Skip to content
Open access

Development of force-field corrections for the RNA A-bulge motif

Aug 2026 · bioRxiv · 0 citations · 2 references
Biology

TL;DR

GHBfix-18Ab, an 18-component hydrogen-bond correction that distinguishes NH and NH□ donors, is developed, demonstrating that targeted refinement of hydrogen-bond interactions provides a practical strategy for systematic improvement of RNA force fields toward more accurate modeling of noncanonical RNA motifs.

Abstract

Many functional RNA motifs adopt structures that deviate from the canonical A-form helix and are emerging targets for RNA-directed therapeutics. The microtubule-associated protein tau (MAPT) A-bulge motif (5′-GCAGU/5′-ACGU) is one such motif. Because its structure is stabilized by a delicate balance of local interactions, its accurate modeling remains a major challenge for molecular dynamics (MD) simulations. The experimentally determined nuclear magnetic resonance (NMR) structure of the MAPT A-bulge motif provides a stringent test of whether RNA force fields can accurately reproduce the experimentally observed conformation. Most current AMBER-family RNA force-field models have incorrectly favored a non-native base-triple state of the MAPT A-bulge motif over the experimentally observed stacked state. Structural comparison of the stacked and base-triple conformations revealed that overly favorable NH□–N hydrogen bonds between the bulged adenosine and an adjacent Watson–Crick base pair were the primary source of this imbalance. We developed gHBfix-18Ab, an 18-component hydrogen-bond correction that distinguishes NH and NH□ donors. gHBfix-18Ab was combined with the previously developed OL3CP and NBfix0BPh corrections to generate the composite model gHBfix-18Ab*. This model restored the experimentally observed stacked state as the global minimum in the calculated free-energy profile and improved agreement with NMR-derived distance data for the A-bulge region. Importantly, gHBfix-18Ab* did not produce marked structural destabilization of the cUUCGg tetraloop, a widely used benchmark for RNA force-field validation, suggesting that the refinement preserves the stability of the unrelated RNA motif. These results demonstrate that targeted refinement of hydrogen-bond interactions provides a practical strategy for systematic improvement of RNA force fields toward more accurate modeling of noncanonical RNA motifs. Graphical Summary

Read PDF

Similar papers

Open access

Experimental data-guided parameterization and validation of an AMBER protein force field

An improved force field is developed, derived from its parent, Amber ff24EXP-GA, and its evaluation against Amber ff14SB and other contemporary force fields, such as CHARMM36m, in capturing the empirically determined conformational properties of unfolded systems: short peptides that serve as model systems for IDPs, and longer unfolded proteins.

Athul Suresh, B. Urbanc · 0 citations
Open access Aug 2026

Exploring Conformational Transitions of Adenine RNA Dimer via Machine Learning Potentials

This work assesses ML potentials for exploring RNA conformations using the adenine–adenine dinucleoside monophosphate (ApA) dimer, a fundamental RNA building block, and parametrized ML potentials based on the equivariant MACE architecture and informed by both ab initio and semiempirical property data.

Leonardo Medrano Sandonas, Macarena Tolmos Nehme, L. F. Cofas-Vargas et al. · 0 citations
Open access Aug 2026

Intra-Protein Interfaces Control Folding Dynamics and Mechanical Stability in a De Novo Designed Repeat Protein

Together, these results show that designed repeat-protein folding is governed by seed formation, interface propagation, and terminal boundary conditions, and establish intramolecular crosslinking as a strategy for rationally reshaping folding landscapes in designed proteins.

Melanie Weiß, Anna Lisa Heit, L. Milles et al. · 0 citations
Open access Jul 2026

Integrative Ensemble Modeling reveals RNA conformations targetable by small molecules

RNA molecules explore heterogeneous conformational ensembles that are essential for their biological function and molecular recognition, yet this intrinsic flexibility poses a major challenge for structure-based drug discovery. In particular, the absence of well-defined binding pockets in static structures limits the identification of ligandable sites. Here, we present an integrative ensemble-based approach that combines enhanced-sampling molecular dynamics simulations with Nuclear Magnetic Resonance data to characterize the conformational landscape of the HIV-1 TAR RNA at atomic resolution. Starting from extensive sampling, we refined the resulting conformational distribution through maximum-entropy reweighting to achieve quantitative agreement with experimental data. Analysis of the reweighted ensemble reveals a diverse set of conformational substates, including compact arrangements that exhibit pocket features compatible with ligand recognition and overlap with known ligand-bound structures. At the same time, highly ligandable conformations, which are only marginally populated, might nonetheless be critical for RNA recognition. Our results demonstrate that integrative ensemble modeling can reveal pharmacologically relevant RNA conformations that are not apparent from experimental static structures, providing a framework for ensemble-based strategies in RNA-targeted drug discovery.

Stefano Bosio, Vincent Schnapka, Mattia Bernetti et al. · 0 citations
Open access Sep 2026

Nearest Neighbor Parameters for Estimating RNA Folding Stability with In Vivo-like Conditions

RNAs regulate gene expression and cellular processes, often relying on specific conformations for function. RNA folding is hierarchical and sequence-dependent, with nearest-neighbor thermodynamic models commonly used to predict secondary structure. Current models were developed using optical melting experiments in 1 M NaCl, which does not represent the cellular environment. To address this, we developed a new model in Advanced Dulbecco’s Modified Eagle Medium (Adv. DMEM), which mimics mammalian extracellular ionic composition. This in vivo-like model provides RNA folding parameters for helical base stacks and loop motifs. Optical melting experiments revealed helical stacks, particularly tandem G-U pairs, are less stabilizing in Adv. DMEM. Loop parameters were generally destabilizing but highly dependent on both sequence and loop type, with internal loops displaying idiosyncratic behavior. Structure prediction benchmarking revealed minimal differences overall, except for tRNAs, which showed improved prediction reliability and enhanced cloverleaf stability. Notably, tRNAs lack internal loops, suggesting further studies in Adv. DMEM could refine secondary structure predictions. This in vivo-like parameter set is included in the RNAstructure software package. Grounding these parameters in a physiologically relevant environment, we improve the biological relevance of RNA secondary structure predictions and establish a foundation for studying RNA folding under in vivo conditions. Graphical Abstract

Olivia M. Hiltke, E. Kierzek, Martina Prochota et al. · 0 citations
Open access Aug 2026

Switching Functional DNA-Binding Modes by Tuning Protein Order-Disorder Equilibria

A conserved sequence-ensemble-dynamics code in Nhp6A is revealed wherein not just stability, but also phosphorylation-induced conformational switching, disordered tail dynamics, and DNA binding-bending closely coordinate chromatin accessibility is revealed.

Shilpi Laha, H. Madhan, Yuji Itoh et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.