QSAR MODELING OF ANTIBACTERIAL ACTIVITY WITH 1,2,4-TRIAZOLE DERIVATIVES
Abstract
Purpose. Development of effective QSAR models for predicting antibacterial activity for 1,2,4-triazole derivatives.
Materials and methods. Experimental data on the antibacterial activity of 1,2,4-triazole derivatives served as the material for scientific research. The research was carried out using the following methods: QSAR modeling, programming, regression multivariate analysis using molecular descriptors.
Results. The paper describes and analyzes mathematical models for predicting antibacterial activity based on the physical and chemical parameters of chemicals. Computational experiments were carried out, which demonstrated the effectiveness of the proposed models. Comparative analysis of the models revealed the model with the best statistical characteristics: MAE=0.11; MAPE=10.74; forecast accuracy=89.26%; MSE=0.0186; RMSE=0.1363.
Conclusion. QSAR models were developed to predict the antibacterial activity of twenty-eight 1,2,4-triazole derivatives. From one to six molecular descriptors generated automatically from structural formulas were used as factors in the models. The best models are selected based on the calculated statistical characteristics.
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