Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection
Carlos Loucera, Marina Esteban‐Medina, Kinza Rian, Matías Marín Falco, Joaquı́n Dopazo, María Peña-Chilet
Abstract
Drug repurposing is a convenient alternative when the need for \nnew drugs in an unexpected medical scenario is urgent, as is the \ncase of emerging pathogens. In recent years, approaches based \non network biology have demonstrated to be superior to genecentric ones.1 Here, we use an innovative methodology that \ncombines mechanistic modeling of the signal transduction circuits \nrelated to SARS-CoV-2 infection (the COVID-19 disease map) with a \nmachine-learning algorithm that learns potential causal interactions between proteins, already targets of drugs, and specific \nsignaling circuits in the COVID-19 disease map, to suggest \npotentially repurposable drugs.