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

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          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.

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          Author and article information

          Journal
          J Chem Inf Model
          Journal of chemical information and modeling
          American Chemical Society (ACS)
          1549-960X
          1549-9596
          Mar 27 2017
          : 57
          : 3
          Affiliations
          [1 ] School of Information Management, Shandong University of Traditional Chinese Medicine , 250355 Jinan, China.
          [2 ] Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge , Lensfield Road, Cambridge CB2 1EW, United Kingdom.
          [3 ] College of TCM, Shandong University of Traditional Chinese Medicine , 250355 Jinan, China.
          Article
          10.1021/acs.jcim.6b00725
          28257573
          340231f0-25eb-4067-990d-6cfd02a4dc00
          History

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