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Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches

Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasiz...

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Autores principales: Ahmed, Fee Faysal, Das, Arnob Dip, Sumi, Mst. Joynab, Islam, Md. Zohurul, Rahman, Md. Shahedur, Rashid, Md. Harun, Alyami, Salem A., Alotaibi, Naif, Azad, A. K. M., Moni, Mohammad Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10625598/
https://www.ncbi.nlm.nih.gov/pubmed/37925496
http://dx.doi.org/10.1038/s41598-023-46455-8
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author Ahmed, Fee Faysal
Das, Arnob Dip
Sumi, Mst. Joynab
Islam, Md. Zohurul
Rahman, Md. Shahedur
Rashid, Md. Harun
Alyami, Salem A.
Alotaibi, Naif
Azad, A. K. M.
Moni, Mohammad Ali
author_facet Ahmed, Fee Faysal
Das, Arnob Dip
Sumi, Mst. Joynab
Islam, Md. Zohurul
Rahman, Md. Shahedur
Rashid, Md. Harun
Alyami, Salem A.
Alotaibi, Naif
Azad, A. K. M.
Moni, Mohammad Ali
author_sort Ahmed, Fee Faysal
collection PubMed
description Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD.
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spelling pubmed-106255982023-11-06 Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches Ahmed, Fee Faysal Das, Arnob Dip Sumi, Mst. Joynab Islam, Md. Zohurul Rahman, Md. Shahedur Rashid, Md. Harun Alyami, Salem A. Alotaibi, Naif Azad, A. K. M. Moni, Mohammad Ali Sci Rep Article Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD. Nature Publishing Group UK 2023-11-04 /pmc/articles/PMC10625598/ /pubmed/37925496 http://dx.doi.org/10.1038/s41598-023-46455-8 Text en © The Author(s) 2023 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
Ahmed, Fee Faysal
Das, Arnob Dip
Sumi, Mst. Joynab
Islam, Md. Zohurul
Rahman, Md. Shahedur
Rashid, Md. Harun
Alyami, Salem A.
Alotaibi, Naif
Azad, A. K. M.
Moni, Mohammad Ali
Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title_full Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title_fullStr Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title_full_unstemmed Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title_short Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
title_sort identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10625598/
https://www.ncbi.nlm.nih.gov/pubmed/37925496
http://dx.doi.org/10.1038/s41598-023-46455-8
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