, and thermodynamic interactions between a drug and its target site in the distribution of a compound within a biosystem and its interaction with competing for binding sites.

中文翻译：

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通过将模糊逻辑与MLR / ANN QSAR模型相结合，对候选药物数据集的抑制活性进行预测。

使用了一种简单，计算成本低的QSAR人工智能的混合体。研究了大约90种基于吡啶二胺基咪唑的候选药物，这些药物具有针对p38R MAP激酶的多种效力。为了获得更多的灵活性和有效的能力来处理和处理有关现实世界的信息，在这种情况下，将模糊集理论引入了QSAR。建立了多元线性回归和人工神经网络与自适应神经模糊推理系统（ANFIS）的集成，以预测抑制活性。应用ANFIS算法来识别合适的变量，然后找到最佳描述符。使用动量反向传播ANN的梯度下降来建立化学结构参数与生物学响应之间的非线性多元关系。线性和非线性回归结果的比较表明，通过ANFIS-ANN方法进行的QSAR建模优于MLR。结果表明，ANFIS可以成功地用作特征选择。该模型中Diam，Homo和LogP描述子的出现表明，在生物系统中化合物分布中，药物与其靶标位点之间的空间，电子和热力学相互作用的重要性以及与竞争性结合位点的相互作用。线性和非线性回归结果的比较表明，通过ANFIS-ANN方法进行的QSAR建模优于MLR。结果表明，ANFIS可以成功地用作特征选择。该模型中Diam，Homo和LogP描述子的出现表明，在生物系统中化合物分布中，药物与其靶标位点之间的空间，电子和热力学相互作用的重要性以及与竞争性结合位点的相互作用。线性和非线性回归结果的比较表明，通过ANFIS-ANN方法进行的QSAR建模优于MLR。结果表明，ANFIS可以成功地用作特征选择。该模型中Diam，Homo和LogP描述子的出现表明，在生物系统中化合物分布中，药物与其靶标位点之间的空间，电子和热力学相互作用的重要性以及与竞争性结合位点的相互作用。