TY - JOUR
T1 - A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research
AU - Zahoránszky-Kőhalmi, Gergely
AU - Siramshetty, Vishal B
AU - Kumar, Praveen
AU - Gurumurthy, Manideep
AU - Grillo, Busola
AU - Mathew, Biju
AU - Metaxatos, Dimitrios
AU - Backus, Mark
AU - Mierzwa, Tim
AU - Simon, Reid
AU - Grishagin, Ivan
AU - Brovold, Laura
AU - Mathé, Ewy A
AU - Hall, Matthew D
AU - Michael, Samuel G
AU - Godfrey, Alexander G
AU - Mestres, Jordi
AU - Jensen, Lars J.
AU - Oprea, Tudor I.
PY - 2022
Y1 - 2022
N2 - Motivation: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, hostpathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy.Results: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.Availability: https://neo4covid19.ncats.io.
AB - Motivation: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, hostpathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy.Results: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.Availability: https://neo4covid19.ncats.io.
U2 - 10.1021/acs.jcim.1c00431
DO - 10.1021/acs.jcim.1c00431
M3 - Journal article
C2 - 33173863
VL - 62
SP - 718
EP - 729
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
SN - 1549-9596
IS - 3
ER -