Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
[Preprint]. 2023 Jul 4:arXiv:2305.15453v2.

Drugst.One - A plug-and-play solution for online systems medicine and network-based drug repurposing

Affiliations

Drugst.One - A plug-and-play solution for online systems medicine and network-based drug repurposing

Andreas Maier et al. ArXiv. .

Update in

  • Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.
    Maier A, Hartung M, Abovsky M, Adamowicz K, Bader GD, Baier S, Blumenthal DB, Chen J, Elkjaer ML, Garcia-Hernandez C, Helmy M, Hoffmann M, Jurisica I, Kotlyar M, Lazareva O, Levi H, List M, Lobentanzer S, Loscalzo J, Malod-Dognin N, Manz Q, Matschinske J, Mee M, Oubounyt M, Pastrello C, Pico AR, Pillich RT, Poschenrieder JM, Pratt D, Pržulj N, Sadegh S, Saez-Rodriguez J, Sarkar S, Shaked G, Shamir R, Trummer N, Turhan U, Wang RS, Zolotareva O, Baumbach J. Maier A, et al. Nucleic Acids Res. 2024 Jul 5;52(W1):W481-W488. doi: 10.1093/nar/gkae388. Nucleic Acids Res. 2024. PMID: 38783119 Free PMC article.

Abstract

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Keywords: Biomedical data analysis; Biomedical network exploration; Data visualization; Drug repurposing; Interactive network enrichment; Network integration; Systems medicine.

PubMed Disclaimer

Conflict of interest statement

JSR reports funding from GSK, Pfizer and Sanofi and fees from Travere Therapeutics and Astex Pharmaceuticals.

Figures

Figure 1:
Figure 1:
Drugst.One enables web developers to add a fully functional network explorer to any website with minimal coding effort (biomedical web tool before (A) and after (B) Drugst.One integration). (C): A network can be explored manually or by using network medicine algorithms to identify disease mechanisms and drug repurposing candidates. Associated diseases and tissue-specific expression are additional information layers to gain insight into the network context.
Figure 2:
Figure 2:
The Drugst.One ecosystem: The Drugst.One server (A) updates weekly from online databases (B), executes computationally demanding tasks, and provides data to the Drugst.One plugin (D i and D ii). The frontend is loaded from the content delivery system (CDS), (C), receives the network data from the developer integrating Drugst.One (E), and presents it to the user. Drugst.One can also be accessed programmatically through a Python package (F).
Figure 3:
Figure 3:
Participants of WikiPathway WP1991 displayed in Drugst.One. Adjacent diseases and drugs are enabled, as well as diseases linked to drugs targeting this smooth muscle cell proliferation and differentiation pathway. Normalized median expression values for ‘Artery - Aorta’ are overlaid as pie charts, where 360° represent the maximum observed transcripts per million (TPM) in the selected tissue and all other TPMs are exponentially scaled.

References

    1. Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A, et al. Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Brief Bioinform. 2021;22: 642–663. - PMC - PubMed
    1. Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, O’Meara MJ, et al. A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing. bioRxiv. 2020. doi:10.1101/2020.03.22.002386 - DOI
    1. Zolotareva O, Kleine M. A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases. J Integr Bioinform. 2019;16. doi:10.1515/jib-2018-0069 - DOI - PMC - PubMed
    1. Hütter CVR, Sin C, Müller F, Menche J. Network cartographs for interpretable visualizations. Nature Computational Science. 2022;2: 84–89. - PMC - PubMed
    1. Hartung M, Anastasi E, Mamdouh ZM, Nogales C, Schmidt HHHW, Baumbach J, et al. Cancer driver drug interaction explorer. Nucleic Acids Res. 2022;50: W138–44. - PMC - PubMed

Publication types

LinkOut - more resources