TY - JOUR
T1 - Identification of Key Contributive Compounds in a Herbal Medicine
T2 - A Novel Mathematic—Biological Evaluation Approach
AU - Zhang, Cheng
AU - Wang, Ning
AU - Xu, Yu
AU - Tan, Hor Yue
AU - Feng, Yibin
N1 - Funding Information:
The authors would like to express thanks to Mr Keith Wong, Ms Cindy Lee, Mr Alex Shek and the Faculty Core Facility for their technical support. This research study was supported by Research Grant Council, HKSAR (Project Code RGC GRF 17152116), Commissioner for Innovation Technology, HKSAR (Project Code ITS/091/16FX) and Health and Medical Research Fund (Project Codes 15162961 and 16172751). Wong's donation (project code: 200006276), and a donation from the Gaia Family Trust of New Zealand (project code: 200007008).
Publisher Copyright:
© 2021 The Authors. Advanced Theory and Simulations published by Wiley-VCH GmbH
PY - 2021/6
Y1 - 2021/6
N2 - A pattern or syndrome in response to a multicomponent system is the actual target of herbal medicine treatment. However, it is a substantial challenge to fill the gap between a contributive compound profile in herbal medicine (especially a formula) and its biological features. This study aims to establish a feasible component-mining strategy, which provides a strong prediction of key compounds in support of experimental and clinical observations. Given interdisciplinary scope of life science and mathematical statistics, the relationship between chemical profile and bioactivities is measured by a model termed mathematical prediction bioactivity, in which gray relational analysis, multiple linear/non-linear regression analysis (including t-distributed stochastic neighbor embedding), and radial basis function analysis are involved. R language programming-dependent analysis is adopted with add-on packages, including UniDOE, Factoextra, FactoMineR, Factanal, Rtsne, and Nnet. By using this assessment method in a biological experiment, it is identified that 6-shogaol extracted from Ginger-Coptis formula (a herbal formula) is beneficial for diabetic retinopathy (DR) treatment. The study provides both a novel compound 6-shogalol for DR treatment and a new strategy for mining key contributors in a multicomponent system.
AB - A pattern or syndrome in response to a multicomponent system is the actual target of herbal medicine treatment. However, it is a substantial challenge to fill the gap between a contributive compound profile in herbal medicine (especially a formula) and its biological features. This study aims to establish a feasible component-mining strategy, which provides a strong prediction of key compounds in support of experimental and clinical observations. Given interdisciplinary scope of life science and mathematical statistics, the relationship between chemical profile and bioactivities is measured by a model termed mathematical prediction bioactivity, in which gray relational analysis, multiple linear/non-linear regression analysis (including t-distributed stochastic neighbor embedding), and radial basis function analysis are involved. R language programming-dependent analysis is adopted with add-on packages, including UniDOE, Factoextra, FactoMineR, Factanal, Rtsne, and Nnet. By using this assessment method in a biological experiment, it is identified that 6-shogaol extracted from Ginger-Coptis formula (a herbal formula) is beneficial for diabetic retinopathy (DR) treatment. The study provides both a novel compound 6-shogalol for DR treatment and a new strategy for mining key contributors in a multicomponent system.
KW - diabetic retinopathy
KW - medical sciences
KW - pattern recognition
KW - target identification
UR - http://www.scopus.com/inward/record.url?scp=85105090149&partnerID=8YFLogxK
U2 - 10.1002/adts.202000279
DO - 10.1002/adts.202000279
M3 - Journal article
AN - SCOPUS:85105090149
SN - 2513-0390
VL - 4
JO - Advanced Theory and Simulations
JF - Advanced Theory and Simulations
IS - 6
M1 - 2000279
ER -
