On Quantitative Structure-Activity Relationship Of Traditional Chinese Medicine

Traditional Chinese Medicine (TCM), whose development history is in accordance with human history of civilization, embodies intelligence of the Chinese people and has made great contribution to human health. In the long course of its development, TCM has developed its own theoretical system and accumulated plenty of experiences, which has greatly promoted the development of modern medicine. Recently, more and more countries have realized its value, and numerous innovative drugs have been developed with vigorous efforts. Based on abundant natural resources of TCM, the exploitation of innovative drugs and screening of active components will become an important field in the development of medicine in 21th century. Quantitative structure activity relationship (QSAR) is an important field for basic research and application of modern chemistry. Although it has become the hotspot of research on organic chemistry, pharmacological chemistry, environment chemistry, chemometrics, molecular biology and immunology, it's inadequate in the research on active components screening of TCM. In this paper, Molecular electro-negativity distance vectors (MEDV) is adopted to express the structure of active components of TCM. Such methods as MLR, STR, PCA, PLS and ANN were used to find the relationship between structure parameters and activity of active components in certain TCM. Models were established with good performance in predicting unknown active components. The research can be divided into the following sections: 1. First of all, MEDV was employed to characterize molecular structure of active components in TCM against SARS and STR to select the important parameters. STR was used to set up correlative models of structure parameters and various activities. The predictive capability using these models for the testing samples were over 80%. While the predictive capability of PLS were over 80% for defervesce, anti-inflammation, promoting blood circulation and prophylactic effect. 2. TCM with toxicity to KB cell was selected to study with QSAR. Models were established by STR and PLS, constructing the relationship between structural parameters and -log(ED₅₀). The correlative coefficients (R²) of the optimized model were 0.674 and 0.618; the correlative coefficients of cross validation (Q²) were 0.519 and 0.547; RMS of testing samples were 1.488 and 1.434. The result showed that the model owned good predictive capability. 3. ANN and PCA-ANN was adopted to distinguish drug effect of anti-SARS active components in TCM. Predictive capabilities for the testing samples were over 80% and 85% of ANN and PCA-ANN for defervesce, anti-inflammation, promoting blood circulation and prophylactic effect. 4. ANN and PCA-ANN were adopted to investigate active components with toxicity to KB cell. RMS of the two methods were 1.530 and 1.516 respectively. The results indicated that PCA-ANN is a better method for prediction than ANN. 5. ANN and PCA-ANN were adopted to distinguish active components with toxicity for KB cell. The predictive capabilities were 64.00% and 73.00% respectively. To some extent, the results illustrated both methods can contribute to the screening of active components. 6. ANN and PCA-ANN were adopted to distinguish the active components which can cause acute toxicity. The results show that PCA-ANN gets a better result than ANN. Establishing models through QSAR method can help to screen active components in TCM and are a new way for TCM research. QSAR research for TCM will have a bright further.