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From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes
Successive oxidative stress and biochemical changes results in neuronal death and neuritic plaques growth in Alzheimer's disease (AD). Therefore, it is interest to analyze amyloid-βeta precursor protein (APP), beta-secretase 1 (BACE1), presenilin (PSEN1 and PSEN2) genes from brain tissues to ga...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6900319/ https://www.ncbi.nlm.nih.gov/pubmed/31831959 http://dx.doi.org/10.6026/97320630015760 |
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author | Aathi, Muthusankar Piramanayagam, Shanmughavel |
author_facet | Aathi, Muthusankar Piramanayagam, Shanmughavel |
author_sort | Aathi, Muthusankar |
collection | PubMed |
description | Successive oxidative stress and biochemical changes results in neuronal death and neuritic plaques growth in Alzheimer's disease (AD). Therefore, it is interest to analyze amyloid-βeta precursor protein (APP), beta-secretase 1 (BACE1), presenilin (PSEN1 and PSEN2) genes from brain tissues to gain insights. Development of potential inhibitors for these targets is of significance. EST sequences of 2898 (APP), 539 (BACE1), 786 (PSEN1) and 314 (PSEN2) genes were analyzed in this study. A contig sequences with APP (contigs 1-4), BACE1 (contigs 5-7), PSEN1 (contigs 8, 9, 10, 11), PSEN2 (contigs 13, 14) except PSEN1 (contigs 10) and PSEN2 (contigs 13) genes were identified. APP (contig 3 without translational error) was further analyzed using molecular modeling and docking to show its binding with curcumin (principal curcuminoid of turmeric) having -7.3 kcal/mol interaction energy for further consideration as a potential inhibitor. |
format | Online Article Text |
id | pubmed-6900319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-69003192019-12-12 From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes Aathi, Muthusankar Piramanayagam, Shanmughavel Bioinformation Research Article Successive oxidative stress and biochemical changes results in neuronal death and neuritic plaques growth in Alzheimer's disease (AD). Therefore, it is interest to analyze amyloid-βeta precursor protein (APP), beta-secretase 1 (BACE1), presenilin (PSEN1 and PSEN2) genes from brain tissues to gain insights. Development of potential inhibitors for these targets is of significance. EST sequences of 2898 (APP), 539 (BACE1), 786 (PSEN1) and 314 (PSEN2) genes were analyzed in this study. A contig sequences with APP (contigs 1-4), BACE1 (contigs 5-7), PSEN1 (contigs 8, 9, 10, 11), PSEN2 (contigs 13, 14) except PSEN1 (contigs 10) and PSEN2 (contigs 13) genes were identified. APP (contig 3 without translational error) was further analyzed using molecular modeling and docking to show its binding with curcumin (principal curcuminoid of turmeric) having -7.3 kcal/mol interaction energy for further consideration as a potential inhibitor. Biomedical Informatics 2019-10-31 /pmc/articles/PMC6900319/ /pubmed/31831959 http://dx.doi.org/10.6026/97320630015760 Text en © 2019 Biomedical Informatics http://creativecommons.org/licenses/by/3.0/ This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Research Article Aathi, Muthusankar Piramanayagam, Shanmughavel From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title | From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title_full | From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title_fullStr | From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title_full_unstemmed | From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title_short | From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes |
title_sort | from est to structure models for functional inference of app, bace1, psen1, psen2 genes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6900319/ https://www.ncbi.nlm.nih.gov/pubmed/31831959 http://dx.doi.org/10.6026/97320630015760 |
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