Abstract
Arginine methyltransferases (PRMTs) are key regulators of chromatin structure, RNA processing, and signal transduction, and their dysregulation has been linked to cancer and other diseases. The development of potent and selective chemical probes for individual PRMTs remains a major challenge. Here we report a discovery campaign using mRNA display under a reprogrammed genetic code that yielded new macrocyclic peptide inhibitors and substrate probes for coactivator-associated arginine methyltransferase 1 (CARM1/PRMT4) and related family members. To fully exploit the sequencing data from these selections, we were necessitated to develop and implement a workflow that analyses complete datasets without arbitrary abundance cut-offs, based on rapid sequence clustering for redundancy reduction and followed by alignment to retain representative diversity for evolutionary analysis. Whereas conventional abundance-based analysis identified a dominant but weakly active sequence family, our comprehensive approach uncovered potent PRMT4-selective inhibitors, broader PRMT-active peptides, and efficient substrate sequences. This unexpected recovery of efficient substrates prompted structural investigation by NMR and molecular dynamics, which revealed distinct binding modes, including interactions outside the canonical substrate-binding cleft and conformational rearrangements upon binding. Overall, these results provide a new set of chemical biology tools for studying arginine methyltransferases and illustrate how full-dataset analysis can expand the diversity of hits from genetically encoded library discovery. With the growing prominence of mRNA display in both academic and industrial settings, this work highlights its value for identifying bioactive macrocycles with diverse functional profiles.
| Original language | English |
|---|---|
| Number of pages | 11 |
| Journal | Chemical Science |
| DOIs | |
| Publication status | E-pub ahead of print - 25 Feb 2026 |
Bibliographical note
Publisher Copyright:This journal is © The Royal Society of Chemistry, 2026
Funding
R. Y. and S. A. K. J. acknowledge funding from the Dutch Research Council (NWO) grant number OCENW.KLEIN.248, and R. Y. acknowledges further support from the Takenaka Scholarship Foundation. U. M. B. acknowledges funding from the German Research Foundation (DFG) grant numbers BA2292/1, BA2292/4, BA2292/5, and the Deutsche José Carreras Leukämie-Stiftung e.V. grant number DJCLS 05 R/2020. Y. Z. was supported by the China Scholarship Council (CSC file number 201706210082). N. T. C., V. C., N. M. and J. C. are supported by grants from CNRS, Université de Strasbourg, INSERM, Instruct-ERIC, part of the European Strategy Forum on Research Infrastructures (ESFRI) supported by national member subscriptions as well as the French Infrastructure for Integrated Structural Biology (FRISBI) ANR-10-INSB-005, grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d’Avenir labelled ANR-19-CE11-0010-01 to J. C. and the IGBMC.
| Funders | Funder number |
|---|---|
| Takenaka Scholarship Foundation | |
| Institut national de la santé et de la recherche médicale | |
| Université de Strasbourg | |
| IGBMC | |
| Centre National de la Recherche Scientifique | |
| José Carreras Leukämie-Stiftung | DJCLS 05 R/2020 |
| China Scholarship Council | 201706210082 |
| Agence Nationale de la Recherche | ANR-19-CE11-0010-01 |
| French Infrastructure for Integrated Structural Biology | ANR-10-INSB-005, ANR-10-LABX-0030-INRT |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | OCENW.KLEIN.248 |
| Deutsche Forschungsgemeinschaft | BA2292/1, BA2292/4, BA2292/5 |
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