Safety assessment of drug combinations used in COVID-19 treatment: in silico toxicogenomic data-mining approach

Toxicol Appl Pharmacol. 2020 Nov 1;406:115237. doi: 10.1016/j.taap.2020.115237. Epub 2020 Sep 11.


Improvement of COVID-19 clinical condition was seen in studies where combination of antiretroviral drugs, lopinavir and ritonavir, as well as immunomodulant antimalaric, chloroquine/hydroxychloroquine together with the macrolide-type antibiotic, azithromycin, was used for patient's treatment. Although these drugs are "old", their pharmacological and toxicological profile in SARS-CoV-2 - infected patients are still unknown. Thus, by using in silico toxicogenomic data-mining approach, we aimed to assess both risks and benefits of the COVID-19 treatment with the most promising candidate drugs combinations: lopinavir/ritonavir and chloroquine/hydroxychloroquine + azithromycin. The Comparative Toxicogenomics Database (CTD;, Cytoscape software ( and ToppGene Suite portal ( served as a foundation in our research. Our results have demonstrated that lopinavir/ritonavir increased the expression of the genes involved in immune response and lipid metabolism (IL6, ICAM1, CCL2, TNF, APOA1, etc.). Chloroquine/hydroxychloroquine + azithromycin interacted with 6 genes (CCL2, CTSB, CXCL8, IL1B, IL6 and TNF), whereas chloroquine and azithromycin affected two additional genes (BCL2L1 and CYP3A4), which might be a reason behind a greater number of consequential diseases. In contrast to lopinavir/ritonavir, chloroquine/hydroxychloroquine + azithromycin downregulated the expression of TNF and IL6. As expected, inflammation, cardiotoxicity, and dyslipidaemias were revealed as the main risks of lopinavir/ritonavir treatment, while chloroquine/hydroxychloroquine + azithromycin therapy was additionally linked to gastrointestinal and skin diseases. According to our results, these drug combinations should be administrated with caution to patients suffering from cardiovascular problems, autoimmune diseases, or acquired and hereditary lipid disorders.

Keywords: Anti-COVID-19 Therapy; Azithromycin; Chloroquine; Lopinavir; Ritonavir; in silico Approach.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antiviral Agents / administration & dosage
  • Antiviral Agents / adverse effects
  • Azithromycin / administration & dosage
  • Azithromycin / adverse effects
  • Betacoronavirus*
  • COVID-19
  • COVID-19 Drug Treatment
  • Chloroquine / administration & dosage
  • Chloroquine / adverse effects
  • Computer Simulation*
  • Coronavirus Infections / drug therapy
  • Coronavirus Infections / genetics
  • Data Mining / methods*
  • Databases, Genetic
  • Drug Therapy, Combination
  • Gene Regulatory Networks / drug effects
  • Gene Regulatory Networks / genetics
  • Humans
  • Hydroxychloroquine / administration & dosage
  • Hydroxychloroquine / adverse effects
  • Lopinavir / administration & dosage
  • Lopinavir / adverse effects
  • Pandemics
  • Pneumonia, Viral / drug therapy
  • Pneumonia, Viral / genetics
  • Ritonavir / administration & dosage
  • Ritonavir / adverse effects
  • SARS-CoV-2
  • Toxicogenetics / methods*


  • Antiviral Agents
  • Lopinavir
  • Hydroxychloroquine
  • Azithromycin
  • Chloroquine
  • Ritonavir