A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases.
Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantag...
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ftdoajarticles:oai:doaj.org/article:b7e3ad0dbea24044bf7ee79627b62ac0 2023-05-15T15:16:50+02:00 A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. Ariel José Berenstein María Paula Magariños Ariel Chernomoretz Fernán Agüero 2016-01-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0004300 https://doaj.org/article/b7e3ad0dbea24044bf7ee79627b62ac0 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC4703370?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004300 https://doaj.org/article/b7e3ad0dbea24044bf7ee79627b62ac0 PLoS Neglected Tropical Diseases, Vol 10, Iss 1, p e0004300 (2016) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2016 ftdoajarticles https://doi.org/10.1371/journal.pntd.0004300 2022-12-31T00:25:28Z Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 10 1 e0004300 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Ariel José Berenstein María Paula Magariños Ariel Chernomoretz Fernán Agüero A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the ... |
format |
Article in Journal/Newspaper |
author |
Ariel José Berenstein María Paula Magariños Ariel Chernomoretz Fernán Agüero |
author_facet |
Ariel José Berenstein María Paula Magariños Ariel Chernomoretz Fernán Agüero |
author_sort |
Ariel José Berenstein |
title |
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
title_short |
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
title_full |
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
title_fullStr |
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
title_full_unstemmed |
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. |
title_sort |
multilayer network approach for guiding drug repositioning in neglected diseases. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2016 |
url |
https://doi.org/10.1371/journal.pntd.0004300 https://doaj.org/article/b7e3ad0dbea24044bf7ee79627b62ac0 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 10, Iss 1, p e0004300 (2016) |
op_relation |
http://europepmc.org/articles/PMC4703370?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004300 https://doaj.org/article/b7e3ad0dbea24044bf7ee79627b62ac0 |
op_doi |
https://doi.org/10.1371/journal.pntd.0004300 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
10 |
container_issue |
1 |
container_start_page |
e0004300 |
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1766347125973581824 |