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Updated: Mar 29, 2026

Quantitative Methods to Study Protein Arginine Methyltransferase 1-9 Activity in Cells
Published on: August 7, 2021
Computational insights into conformational dynamics and allosteric regulation in protein arginine methyltransferase 4
Amr Abbas1, Zhanpeng Miao2, Jia Jin2
1College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China; Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt.
Abstract:
Protein arginine methyltransferases are key epigenetic regulators and promising targets for cancer therapy. PRMT4 plays an important role in transcriptional regulation and tumor progression, yet selective inhibition remains challenging because type I PRMTs share highly conserved catalytic sites. The success of allosteric inhibitors targeting PRMT3 and PRMT6 suggests that selective modulation through regulatory sites outside the catalytic pocket may also be feasible for PRMT4. Motivated by this rationale, we investigated whether PRMT4 undergoes conformational transitions between active and inactive states and whether it contains allosterically targetable pockets capable of regulating its enzymatic activity. Using an integrated computational strategy, we characterized the conformational dynamics and allosteric regulation mechanisms of PRMT4. Structural analysis identified a molecular switch involving order and disorder transitions of the N terminal helices that governs the active inactive transition. Free energy landscape analysis supported that this transition is thermodynamically accessible. We identified a PRMT3 like allosteric pocket, Cavity 1, whose targeting is predicted to disrupt inter chain communication and impair cofactor binding and active site organization. Dynamic residue network analysis further supported Cavity 1 as a functional allosteric site. We also identified a PRMT4 specific pocket, Cavity 2, with a distinct selectivity profile. These findings validate the active inactive switch and identify two druggable allosteric sites. Although experimental validation is required, this work provides a computational framework for the rational design of PRMT4 selective allosteric inhibitors.
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