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Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor

Epidermal growth factor receptor (EGFR) resistance to tyrosine kinase inhibitors can cause low survival rates in mutation-positive non-small cell lung cancer patients. It is necessary to predict new mutations in the development of more potent EGFR inhibitors since classical and rare mutations observ...

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Autores principales: Amelia, Tasia, Setiawan, Aderian Novito, Kartasasmita, Rahmana Emran, Ohwada, Tomohiko, Tjahjono, Daryono Hadi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784575/
https://www.ncbi.nlm.nih.gov/pubmed/36555475
http://dx.doi.org/10.3390/ijms232415828
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author Amelia, Tasia
Setiawan, Aderian Novito
Kartasasmita, Rahmana Emran
Ohwada, Tomohiko
Tjahjono, Daryono Hadi
author_facet Amelia, Tasia
Setiawan, Aderian Novito
Kartasasmita, Rahmana Emran
Ohwada, Tomohiko
Tjahjono, Daryono Hadi
author_sort Amelia, Tasia
collection PubMed
description Epidermal growth factor receptor (EGFR) resistance to tyrosine kinase inhibitors can cause low survival rates in mutation-positive non-small cell lung cancer patients. It is necessary to predict new mutations in the development of more potent EGFR inhibitors since classical and rare mutations observed were known to affect the effectiveness of the therapy. Therefore, this research aimed to perform alanine mutagenesis scanning on ATP binding site residues without COSMIC data, followed by molecular dynamic simulations to determine their molecular interactions with ATP and erlotinib compared to wild-type complexes. Based on the result, eight mutations were found to cause changes in the binding energy of the ATP analogue to become more negative. These included G779A, Q791A, L792A, R841A, N842A, V843A, I853A, and D855A, which were predicted to enhance the affinity of ATP and reduce the binding ability of inhibitors with the same interaction site. Erlotinib showed more positive energy among G779A, Q791A, I853A, and D855A, due to their weaker binding energy than ATP. These four mutations could be anticipated in the development of the next inhibitor to overcome the incidence of resistance in lung cancer patients.
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spelling pubmed-97845752022-12-24 Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor Amelia, Tasia Setiawan, Aderian Novito Kartasasmita, Rahmana Emran Ohwada, Tomohiko Tjahjono, Daryono Hadi Int J Mol Sci Article Epidermal growth factor receptor (EGFR) resistance to tyrosine kinase inhibitors can cause low survival rates in mutation-positive non-small cell lung cancer patients. It is necessary to predict new mutations in the development of more potent EGFR inhibitors since classical and rare mutations observed were known to affect the effectiveness of the therapy. Therefore, this research aimed to perform alanine mutagenesis scanning on ATP binding site residues without COSMIC data, followed by molecular dynamic simulations to determine their molecular interactions with ATP and erlotinib compared to wild-type complexes. Based on the result, eight mutations were found to cause changes in the binding energy of the ATP analogue to become more negative. These included G779A, Q791A, L792A, R841A, N842A, V843A, I853A, and D855A, which were predicted to enhance the affinity of ATP and reduce the binding ability of inhibitors with the same interaction site. Erlotinib showed more positive energy among G779A, Q791A, I853A, and D855A, due to their weaker binding energy than ATP. These four mutations could be anticipated in the development of the next inhibitor to overcome the incidence of resistance in lung cancer patients. MDPI 2022-12-13 /pmc/articles/PMC9784575/ /pubmed/36555475 http://dx.doi.org/10.3390/ijms232415828 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Amelia, Tasia
Setiawan, Aderian Novito
Kartasasmita, Rahmana Emran
Ohwada, Tomohiko
Tjahjono, Daryono Hadi
Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title_full Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title_fullStr Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title_full_unstemmed Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title_short Computational Prediction of Resistance Induced Alanine-Mutation in ATP Site of Epidermal Growth Factor Receptor
title_sort computational prediction of resistance induced alanine-mutation in atp site of epidermal growth factor receptor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784575/
https://www.ncbi.nlm.nih.gov/pubmed/36555475
http://dx.doi.org/10.3390/ijms232415828
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