摘要
Dear Editor,Drug repurposing is a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent,as is the case of emerging pathogens.In recent years,approaches based on network biology have demonstrated to be superior to genecentric ones.1 Here,we use an innovative methodology that combines mechanistic modeling of the signal transduction circuits related to SARS-CoV-2 infection(the COVID-19 disease map)with a machine-learning algorithm that learns potential causal interactions between proteins,already targets of drugs,and specific signaling circuits in the COVID-19 disease map,to suggest potentially repurposable drugs.
基金
supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness,PT17/0009/0006,ACCI2018/29 from CIBER-ISCIII and COV20/00788 from the ISCIII,co-funded with European Regional Development Funds(ERDF)
the grant“Large-scale drug repurposing in rare diseases by genomic Big Data analysis with machine learning methods”from the Fundación BBVA(G999088Q)
as well as H2020 Programme of the European Union grants Marie Curie Innovative Training Network“Machine Learning Frontiers in Precision Medicine”(MLFPM)(GA 813533).
