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High Throughput and Computational Repurposing for Neglected Diseases
PURPOSE: Neglected tropical diseases (NTDs) represent are a heterogeneous group of communicable diseases that are found within the poorest populations of the world. There are 23 NTDs that have been prioritized by the World Health Organization, which are endemic in 149 countries and affect more than...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792295/ https://www.ncbi.nlm.nih.gov/pubmed/30560386 http://dx.doi.org/10.1007/s11095-018-2558-3 |
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author | Hernandez, Helen W. Soeung, Melinda Zorn, Kimberley M. Ashoura, Norah Mottin, Melina Andrade, Carolina Horta Caffrey, Conor R. de Siqueira-Neto, Jair Lage Ekins, Sean |
author_facet | Hernandez, Helen W. Soeung, Melinda Zorn, Kimberley M. Ashoura, Norah Mottin, Melina Andrade, Carolina Horta Caffrey, Conor R. de Siqueira-Neto, Jair Lage Ekins, Sean |
author_sort | Hernandez, Helen W. |
collection | PubMed |
description | PURPOSE: Neglected tropical diseases (NTDs) represent are a heterogeneous group of communicable diseases that are found within the poorest populations of the world. There are 23 NTDs that have been prioritized by the World Health Organization, which are endemic in 149 countries and affect more than 1.4 billion people, costing these developing economies billions of dollars annually. The NTDs result from four different causative pathogens: protozoa, bacteria, helminth and virus. The majority of the diseases lack effective treatments. Therefore, new therapeutics for NTDs are desperately needed. METHODS: We describe various high throughput screening and computational approaches that have been performed in recent years. We have collated the molecules identified in these studies and calculated molecular properties. RESULTS: Numerous global repurposing efforts have yielded some promising compounds for various neglected tropical diseases. These compounds when analyzed as one would expect appear drug-like. Several large datasets are also now in the public domain and this enables machine learning models to be constructed that then facilitate the discovery of new molecules for these pathogens. CONCLUSIONS: In the space of a few years many groups have either performed experimental or computational repurposing high throughput screens against neglected diseases. These have identified compounds which in many cases are already approved drugs. Such approaches perhaps offer a more efficient way to develop treatments which are generally not a focus for global pharmaceutical companies because of the economics or the lack of a viable market. Other diseases could perhaps benefit from these repurposing approaches. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11095-018-2558-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6792295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-67922952019-12-17 High Throughput and Computational Repurposing for Neglected Diseases Hernandez, Helen W. Soeung, Melinda Zorn, Kimberley M. Ashoura, Norah Mottin, Melina Andrade, Carolina Horta Caffrey, Conor R. de Siqueira-Neto, Jair Lage Ekins, Sean Pharm Res Expert Review PURPOSE: Neglected tropical diseases (NTDs) represent are a heterogeneous group of communicable diseases that are found within the poorest populations of the world. There are 23 NTDs that have been prioritized by the World Health Organization, which are endemic in 149 countries and affect more than 1.4 billion people, costing these developing economies billions of dollars annually. The NTDs result from four different causative pathogens: protozoa, bacteria, helminth and virus. The majority of the diseases lack effective treatments. Therefore, new therapeutics for NTDs are desperately needed. METHODS: We describe various high throughput screening and computational approaches that have been performed in recent years. We have collated the molecules identified in these studies and calculated molecular properties. RESULTS: Numerous global repurposing efforts have yielded some promising compounds for various neglected tropical diseases. These compounds when analyzed as one would expect appear drug-like. Several large datasets are also now in the public domain and this enables machine learning models to be constructed that then facilitate the discovery of new molecules for these pathogens. CONCLUSIONS: In the space of a few years many groups have either performed experimental or computational repurposing high throughput screens against neglected diseases. These have identified compounds which in many cases are already approved drugs. Such approaches perhaps offer a more efficient way to develop treatments which are generally not a focus for global pharmaceutical companies because of the economics or the lack of a viable market. Other diseases could perhaps benefit from these repurposing approaches. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11095-018-2558-3) contains supplementary material, which is available to authorized users. Springer US 2018-12-17 2019 /pmc/articles/PMC6792295/ /pubmed/30560386 http://dx.doi.org/10.1007/s11095-018-2558-3 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2018 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Expert Review Hernandez, Helen W. Soeung, Melinda Zorn, Kimberley M. Ashoura, Norah Mottin, Melina Andrade, Carolina Horta Caffrey, Conor R. de Siqueira-Neto, Jair Lage Ekins, Sean High Throughput and Computational Repurposing for Neglected Diseases |
title | High Throughput and Computational Repurposing for Neglected Diseases |
title_full | High Throughput and Computational Repurposing for Neglected Diseases |
title_fullStr | High Throughput and Computational Repurposing for Neglected Diseases |
title_full_unstemmed | High Throughput and Computational Repurposing for Neglected Diseases |
title_short | High Throughput and Computational Repurposing for Neglected Diseases |
title_sort | high throughput and computational repurposing for neglected diseases |
topic | Expert Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792295/ https://www.ncbi.nlm.nih.gov/pubmed/30560386 http://dx.doi.org/10.1007/s11095-018-2558-3 |
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