Nature Identification of Chinese Herbal Medicine Compounds Based on Molecular Descriptors

Background: The nature of Chinese herbal medicines (CHMs) is a bridge between traditional Chinese medicine and clinical application. Accurate nature identification of CHMs is essential for guiding the clinical application of CHMs. Objective: To develop a new method for nature identification of CHMs according to compounds in CHMs. Methods: The nature of a CHM is a comprehensive manifestation of the properties of various compounds in the CHM. In this study, 2012 CHM compounds were extracted to construct a compound data set. Molecular descriptors were utilized to build an identification model for classification of the cold-hot-neutral nature of CHM compounds. Results: The predictive accuracy and confusion matrix were validated using the assembled data set. The best model produced accuracies of 96.50.5% and 86.51.5% on training set and test set, respectively. Furthermore, the identification model is robust in predicting the cold-hot-neutral nature of CHM compounds. Conclusion: This work shows how a classification model for medical nature identification can be developed. The derived model can be utilized for the application of CHMs. Highlights: To construct a nature identification model for analysis of the cold-hot-neutral nature of CHMs according to the compounds in CHMs.

Automated summary

This study developed a classification model using compound data set and molecular descriptors to predict the cold-hot-neutral nature of CHM compounds, demonstrating high predictive accuracy of the model.