QSAR MODELING OF ANTIFUNGAL ACTIVITY OF 1,2,4-TRIAZOLE DERIVATIVES

Abstract

Purpose. Development of QSAR models and investigation of their effectiveness for predicting antifungal activity of 1,2,4-triazole derivatives. Materials and methods. Experimental data on the antifungal activity of 1,2,4-triazole derivatives were used for scientific research. The obtained data were processed using QSAR modeling methods using molecular descriptors automatically generated from structural formulas. Results. New QSAR models for predicting antifungal activity based on six physico-chemical parameters of chemicals are presented. A comparative analysis of QSAR models was carried out. A model has been identified that has the best statistical parameters: MAE=0.088; MAPE=8.63; forecast accuracy=91.37%; MSE=0.013; RMSE=0.1145. Among the six factors, the most significant ones were identified. Conclusion. As a result of the conducted studies, QSAR models for predicting the antifungal activity of 1,2,4-triazole derivatives were identified and analyzed. From one to six molecular descriptors were taken as features in the models. The factors that make the greatest contribution to the prediction of antifungal activity were evaluated. The best models are selected based on the calculated statistical parameters.

Keywords

• antifungal activity
• quantitative structure – activity ratios
• 1,2,4-triazole derivatives
• multidimensional linear and nonlinear regression
• molecular descriptors