In-silico identification and prioritization of therapeutic targets of asthma
Abstract Asthma is a “common chronic disorder that affects the lungs causing variable and recurring symptoms like repeated episodes of wheezing, breathlessness, chest tightness and underlying inflammation. The interaction of these features of asthma determines the clinical manifestations and severit...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-42803-w |
| _version_ | 1827634216101216256 |
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| author | Ishita Mallick Pradnya Panchal Smita Kadam Priyanka Mohite Jürgen Scheele Werner Seiz Amit Agarwal Om Prakash Sharma |
| author_facet | Ishita Mallick Pradnya Panchal Smita Kadam Priyanka Mohite Jürgen Scheele Werner Seiz Amit Agarwal Om Prakash Sharma |
| author_sort | Ishita Mallick |
| collection | DOAJ |
| description | Abstract Asthma is a “common chronic disorder that affects the lungs causing variable and recurring symptoms like repeated episodes of wheezing, breathlessness, chest tightness and underlying inflammation. The interaction of these features of asthma determines the clinical manifestations and severity of asthma and the response to treatment" [cited from: National Heart, Lung, and Blood Institute. Expert Panel 3 Report. Guidelines for the Diagnosis and Management of Asthma 2007 (EPR-3). Available at: https://www.ncbi.nlm.nih.gov/books/NBK7232/ (accessed on January 3, 2023)]. As per the WHO, 262 million people were affected by asthma in 2019 that leads to 455,000 deaths ( https://www.who.int/news-room/fact-sheets/detail/asthma ). In this current study, our aim was to evaluate thousands of scientific documents and asthma associated omics datasets to identify the most crucial therapeutic target for experimental validation. We leveraged the proprietary tool Ontosight® Discover to annotate asthma associated genes and proteins. Additionally, we also collected and evaluated asthma related patient datasets through bioinformatics and machine learning based approaches to identify most suitable targets. Identified targets were further evaluated based on the various biological parameters to scrutinize their candidature for the ideal therapeutic target. We identified 7237 molecular targets from published scientific documents, 2932 targets from genomic structured databases and 7690 dysregulated genes from the transcriptomics and 560 targets from genomics mutational analysis. In total, 18,419 targets from all the desperate sources were analyzed and evaluated though our approach to identify most promising targets in asthma. Our study revealed IL-13 as one of the most important targets for asthma with approved drugs on the market currently. TNF, VEGFA and IL-18 were the other top targets identified to be explored for therapeutic benefit in asthma but need further clinical testing. HMOX1, ITGAM, DDX58, SFTPD and ADAM17 were the top novel targets identified for asthma which needs to be validated experimentally. |
| first_indexed | 2024-03-09T15:10:17Z |
| format | Article |
| id | doaj.art-dccd9894b0bb4eee84ddd9f7217f8a27 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:10:17Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-dccd9894b0bb4eee84ddd9f7217f8a272023-11-26T13:25:35ZengNature PortfolioScientific Reports2045-23222023-09-0113111910.1038/s41598-023-42803-wIn-silico identification and prioritization of therapeutic targets of asthmaIshita Mallick0Pradnya Panchal1Smita Kadam2Priyanka Mohite3Jürgen Scheele4Werner Seiz5Amit Agarwal6Om Prakash Sharma7Innoplexus Consulting Pvt. LtdInnoplexus Consulting Pvt. LtdInnoplexus Consulting Pvt. LtdInnoplexus Consulting Pvt. LtdInnoplexus AGInnoplexus AGInnoplexus Consulting Pvt. LtdInnoplexus AGAbstract Asthma is a “common chronic disorder that affects the lungs causing variable and recurring symptoms like repeated episodes of wheezing, breathlessness, chest tightness and underlying inflammation. The interaction of these features of asthma determines the clinical manifestations and severity of asthma and the response to treatment" [cited from: National Heart, Lung, and Blood Institute. Expert Panel 3 Report. Guidelines for the Diagnosis and Management of Asthma 2007 (EPR-3). Available at: https://www.ncbi.nlm.nih.gov/books/NBK7232/ (accessed on January 3, 2023)]. As per the WHO, 262 million people were affected by asthma in 2019 that leads to 455,000 deaths ( https://www.who.int/news-room/fact-sheets/detail/asthma ). In this current study, our aim was to evaluate thousands of scientific documents and asthma associated omics datasets to identify the most crucial therapeutic target for experimental validation. We leveraged the proprietary tool Ontosight® Discover to annotate asthma associated genes and proteins. Additionally, we also collected and evaluated asthma related patient datasets through bioinformatics and machine learning based approaches to identify most suitable targets. Identified targets were further evaluated based on the various biological parameters to scrutinize their candidature for the ideal therapeutic target. We identified 7237 molecular targets from published scientific documents, 2932 targets from genomic structured databases and 7690 dysregulated genes from the transcriptomics and 560 targets from genomics mutational analysis. In total, 18,419 targets from all the desperate sources were analyzed and evaluated though our approach to identify most promising targets in asthma. Our study revealed IL-13 as one of the most important targets for asthma with approved drugs on the market currently. TNF, VEGFA and IL-18 were the other top targets identified to be explored for therapeutic benefit in asthma but need further clinical testing. HMOX1, ITGAM, DDX58, SFTPD and ADAM17 were the top novel targets identified for asthma which needs to be validated experimentally.https://doi.org/10.1038/s41598-023-42803-w |
| spellingShingle | Ishita Mallick Pradnya Panchal Smita Kadam Priyanka Mohite Jürgen Scheele Werner Seiz Amit Agarwal Om Prakash Sharma In-silico identification and prioritization of therapeutic targets of asthma Scientific Reports |
| title | In-silico identification and prioritization of therapeutic targets of asthma |
| title_full | In-silico identification and prioritization of therapeutic targets of asthma |
| title_fullStr | In-silico identification and prioritization of therapeutic targets of asthma |
| title_full_unstemmed | In-silico identification and prioritization of therapeutic targets of asthma |
| title_short | In-silico identification and prioritization of therapeutic targets of asthma |
| title_sort | in silico identification and prioritization of therapeutic targets of asthma |
| url | https://doi.org/10.1038/s41598-023-42803-w |
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