In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors
Interleukin-2 (IL-2) is involved in the activation and differentiation of T-helper cells. Uncontrolled activated T cells play a key role in the pathophysiology by stimulating inflammation and autoimmune diseases like arthritis, psoriasis and Crohn’s disease. T cells activation can be suppressed eith...
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| Format: | Article |
| Language: | English |
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Sciendo
2021-03-01
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| Series: | Acta Pharmaceutica |
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| Online Access: | https://doi.org/10.2478/acph-2021-0002 |
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| author | Halim Sobia Ahsan Zaheer-Ul-Haq Khan Ajmal Al-Rawahi Ahmed Al-Harrasi Ahmed |
| author_facet | Halim Sobia Ahsan Zaheer-Ul-Haq Khan Ajmal Al-Rawahi Ahmed Al-Harrasi Ahmed |
| author_sort | Halim Sobia Ahsan |
| collection | DOAJ |
| description | Interleukin-2 (IL-2) is involved in the activation and differentiation of T-helper cells. Uncontrolled activated T cells play a key role in the pathophysiology by stimulating inflammation and autoimmune diseases like arthritis, psoriasis and Crohn’s disease. T cells activation can be suppressed either by preventing IL-2 production or blocking the IL-2 interaction with its receptor. Hence, IL-2 is now emerging as a target for novel therapeutic approaches in several autoimmune disorders. This study was carried out to set up an effective virtual screening (VS) pipeline for IL-2. Four docking/scoring approaches (FRED, MOE, GOLD and Surflex-Dock) were compared in the re-docking process to test their performance in producing correct binding modes of IL-2 inhibitors. Surflex-Dock and FRED were the best in predicting the native pose in its top-ranking position. Shapegauss and CGO scoring functions identified the known inhibitors of IL-2 in top 1, 5 and 10 % of library and differentiated binders from non-binders efficiently with average AUC of > 0.9 and > 0.7, resp. The applied docking protocol served as a basis for the VS of a large database that will lead to the identification of more active compounds against IL-2. |
| format | Article |
| id | doaj-art-8a820464495a4081b33104be5b579455 |
| institution | Kabale University |
| issn | 1846-9558 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Acta Pharmaceutica |
| spelling | doaj-art-8a820464495a4081b33104be5b5794552025-02-02T09:44:23ZengSciendoActa Pharmaceutica1846-95582021-03-01711335610.2478/acph-2021-0002acph-2021-0002In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitorsHalim Sobia Ahsan0Zaheer-Ul-Haq1Khan Ajmal2Al-Rawahi Ahmed3Al-Harrasi Ahmed4Natural and Medical Science Research Center, University of Nizwa Birkat-ul-Mouz616, Nizwa Sultanate of OmanDr. Panjwani Center for Molecular Medicine and Drug Research International Center for Chemical and Biological Sciences, University of Karachi, 75270Karachi, PakistanNatural and Medical Science Research Center, University of Nizwa Birkat-ul-Mouz616, Nizwa Sultanate of OmanNatural and Medical Science Research Center, University of Nizwa Birkat-ul-Mouz616, Nizwa Sultanate of OmanNatural and Medical Science Research Center, University of Nizwa Birkat-ul-Mouz616, Nizwa Sultanate of OmanInterleukin-2 (IL-2) is involved in the activation and differentiation of T-helper cells. Uncontrolled activated T cells play a key role in the pathophysiology by stimulating inflammation and autoimmune diseases like arthritis, psoriasis and Crohn’s disease. T cells activation can be suppressed either by preventing IL-2 production or blocking the IL-2 interaction with its receptor. Hence, IL-2 is now emerging as a target for novel therapeutic approaches in several autoimmune disorders. This study was carried out to set up an effective virtual screening (VS) pipeline for IL-2. Four docking/scoring approaches (FRED, MOE, GOLD and Surflex-Dock) were compared in the re-docking process to test their performance in producing correct binding modes of IL-2 inhibitors. Surflex-Dock and FRED were the best in predicting the native pose in its top-ranking position. Shapegauss and CGO scoring functions identified the known inhibitors of IL-2 in top 1, 5 and 10 % of library and differentiated binders from non-binders efficiently with average AUC of > 0.9 and > 0.7, resp. The applied docking protocol served as a basis for the VS of a large database that will lead to the identification of more active compounds against IL-2.https://doi.org/10.2478/acph-2021-0002il-2virtual screeningfredmoegoldsurflex-dockroc-curves |
| spellingShingle | Halim Sobia Ahsan Zaheer-Ul-Haq Khan Ajmal Al-Rawahi Ahmed Al-Harrasi Ahmed In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors Acta Pharmaceutica il-2 virtual screening fred moe gold surflex-dock roc-curves |
| title | In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors |
| title_full | In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors |
| title_fullStr | In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors |
| title_full_unstemmed | In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors |
| title_short | In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors |
| title_sort | in silico data mining of large scale databases for the virtual screening of human interleukin 2 inhibitors |
| topic | il-2 virtual screening fred moe gold surflex-dock roc-curves |
| url | https://doi.org/10.2478/acph-2021-0002 |
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