Toward Understanding the Cold, Hot, and Neutral Nature of Chinese Medicines Using in Silico Mode-of-Action Analysis

Abstract

One important, however, poorly understood, concept of Traditional Chinese Medicine (TCM) is that of hot, cold, and neutral nature of its bioactive principles. To advance the field, in this study, we analyzed compound-nature pairs from TCM on a large scale (>23 000 structures) via chemical space visualizations to understand its physicochemical domain and in silico target prediction to understand differences related to their modes-of-action (MoA) against proteins. We found that overall TCM natures spread into different subclusters with specific molecular patterns, as opposed to forming coherent global groups. Compounds associated with cold nature had a lower clogP and contain more aliphatic rings than the other groups and were found to control detoxification, heat-clearing, heart development processes, and have sedative function, associated with "Mental and behavioural disorders" diseases. While compounds associated with hot nature were on average of lower molecular weight, have more aromatic ring systems than other groups, frequently seemed to control body temperature, have cardio-protection function, improve fertility and sexual function, and represent excitatory or activating effects, associated with "endocrine, nutritional and metabolic diseases" and "diseases of the circulatory system". Compounds associated with neutral nature had a higher polar surface area and contain more cyclohexene moieties than other groups and seem to be related to memory function, suggesting that their nature may be a useful guide for their utility in neural degenerative diseases. We were hence able to elucidate the difference between different nature classes in TCM on the molecular level, and on a large data set, for the first time, thereby helping a better understanding of TCM nature theory and bridging the gap between traditional medicine and our current understanding of the human body.

Exploring the ‘cold/hot’ properties of traditional Chinese medicine by cell temperature measurement

“…However, the alleged 'cold/hot' properties of TCM is a highly metaphysical theory and it is difficult to identify a scientific way to prove and characterize it. Besides, there have been many related studies on the 'cold/hot' properties of TCM, but the inconsistency of research methods has resulted in a significant difference in the results (Liu et al 2008;Wang et al 2016;Fu et al 2017;Jia et al 2017;Huang et al 2018). To date, it remains unlikely to obtain the common internal law of the "cold/hot" herbs.…”

The Yin-Yang Property of Chinese Medicinal Herbs Relates to Chemical Composition but Not Anti-Oxidative Activity: An Illustration Using Spleen-Meridian Herbs

“…According to previous research, the herbal compounds associated with cold nature generally possess more polar structures; in contrast the compounds associated with hot nature have lower molecular weight; and the neutral compounds have a higher polar surface area ( Fu et al, 2017a ). The cold and hot properties of TCM are defined according to the impacts to human physiological condition, indicating the importance of chemical composition of herbal extracts.…”

“…Thus, the exact relationship between these two identification systems of TCM, i.e., “Yin-Yang” versus chemical composition, remains as a puzzle ( Zhou et al, 2009 ; Ma et al, 2010 ; Li, 2012 ). In order to maintain a homeostasis in our body, the herbs with cold nature, also known as Yin-stimulating herbs, were generally used to treat hot diseases like inflammation, while the herbs with nature of warm and hot, belonging to Yang-stimulating herbs, were good for various types of deficiency ( Fu et al, 2017a ). In recent years, the works on chemical properties of TCMs has made a significant progress, and new ideas have been proposed, e.g., molecular drug hypothesis ( Fu et al, 2017b ), biodynamics ( Yang et al, 2017 ), genetic hypothesis ( Rezapour-Firouzi, 2017 ), transient receptor potential channel hypothesis ( Bishnoi et al, 2018 ).…”

Predicting the Associations between Meridians and Chinese Traditional Medicine Using a Cost-Sensitive Graph Convolutional Neural Network

“…As an example, given a molecule compound discovered from a herb, we can use chemical similarity searching to find compounds with similar structure and to infer the potential similar bioactivity [17]. Fu et al discovered the hot/cold herb groups associated with the target functional pathways of the chemical compounds [18]. Wang et al established a hot/cold property classifier based on the different types of the molecular descriptors of the ingredient compounds of TCM [19].…”