Drug repositioning based on similarity constrained probabilistic matrix factorization: COVID-19 as a case study.

ABSTRACT: The novel coronavirus disease 2019 (COVID-19) pandemic has caused a massive health crisis worldwide and upended the global economy. However, vaccines and traditional drug discovery for COVID-19 cost too much in terms of time, manpower, and money. Drug repurposing becomes one of the promising treatment strategies amid the COVID-19 crisis. At present, there are no publicly existing databases for experimentally supported human drug-virus interactions, and most existing drug repurposing methods require the rich information, which is not always available, especially for a new virus. In this study, on the one hand, we put size-able efforts to collect drug-virus interaction entries from literature and build the Human Drug Virus Database (HDVD). On the other hand, we propose a new approach, called

SUBMITTER: Meng Y 

PROVIDER: S-EPMC7825831 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature