# qsar ## Getting started [chembl](https://www.ebi.ac.uk/chembl/) DOI https://doi.org/10.1016/j.ejmech.2022.114495 Design, synthesis and activity against drug-resistant bacteria evaluation of C-20, C-23 modified 5-O-mycaminosyltylonolide derivatives A类似物:22个活性数据 B类似物:7个活性数据 C类似物:47个活性数据 检索条件:Structure2D_A1.mol 85% 以上相似度 检索结果:A_85.csv ## env [unimol install](https://unimol.readthedocs.io/en/latest/installation.html#install) ```shell python -m pip install --upgrade pip pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple pip install unimol_tools pip install huggingface_hub ``` ## result ```shell (analyse) (base) root@DESK4090:/mnt/c/project/qsar/MIC# python qsar_1D.py [1D-QSAR][Linear Regression] MSE:32.3949 R2:0.6525 Model saved to 1d_qsar_linear_regression_model.pkl [1D-QSAR][Stochastic Gradient Descent] MSE:230009980374197965960989638656.0000 R2:-2467672699617844819673481216.0000 Model saved to 1d_qsar_stochastic_gradient_descent_model.pkl [1D-QSAR][K-Nearest Neighbors] MSE:30.2081 R2:0.6759 Model saved to 1d_qsar_k-nearest_neighbors_model.pkl [1D-QSAR][Decision Tree] MSE:27.7150 R2:0.7027 Model saved to 1d_qsar_decision_tree_model.pkl [1D-QSAR][Random Forest] MSE:26.5204 R2:0.7155 Model saved to 1d_qsar_random_forest_model.pkl [1D-QSAR][XGBoost] MSE:27.7147 R2:0.7027 Model saved to 1d_qsar_xgboost_model.pkl [1D-QSAR][Multi-layer Perceptron] MSE:143.3505 R2:-0.5379 Model saved to 1d_qsar_multi-layer_perceptron_model.pkl --- [2D-QSAR][Linear Regression] MSE:30.1093 R2:0.6770 Model saved to 2d_qsar_linear_regression_model.pkl [2D-QSAR][Stochastic Gradient Descent] MSE:33.7336 R2:0.6381 Model saved to 2d_qsar_stochastic_gradient_descent_model.pkl [2D-QSAR][K-Nearest Neighbors] MSE:48.8179 R2:0.4763 Model saved to 2d_qsar_k-nearest_neighbors_model.pkl [2D-QSAR][Decision Tree] MSE:30.2360 R2:0.6756 Model saved to 2d_qsar_decision_tree_model.pkl [2D-QSAR][Random Forest] MSE:28.7916 R2:0.6911 Model saved to 2d_qsar_random_forest_model.pkl [2D-QSAR][XGBoost] MSE:30.2351 R2:0.6756 Model saved to 2d_qsar_xgboost_model.pkl [2D-QSAR][Multi-layer Perceptron] MSE:30.1715 R2:0.6763 Model saved to 2d_qsar_multi-layer_perceptron_model.pkl --- [3D-QSAR][Stochastic Gradient Descent] MSE:64.5768 R2:0.3072 Model saved to 3d_qsar_stochastic_gradient_descent_model.pkl [3D-QSAR][K-Nearest Neighbors] MSE:38.6921 R2:0.5849 Model saved to 3d_qsar_k-nearest_neighbors_model.pkl [3D-QSAR][Decision Tree] MSE:30.2360 R2:0.6756 Model saved to 3d_qsar_decision_tree_model.pkl [3D-QSAR][Random Forest] MSE:30.8310 R2:0.6692 Model saved to 3d_qsar_random_forest_model.pkl [3D-QSAR][XGBoost] MSE:30.2362 R2:0.6756 Model saved to 3d_qsar_xgboost_model.pkl [3D-QSAR][Multi-layer Perceptron] MSE:29.9844 R2:0.6783 Model saved to 3d_qsar_multi-layer_perceptron_model.pkl --- unimol qsar {'mse': 59.72037918598548, 'mae': 5.179289798987539, 'pearsonr': 0.638764928149331, 'spearmanr': 0.6006870492749102, 'r2': 0.35928715315601223} ```