Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis
Autotaxin (ATX) is considered as an interesting drug target for the therapy of several diseases. The goal of the research was to detect new ATX inhibitors which have novel scaffolds by using virtual screening. First, based on two diverse receptor-ligand complexes, 14 pharmacophore models were develo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-03-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/25/5/1107 |
| _version_ | 1819266360625070080 |
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| author | Ji-Xia Ren Rui-Tao Zhang Hui Zhang |
| author_facet | Ji-Xia Ren Rui-Tao Zhang Hui Zhang |
| author_sort | Ji-Xia Ren |
| collection | DOAJ |
| description | Autotaxin (ATX) is considered as an interesting drug target for the therapy of several diseases. The goal of the research was to detect new ATX inhibitors which have novel scaffolds by using virtual screening. First, based on two diverse receptor-ligand complexes, 14 pharmacophore models were developed, and the 14 models were verified through a big test database. Those pharmacophore models were utilized to accomplish virtual screening. Next, for the purpose of predicting the probable binding poses of compounds and then carrying out further virtual screening, docking-based virtual screening was performed. Moreover, an excellent 3D QSAR model was established, and 3D QSAR-based virtual screening was applied for predicting the activity values of compounds which got through the above two-round screenings. A correlation coefficient r<sup>2</sup>, which equals 0.988, was supplied by the 3D QSAR model for the training set, and the correlation coefficient r<sup>2</sup> equaling 0.808 for the test set means that the developed 3D QSAR model is an excellent model. After the filtering was done by the combinatory virtual screening, which is based on the pharmacophore modelling, docking study, and 3D QSAR modelling, we chose nine potent inhibitors with novel scaffolds finally. Furthermore, two potent compounds have been particularly discussed. |
| first_indexed | 2024-12-23T21:00:02Z |
| format | Article |
| id | doaj.art-91a4f711e1004355a89212699cc38107 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-12-23T21:00:02Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-91a4f711e1004355a89212699cc381072022-12-21T17:31:24ZengMDPI AGMolecules1420-30492020-03-01255110710.3390/molecules25051107molecules25051107Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR AnalysisJi-Xia Ren0Rui-Tao Zhang1Hui Zhang2College of Life Science, Liaocheng University, Liaocheng 252059, ChinaCollege of Agronomy, Liaocheng University, Liaocheng 252059, ChinaCollege of Life Science, Northwest Normal University, Lanzhou 730070, ChinaAutotaxin (ATX) is considered as an interesting drug target for the therapy of several diseases. The goal of the research was to detect new ATX inhibitors which have novel scaffolds by using virtual screening. First, based on two diverse receptor-ligand complexes, 14 pharmacophore models were developed, and the 14 models were verified through a big test database. Those pharmacophore models were utilized to accomplish virtual screening. Next, for the purpose of predicting the probable binding poses of compounds and then carrying out further virtual screening, docking-based virtual screening was performed. Moreover, an excellent 3D QSAR model was established, and 3D QSAR-based virtual screening was applied for predicting the activity values of compounds which got through the above two-round screenings. A correlation coefficient r<sup>2</sup>, which equals 0.988, was supplied by the 3D QSAR model for the training set, and the correlation coefficient r<sup>2</sup> equaling 0.808 for the test set means that the developed 3D QSAR model is an excellent model. After the filtering was done by the combinatory virtual screening, which is based on the pharmacophore modelling, docking study, and 3D QSAR modelling, we chose nine potent inhibitors with novel scaffolds finally. Furthermore, two potent compounds have been particularly discussed.https://www.mdpi.com/1420-3049/25/5/1107autotaxin inhibitor3d qsar modelpharmacophore modelvirtual screeningdocking calculation |
| spellingShingle | Ji-Xia Ren Rui-Tao Zhang Hui Zhang Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis Molecules autotaxin inhibitor 3d qsar model pharmacophore model virtual screening docking calculation |
| title | Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis |
| title_full | Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis |
| title_fullStr | Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis |
| title_full_unstemmed | Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis |
| title_short | Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis |
| title_sort | identifying novel atx inhibitors via combinatory virtual screening using crystallography derived pharmacophore modelling docking study and qsar analysis |
| topic | autotaxin inhibitor 3d qsar model pharmacophore model virtual screening docking calculation |
| url | https://www.mdpi.com/1420-3049/25/5/1107 |
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