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A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis

BACKGROUND AND PURPOSE: Recently, the use of immunotoxins for targeted cancer therapy has been proposed, to find new anticancer drugs with high efficacy on tumor cells with minimal side effects on normal cells. we designed and compared several arazyme (AraA)-based fusion proteins with different liga...

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Autores principales: Mehrab, Rezvan, Sedighian, Hamid, Sotoodehnejadnematalahi, Fattah, Halabian, Raheleh, Fooladi, Abbas Ali Imani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9976060/
https://www.ncbi.nlm.nih.gov/pubmed/36873271
http://dx.doi.org/10.4103/1735-5362.367795
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author Mehrab, Rezvan
Sedighian, Hamid
Sotoodehnejadnematalahi, Fattah
Halabian, Raheleh
Fooladi, Abbas Ali Imani
author_facet Mehrab, Rezvan
Sedighian, Hamid
Sotoodehnejadnematalahi, Fattah
Halabian, Raheleh
Fooladi, Abbas Ali Imani
author_sort Mehrab, Rezvan
collection PubMed
description BACKGROUND AND PURPOSE: Recently, the use of immunotoxins for targeted cancer therapy has been proposed, to find new anticancer drugs with high efficacy on tumor cells with minimal side effects on normal cells. we designed and compared several arazyme (AraA)-based fusion proteins with different ligands to choose the best-targeted therapy for interleukin 13 receptor alpha 2 (IL13Rα2)-overexpressed cancer cells. For this purpose, IL13Rα2 was selected as a receptor and IL13 and IL13.E13K were evaluated as native and mutant ligands, respectively. In addition, Pep-1 and A2b11 were chosen as the peptide ligands for targeted cancer therapy. EXPERIMENTAL APPROACH: Several bioinformatics servers were used for designing constructs and optimization. The structures of the chimeric proteins were predicted and verified by I-TASSER, Q-Mean, ProSA, Ramachandran plot, and Verify3D program. Physicochemical properties, toxicity, and antigenicity were predicted by ProtParam, ToxinPred, and VaxiJen. HawkDock, LigPlot(+), and GROMACS software were used for docking and molecular dynamics simulation of the ligand-receptor interaction. FINDINGS/RESULTS: The in silico results showed AraA-A2b11 has higher values of confidence score and Q-mean score was obtained for high-resolution crystal structures. All chimeric proteins were stable, non-toxic, and non-antigenic. AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 retained its natural structure and based on ligand-receptor docking and molecular dynamic analysis, the binding ability of AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 to IL13Rα2 was sufficiently strong. CONCLUSION AND IMPLICATIONS: Based on the bioinformatics result AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 was a stable fusion protein with two separate domains and high affinity with the IL13Rα2 receptor. Therefore, AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 fusion protein could be a new potent candidate for target cancer therapy.
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spelling pubmed-99760602023-03-02 A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis Mehrab, Rezvan Sedighian, Hamid Sotoodehnejadnematalahi, Fattah Halabian, Raheleh Fooladi, Abbas Ali Imani Res Pharm Sci Original Article BACKGROUND AND PURPOSE: Recently, the use of immunotoxins for targeted cancer therapy has been proposed, to find new anticancer drugs with high efficacy on tumor cells with minimal side effects on normal cells. we designed and compared several arazyme (AraA)-based fusion proteins with different ligands to choose the best-targeted therapy for interleukin 13 receptor alpha 2 (IL13Rα2)-overexpressed cancer cells. For this purpose, IL13Rα2 was selected as a receptor and IL13 and IL13.E13K were evaluated as native and mutant ligands, respectively. In addition, Pep-1 and A2b11 were chosen as the peptide ligands for targeted cancer therapy. EXPERIMENTAL APPROACH: Several bioinformatics servers were used for designing constructs and optimization. The structures of the chimeric proteins were predicted and verified by I-TASSER, Q-Mean, ProSA, Ramachandran plot, and Verify3D program. Physicochemical properties, toxicity, and antigenicity were predicted by ProtParam, ToxinPred, and VaxiJen. HawkDock, LigPlot(+), and GROMACS software were used for docking and molecular dynamics simulation of the ligand-receptor interaction. FINDINGS/RESULTS: The in silico results showed AraA-A2b11 has higher values of confidence score and Q-mean score was obtained for high-resolution crystal structures. All chimeric proteins were stable, non-toxic, and non-antigenic. AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 retained its natural structure and based on ligand-receptor docking and molecular dynamic analysis, the binding ability of AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 to IL13Rα2 was sufficiently strong. CONCLUSION AND IMPLICATIONS: Based on the bioinformatics result AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 was a stable fusion protein with two separate domains and high affinity with the IL13Rα2 receptor. Therefore, AraA-(A(EAAAK)(4)ALEA(EAAAK)(4)A)(2)-IL13 fusion protein could be a new potent candidate for target cancer therapy. Wolters Kluwer - Medknow 2023-01-19 /pmc/articles/PMC9976060/ /pubmed/36873271 http://dx.doi.org/10.4103/1735-5362.367795 Text en Copyright: © 2023 Research in Pharmaceutical Sciences https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Mehrab, Rezvan
Sedighian, Hamid
Sotoodehnejadnematalahi, Fattah
Halabian, Raheleh
Fooladi, Abbas Ali Imani
A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title_full A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title_fullStr A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title_full_unstemmed A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title_short A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
title_sort comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9976060/
https://www.ncbi.nlm.nih.gov/pubmed/36873271
http://dx.doi.org/10.4103/1735-5362.367795
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