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Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency

Gamma-aminobutyric acid (GABA) transaminase—also called GABA aminotransferase (GABA-AT)—deficiency is a rare autosomal recessive disorder characterized by a severe neonatal-infantile epileptic encephalopathy with symptoms such as seizures, hypotonia, hyperreflexia, developmental delay, and growth ac...

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Autores principales: Yasir, Muhammad, Park, Jinyoung, Han, Eun-Taek, Park, Won Sun, Han, Jin-Hee, Kwon, Yong-Soo, Lee, Hee-Jae, Chun, Wanjoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342115/
https://www.ncbi.nlm.nih.gov/pubmed/37446113
http://dx.doi.org/10.3390/ijms241310933
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author Yasir, Muhammad
Park, Jinyoung
Han, Eun-Taek
Park, Won Sun
Han, Jin-Hee
Kwon, Yong-Soo
Lee, Hee-Jae
Chun, Wanjoo
author_facet Yasir, Muhammad
Park, Jinyoung
Han, Eun-Taek
Park, Won Sun
Han, Jin-Hee
Kwon, Yong-Soo
Lee, Hee-Jae
Chun, Wanjoo
author_sort Yasir, Muhammad
collection PubMed
description Gamma-aminobutyric acid (GABA) transaminase—also called GABA aminotransferase (GABA-AT)—deficiency is a rare autosomal recessive disorder characterized by a severe neonatal-infantile epileptic encephalopathy with symptoms such as seizures, hypotonia, hyperreflexia, developmental delay, and growth acceleration. GABA transaminase deficiency is caused by mutations in GABA-AT, the enzyme responsible for the catabolism of GABA. Mutations in multiple locations on GABA-AT have been reported and their locations have been shown to influence the onset of the disease and the severity of symptoms. We examined how GABA-AT mutations influence the structural stability of the enzyme and GABA-binding affinity using computational methodologies such as molecular dynamics simulation and binding free energy calculation to understand the underlying mechanism through which GABA-AT mutations cause GABA-AT deficiency. GABA-AT 3D model depiction was carried out together with seven individual mutated models of GABA-AT. The structural stability of all the predicted models was analyzed using several tools and web servers. All models were evaluated based on their phytochemical values. Additionally, 100 ns MD simulation was carried out and the mutated models were evaluated using RMSD, RMSF, R(g), and SASA. gmxMMPBSA free energy calculation was carried out. Moreover, RMSD and free energy calculations were also compared with those obtained using online web servers. Our study demonstrates that P152S, Q296H, and R92Q play a more critical role in the structural instability of GABA-AT compared with the other mutated models: G465R, L211F, L478P, and R220K.
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spelling pubmed-103421152023-07-14 Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency Yasir, Muhammad Park, Jinyoung Han, Eun-Taek Park, Won Sun Han, Jin-Hee Kwon, Yong-Soo Lee, Hee-Jae Chun, Wanjoo Int J Mol Sci Article Gamma-aminobutyric acid (GABA) transaminase—also called GABA aminotransferase (GABA-AT)—deficiency is a rare autosomal recessive disorder characterized by a severe neonatal-infantile epileptic encephalopathy with symptoms such as seizures, hypotonia, hyperreflexia, developmental delay, and growth acceleration. GABA transaminase deficiency is caused by mutations in GABA-AT, the enzyme responsible for the catabolism of GABA. Mutations in multiple locations on GABA-AT have been reported and their locations have been shown to influence the onset of the disease and the severity of symptoms. We examined how GABA-AT mutations influence the structural stability of the enzyme and GABA-binding affinity using computational methodologies such as molecular dynamics simulation and binding free energy calculation to understand the underlying mechanism through which GABA-AT mutations cause GABA-AT deficiency. GABA-AT 3D model depiction was carried out together with seven individual mutated models of GABA-AT. The structural stability of all the predicted models was analyzed using several tools and web servers. All models were evaluated based on their phytochemical values. Additionally, 100 ns MD simulation was carried out and the mutated models were evaluated using RMSD, RMSF, R(g), and SASA. gmxMMPBSA free energy calculation was carried out. Moreover, RMSD and free energy calculations were also compared with those obtained using online web servers. Our study demonstrates that P152S, Q296H, and R92Q play a more critical role in the structural instability of GABA-AT compared with the other mutated models: G465R, L211F, L478P, and R220K. MDPI 2023-06-30 /pmc/articles/PMC10342115/ /pubmed/37446113 http://dx.doi.org/10.3390/ijms241310933 Text en © 2023 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
Yasir, Muhammad
Park, Jinyoung
Han, Eun-Taek
Park, Won Sun
Han, Jin-Hee
Kwon, Yong-Soo
Lee, Hee-Jae
Chun, Wanjoo
Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title_full Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title_fullStr Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title_full_unstemmed Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title_short Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
title_sort computational exploration of the effects of mutations on gaba aminotransferase in gaba aminotransferase deficiency
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342115/
https://www.ncbi.nlm.nih.gov/pubmed/37446113
http://dx.doi.org/10.3390/ijms241310933
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