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Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening

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...

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Autores principales: Tiwari, Vikas, Viswanath, Shruthi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509314/
https://www.ncbi.nlm.nih.gov/pubmed/36153346
http://dx.doi.org/10.1038/s41598-022-20259-8
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author Tiwari, Vikas
Viswanath, Shruthi
author_facet Tiwari, Vikas
Viswanath, Shruthi
author_sort Tiwari, Vikas
collection PubMed
description 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.
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spelling pubmed-95093142022-09-26 Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening Tiwari, Vikas Viswanath, Shruthi Sci Rep Article 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. Nature Publishing Group UK 2022-09-24 /pmc/articles/PMC9509314/ /pubmed/36153346 http://dx.doi.org/10.1038/s41598-022-20259-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tiwari, Vikas
Viswanath, Shruthi
Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening
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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509314/
https://www.ncbi.nlm.nih.gov/pubmed/36153346
http://dx.doi.org/10.1038/s41598-022-20259-8
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