Targeting RNA:protein interactions with an integrative approach leads to the identification of potent YBX1 inhibitors
Abstract
RNA-protein interactions (RPIs) are promising targets for developing new molecules of therapeutic interest. Nevertheless, challenges arise from the lack of methods and feedback between computational and experimental techniques during the drug discovery process. Here, we tackle these challenges by developing a drug screening approach that integrates chemical, structural and cellular data from both advanced computational techniques and a method to score RPIs in cells for the development of small RPI inhibitors; and we demonstrate its robustness by targeting Y-box binding protein 1 (YB-1), a messenger RNA-binding protein involved in cancer progression and resistance to chemotherapy. This approach led to the identification of 22 hits validated by molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy of which 11 were found to significantly interfere with the binding of messenger RNA (mRNA) to YB-1 in cells. One of our leads is an FDA-approved poly(ADP-ribose) polymerase 1 (PARP-1) inhibitor. This work shows the potential of our integrative approach and paves the way for the rational development of RPI inhibitors.
Data availability
All data are available within the Article, Supplementary Files and Appendices, or available from the corresponding authors on reasonable request. Source data for figures 2, 4d, 7b, Figure 3-Figure supplement 3, Figure 8a, Figure 8-Figure supplement 1b-c, Figure 8-Figure supplement 4b-c, Appendix 5 Table 1 and Appendix 5 Figure 1 are also provided with the paper.
Article and author information
Author details
Funding
HORIZON EUROPE Marie Sklodowska-Curie Actions (895024)
- Krystel El Hage
Genopole (SATURNE 2020)
- David Pastré
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, El Hage et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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