Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches
In this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantit...
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MDPI AG
2016-04-01
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| Series: | International Journal of Molecular Sciences |
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| author | Meimei Chen Xuemei Yang Xinmei Lai Jie Kang Huijuan Gan Yuxing Gao |
| author_facet | Meimei Chen Xuemei Yang Xinmei Lai Jie Kang Huijuan Gan Yuxing Gao |
| author_sort | Meimei Chen |
| collection | DOAJ |
| description | In this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantitative structure activity relationship (2D- and 3D-QSAR) studies were performed based on such AAD by a stepwise technology combined with multiple linear regression and comparative molecular field analysis. The obtained 2D-QSAR model gave a high predictive ability (R2train = 0.935, R2test = 0.902, Q2LOO = 0.899). It also uncovered that number of rotatable single bonds (b_rotN), relative negative partial charges (RPC−), oprea's lead-like (opr_leadlike), subdivided van der Waal’s surface area (SlogP_VSA2) and accessible surface area (ASA) were important features in defining activity. Additionally, the derived3D-QSAR model presented a higher predictive ability (R2train = 0.944, R2test = 0.892, Q2LOO = 0.802). Meanwhile, the derived contour maps from the 3D-QSAR model revealed the significant structural features (steric and electronic effects) required for improving FXR agonist activity. Finally, nine newly designed AAD with higher predicted EC50 values than the known template compound were docked into the FXR active site. The excellent molecular binding patterns of these molecules also suggested that they can be robust and potent partial FXR agonists in agreement with the QSAR results. Overall, these derived models may help to identify and design novel AAD with better FXR agonist activity. |
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| issn | 1422-0067 |
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| last_indexed | 2024-04-12T12:10:01Z |
| publishDate | 2016-04-01 |
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| series | International Journal of Molecular Sciences |
| spelling | doaj.art-514888d5f20843d8a8e6835aa22593c72022-12-22T03:33:35ZengMDPI AGInternational Journal of Molecular Sciences1422-00672016-04-0117453610.3390/ijms17040536ijms17040536Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico ApproachesMeimei Chen0Xuemei Yang1Xinmei Lai2Jie Kang3Huijuan Gan4Yuxing Gao5College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, ChinaCollege of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, ChinaCollege of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, ChinaCollege of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, ChinaCollege of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, ChinaCollege of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, ChinaIn this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantitative structure activity relationship (2D- and 3D-QSAR) studies were performed based on such AAD by a stepwise technology combined with multiple linear regression and comparative molecular field analysis. The obtained 2D-QSAR model gave a high predictive ability (R2train = 0.935, R2test = 0.902, Q2LOO = 0.899). It also uncovered that number of rotatable single bonds (b_rotN), relative negative partial charges (RPC−), oprea's lead-like (opr_leadlike), subdivided van der Waal’s surface area (SlogP_VSA2) and accessible surface area (ASA) were important features in defining activity. Additionally, the derived3D-QSAR model presented a higher predictive ability (R2train = 0.944, R2test = 0.892, Q2LOO = 0.802). Meanwhile, the derived contour maps from the 3D-QSAR model revealed the significant structural features (steric and electronic effects) required for improving FXR agonist activity. Finally, nine newly designed AAD with higher predicted EC50 values than the known template compound were docked into the FXR active site. The excellent molecular binding patterns of these molecules also suggested that they can be robust and potent partial FXR agonists in agreement with the QSAR results. Overall, these derived models may help to identify and design novel AAD with better FXR agonist activity.http://www.mdpi.com/1422-0067/17/4/536QSARdockingFXRanthranilic acid derivatives |
| spellingShingle | Meimei Chen Xuemei Yang Xinmei Lai Jie Kang Huijuan Gan Yuxing Gao Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches International Journal of Molecular Sciences QSAR docking FXR anthranilic acid derivatives |
| title | Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches |
| title_full | Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches |
| title_fullStr | Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches |
| title_full_unstemmed | Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches |
| title_short | Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches |
| title_sort | structural investigation for optimization of anthranilic acid derivatives as partial fxr agonists by in silico approaches |
| topic | QSAR docking FXR anthranilic acid derivatives |
| url | http://www.mdpi.com/1422-0067/17/4/536 |
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