DCcov: Repositioning of Drugs and Drug Combinations for SARS-CoV-2 Infected Lung through Constraint-Based Modelling

TL;DR

This study uses constraint-based metabolic modeling and flux balance analysis on infected lung cells to identify existing drugs and combinations that could be repurposed for COVID-19 treatment by targeting virus-specific metabolic pathways.

Contribution

It introduces a COVID-19-specific metabolic model and identifies potential drug candidates and combinations through in-silico screening based on essential genes and pathways.

Findings

Identified 45 promising drug candidates for COVID-19.

Discovered key pathways related to COVID-19 severity, including oxidative stress and ferroptosis.

Predicted drug combinations with potential therapeutic effects.

Abstract

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no effective antiviral drug except treatments for symptomatic therapy. Flux balance analysis is an efficient method to analyze metabolic networks. It allows optimizing for a metabolic function and thus e.g., predicting the growth rate of a specific cell or the production rate of a metabolite of interest. Here flux balance analysis was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the replication of the SARS-CoV-2 virus within the host tissue. Making use of expression data sets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then host-specific essential genes and gene-pairs were determined through in-silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, as well as ferroptosis, sphingolipid metabolism, cysteine metabolism, and fat digestion. By in-silico screening of FDA approved drugs on the putative disease-specific essential genes and gene-pairs, 45 drugs and 99 drug combinations were predicted as promising candidates for COVID-19 focused drug repositioning (https://github.com/sysbiolux/DCcov). Among the 45 drug candidates, six antiviral drugs were found and seven drugs that are being tested in clinical trials against COVID-19. Other drugs like gemcitabine, rosuvastatin and acetylcysteine, and drug combinations like azathioprine-pemetrexed might offer new chances for treating COVID-19.