Authors: | Worachartcheewan, Apilak Prachayasittikul, Veda Prachayasittikul, Supaluk Tantivit, Visanu Yeeyahya, Chareef Prachayasittikul, Virapong |
Title: | Rational design of novel coumarins |
Other Titles: | a potential trend for antioxidants in cosmetics |
Language (ISO): | en |
Abstract: | Coumarins are well-known for their antioxidant effect and aromatic property, thus, they are one of ingredients commonly added in cosmetics and personal care products. Quantitative structure-activity relationships (QSAR) modeling is an in silico method widely used to facilitate rational design and structural optimization of novel drugs. Herein, QSAR modeling was used to elucidate key properties governing antioxidant activity of a series of the reported coumarin-based antioxidant agents (1-28). Several types of descriptors (calculated from 4 softwares i.e., Gaussian 09, Dragon, PaDEL and Mold2 softwares) were used to generate three multiple linear regression (MLR) models with preferable predictive performance (Q2LOO-CV = 0.813-0.908; RMSELOO-CV = 0.150-0.210; Q2Ext = 0.875-0.952; RMSEExt = 0.104-0.166). QSAR analysis indicated that number of secondary amines (nArNHR), polarizability (G2p), electronegativity (D467, D580, SpMin2_Bhe, and MATS8e), van der Waals volume (D491 and D461), and H-bond potential (SHBint4) are important properties governing antioxidant activity. The constructed models were also applied to guide in silico rational design of an additional set of 69 structurally modified coumarins with improved antioxidant activity. Finally, a set of 9 promising newly design compounds were highlighted for further development. Structure-activity analysis also revealed key features required for potent activity which would be useful for guiding the future rational design. In overview, our findings demonstrated that QSAR modeling could possibly be a facilitating tool to enhance successful development of bioactive compounds for health and cosmetic applications. |
Subject Headings: | coumarin antioxidant activity rational design QSAR MLR |
URI: | http://hdl.handle.net/2003/39773 http://dx.doi.org/10.17877/de290r-21665 |
Issue Date: | 2020-02-26 |
Rights link: | http://creativecommons.org/licenses/by/4.0/ |
Provenance: | IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund |
Appears in Collections: | Original Articles 2020 |
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