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Conference Paper: Effects of bone formation by flavonoids: an in silico study

TitleEffects of bone formation by flavonoids: an in silico study
Authors
Issue Date2016
Citation
The 94th General Session and Exhibition of the IADR, 3rd Meeting of the IADR Asia Pacific Region and 35th Annual Meeting of the IADR Korean Dicision, Seoul, Korea, 22-25 June 2016. How to Cite?
AbstractOBJECTIVES: Flavonoids are polyphenol compounds that are categorized according to their chemical structures into distinct groups, i.e. flavonols, flavones, flavanones, flavanols, and isoflavones. Previous laboratory and animal studies have shown some flavonoids, e.g. Naringin, Quercetin, Genistein and Daidzein, could promote bone formation via gene transcription or signalling the protein. However, the exact mechanism acts onto the osteoblast is unknown. In the last decade, inexpensive and time-saving Quantitative structure-activity relationship (QSAR) in silico modeling has been used in fields of biochemistry, molecular biology and biomaterials science to simulate and correlate various biochemical features and the behavioral manifestations. Thus, in the current study, we target to establish a validated and predictive QSAR model by different types of descriptors involved in the flavonoid biochemistry. METHODS: Twenty flavonoids (Kaempferol, Taxifolin, Daidzein, Morin, Scutellarein, Quercetin, Apigenin, Myricetin, Tamarixetin, Rutin, Genistein, 5,7,2'-Trihydroxyflavone, Baicalein, Luteolin, Galangin, Chrysin, Isorhamnetin, Naringin, 3-Methyl galangin, Resokaempferol) were identified with their structural information, e.g. the position of hydroxyl groups and half maximal inhibitory concentration (IC50). Then, these data were fitted into QSAR Software (VLifeMDS 4.3, VLife Technologies, India) with topological quantum-chemical descriptors involving in electronic, physicochemical or electronic properties of the flavonoids. Partial least squares (PLS), multiple linear regression (MLR) and Principal Component Regression (PCR) statistical modules were used to predict and establish the mathematical models. Finally, results from previous animal models were used to validate the mathematical model. RESULTS: A QSAR model has been successfully established, with Kaempferol was screened to be the best flavonoids. Electronic interactions between atomic charges within flavonoids would activate receptor-like structures in the calcium-voltage channels on osteoblasts, which was sought to be the significant mechanism for some flavonoids in assisting the bone formation. CONCLUSIONS: The QSAR model indicated that the activation of calcium-voltage channels on osteoblasts by flavonoids played an important role in bone formation.
DescriptionGroup/Network Programs: Mineralized Tissue: no. 0311
Persistent Identifierhttp://hdl.handle.net/10722/232193

 

DC FieldValueLanguage
dc.contributor.authorTsoi, JKH-
dc.contributor.authorChan, K-
dc.contributor.authorYang, Y-
dc.date.accessioned2016-09-20T05:28:22Z-
dc.date.available2016-09-20T05:28:22Z-
dc.date.issued2016-
dc.identifier.citationThe 94th General Session and Exhibition of the IADR, 3rd Meeting of the IADR Asia Pacific Region and 35th Annual Meeting of the IADR Korean Dicision, Seoul, Korea, 22-25 June 2016.-
dc.identifier.urihttp://hdl.handle.net/10722/232193-
dc.descriptionGroup/Network Programs: Mineralized Tissue: no. 0311-
dc.description.abstractOBJECTIVES: Flavonoids are polyphenol compounds that are categorized according to their chemical structures into distinct groups, i.e. flavonols, flavones, flavanones, flavanols, and isoflavones. Previous laboratory and animal studies have shown some flavonoids, e.g. Naringin, Quercetin, Genistein and Daidzein, could promote bone formation via gene transcription or signalling the protein. However, the exact mechanism acts onto the osteoblast is unknown. In the last decade, inexpensive and time-saving Quantitative structure-activity relationship (QSAR) in silico modeling has been used in fields of biochemistry, molecular biology and biomaterials science to simulate and correlate various biochemical features and the behavioral manifestations. Thus, in the current study, we target to establish a validated and predictive QSAR model by different types of descriptors involved in the flavonoid biochemistry. METHODS: Twenty flavonoids (Kaempferol, Taxifolin, Daidzein, Morin, Scutellarein, Quercetin, Apigenin, Myricetin, Tamarixetin, Rutin, Genistein, 5,7,2'-Trihydroxyflavone, Baicalein, Luteolin, Galangin, Chrysin, Isorhamnetin, Naringin, 3-Methyl galangin, Resokaempferol) were identified with their structural information, e.g. the position of hydroxyl groups and half maximal inhibitory concentration (IC50). Then, these data were fitted into QSAR Software (VLifeMDS 4.3, VLife Technologies, India) with topological quantum-chemical descriptors involving in electronic, physicochemical or electronic properties of the flavonoids. Partial least squares (PLS), multiple linear regression (MLR) and Principal Component Regression (PCR) statistical modules were used to predict and establish the mathematical models. Finally, results from previous animal models were used to validate the mathematical model. RESULTS: A QSAR model has been successfully established, with Kaempferol was screened to be the best flavonoids. Electronic interactions between atomic charges within flavonoids would activate receptor-like structures in the calcium-voltage channels on osteoblasts, which was sought to be the significant mechanism for some flavonoids in assisting the bone formation. CONCLUSIONS: The QSAR model indicated that the activation of calcium-voltage channels on osteoblasts by flavonoids played an important role in bone formation. -
dc.languageeng-
dc.relation.ispartofGeneral Session of the International Association for Dental Research, IADR 2016-
dc.titleEffects of bone formation by flavonoids: an in silico study-
dc.typeConference_Paper-
dc.identifier.emailTsoi, JKH: jkhtsoi@hku.hk-
dc.identifier.emailYang, Y: yangyanq@hku.hk-
dc.identifier.authorityTsoi, JKH=rp01609-
dc.identifier.authorityYang, Y=rp00045-
dc.identifier.hkuros263884-

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