ArticlebioRxiv : the preprint server for biology2026
Decoding the Conformational Dynamics and Hyperactivity of Histone H3K36 N-Methyltransferase in Oncogenic Mutations
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
NSD2 is a histone methyltransferase that modifies lysine 36 in histone H3 (H3K36), playing a central role in chromatin organization and transcriptional regulation. Oncogenic mutations, such as E1099K and T1150A in NSD2, have been associated with hyperactive methylation, but the molecular mechanisms underlying this gain of function remain poorly understood. In this study, we performed all-atom molecular dynamics simulations on models of NSD2 bound to the nucleosome for the wild type (WT), E1099K, T1150A, and the E1099K/T1150A double mutant. Analysis of MD simulations reveals that the global dynamics of the enzymes remain unaltered upon mutations. The time-lagged independent component analysis (tICA) and Markov state modeling uncovered fundamental differences in free-energy landscapes among the variants. The WT NSD2 exhibited energetically and kinetically unfavorable transitions between the macrostates along with extended enzyme-substrate distances. On the other hand, the mutant systems demonstrate reduced SAM-H3K36 distances with modified energy landscapes that facilitate transitions or favor prolonged occupancy of catalytically competent states. Importantly, the mutations reorganize the network of intramolecular contacts around the catalytic site, SAM-binding pocket, and histone-binding interface, optimizing substance engagement geometry. These findings demonstrate that oncogenic mutations achieve hyperactivity through strategic reorganization of conformational dynamics rather than simple destabilization, balancing local flexibility with global stability to enhance catalytic efficiency. Our results provide mechanistic insights into NSD2 dysregulation in cancer and establish a framework to develop allosteric inhibitors that target the enzyme's dynamic landscape.
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