Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening
Abstract IFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-20259-8 |
| _version_ | 1798001412184997888 |
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| author | Vikas Tiwari Shruthi Viswanath |
| author_facet | Vikas Tiwari Shruthi Viswanath |
| author_sort | Vikas Tiwari |
| collection | DOAJ |
| description | Abstract IFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is mediated by multiple post-translational modifications (PTM). In this study, we have modelled the structure of IFITM3, consistent with experimental predictions on its membrane topology. MD simulation in membrane-aqueous environment revealed the stability of the model. Ligand binding sites on the IFITM3 surface were predicted and it was observed that the best site includes important residues involved in PTM and has good druggable score. Molecular docking was performed using FDA approved ligands and natural ligands from Super Natural II database. The ligands were re-ranked by calculating binding free energy. Select docking complexes were simulated again to substantiate the binding between ligand and IFITM3. We observed that known drugs like Eluxadoline and natural products like SN00224572 and Parishin A have good binding affinity against IFITM3. These ligands form persistent interactions with key lysine residues (Lys83, Lys104) and hence can potentially alter the activity of IFITM3. The results of this computational study can provide a starting point for experimental investigations on IFITM3 modulators. |
| first_indexed | 2024-04-11T11:35:54Z |
| format | Article |
| id | doaj.art-87745169507e48a1af750d3d55fe52c8 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T11:35:54Z |
| publishDate | 2022-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-87745169507e48a1af750d3d55fe52c82022-12-22T04:25:58ZengNature PortfolioScientific Reports2045-23222022-09-0112111110.1038/s41598-022-20259-8Identification of potential modulators of IFITM3 by in-silico modeling and virtual screeningVikas Tiwari0Shruthi Viswanath1National Centre for Biological Sciences, Tata Institute of Fundamental ResearchNational Centre for Biological Sciences, Tata Institute of Fundamental ResearchAbstract IFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is mediated by multiple post-translational modifications (PTM). In this study, we have modelled the structure of IFITM3, consistent with experimental predictions on its membrane topology. MD simulation in membrane-aqueous environment revealed the stability of the model. Ligand binding sites on the IFITM3 surface were predicted and it was observed that the best site includes important residues involved in PTM and has good druggable score. Molecular docking was performed using FDA approved ligands and natural ligands from Super Natural II database. The ligands were re-ranked by calculating binding free energy. Select docking complexes were simulated again to substantiate the binding between ligand and IFITM3. We observed that known drugs like Eluxadoline and natural products like SN00224572 and Parishin A have good binding affinity against IFITM3. These ligands form persistent interactions with key lysine residues (Lys83, Lys104) and hence can potentially alter the activity of IFITM3. The results of this computational study can provide a starting point for experimental investigations on IFITM3 modulators.https://doi.org/10.1038/s41598-022-20259-8 |
| spellingShingle | Vikas Tiwari Shruthi Viswanath Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening Scientific Reports |
| title | Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening |
| title_full | Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening |
| title_fullStr | Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening |
| title_full_unstemmed | Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening |
| title_short | Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening |
| title_sort | identification of potential modulators of ifitm3 by in silico modeling and virtual screening |
| url | https://doi.org/10.1038/s41598-022-20259-8 |
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