Discovery of new drug indications for COVID-19: A drug repurposing approach

PLoS One. 2022 May 24;17(5):e0267095. doi: 10.1371/journal.pone.0267095. eCollection 2022.

Abstract

Motivation: The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem ID: CID0000005743), baricitinib(Pubchem ID: CID44205240), remdesivir (PubchemID: CID121304016) are three generic drugs that have demonstrated in-vitro high antiviral activity against SARS-CoV-2. The present study aims to widen the search and explore the anti-SARS-CoV-2 properties of these potential drugs while looking for new drug indications with optimised benefits via in-silico research.

Method: Here, we designed a unique drug-similarity model to repurpose existing drugs against SARS-CoV-2, using the anti-Covid properties of dexamethasone, baricitinib, and remdesivir as references. Known chemical-chemical interactions of reference drugs help extract interactive compounds withimprovedanti-SARS-CoV-2 properties. Here, we calculated the likelihood of these drug compounds treating SARS-CoV-2 related symptoms using chemical-protein interactions between the interactive compounds of the reference drugs and SARS-CoV-2 target genes. In particular, we adopted a two-tier clustering approach to generate a drug similarity model for the final selection of potential anti-SARS-CoV-2 drug molecules. Tier-1 clustering was based on t-Distributed Stochastic Neighbor Embedding (t-SNE) and aimed to filter and discard outlier drugs. The tier-2 analysis incorporated two cluster analyses performed in parallel using Ordering Points To Identify the Clustering Structure (OPTICS) and Hierarchical Agglomerative Clustering (HAC). As a result, itidentified clusters of drugs with similar actions. In addition, we carried out a docking study for in-silico validation of top candidate drugs.

Result: Our drug similarity model highlighted ten drugs, including reference drugs that can act as potential therapeutics against SARS-CoV-2. The docking results suggested that doxorubicin showed the least binding energy compared to reference drugs. Their practical utility as anti-SARS-CoV-2 drugs, either individually or in combination, warrants further investigation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antiviral Agents / chemistry
  • Antiviral Agents / pharmacology
  • Antiviral Agents / therapeutic use
  • COVID-19 Drug Treatment*
  • Dexamethasone / pharmacology
  • Dexamethasone / therapeutic use
  • Drug Repositioning*
  • Humans
  • Molecular Docking Simulation
  • SARS-CoV-2

Substances

  • Antiviral Agents
  • Dexamethasone

Grants and funding

This work is supported in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement no. 860895 (TranSYS - h2020transys.eu). The funders had no role in study design, data collection and analysis, decision.