Integrating Parallel-Bias Metadynamics-Metainference and Relaxation Dispersion NMR to Resolve Hidden Conformational States Driving Toxin-Channel Recognition.
Aug 2026· Journal of the American Chemical Society· Vol 148 31, pp.
32977-32992
· 0 citations· 71 references
Medicine
Abstract
Conformational dynamics in toxin inhibitors are an important contributor to ion channel affinity, yet toxin multidimensional energy landscapes remain largely unexplored. In the current work, we combine parallel-bias metadynamics-metainference (PBMetaD) simulations with relaxation dispersion NMR to define, at atomistic resolution, the thermodynamics and kinetics of Hui1, a de novo three disulfide toxin derived from the SAK-I family that targets K+-channels. Using the three χ3 disulfide dihedrals as collective variables, an extensive 48-replica well-tempered PBmetaD simulation (16.2 μs cumulative sampling) resulted in a fully converged three-dimensional (3D) free-energy surface comprising eight Hui1 conformers. These basins account for ∼96% of the bias-weighted ensemble and partition into four low- and four high-energy states separated by 7.5 kJ/mol associated with the (-) and (+)Cys12-Cys28 χ3 states, respectively. Transition-state theory identifies rota-isomerization of Cys3-Cys35 as the slowest, and therefore rate-determining, coordinate, while the analogous motions around Cys12-Cys28 and Cys17-Cys32 are ∼5-fold faster. 15N R1ρ relaxation dispersion NMR measurements confirmed these kinetics, identifying two structurally distinct residue clusters exhibiting intermediate and faster exchange processes. The Key Interaction Finder (KIF) approach reveals that Cys17-Cys32 conformation modifies connectivities within a dense interaction network between Cys17 and residues Gln14, Tyr23, Arg24, and Lys29, and correlates with the accessibility of residues Tyr23 and Arg24 of the helix-kink-helix region for interaction with the channel vestibule. Our work establishes PBMetaD as a powerful framework for mapping coupled disulfide and backbone dynamics in toxins and reveals specific conformers and interactions likely to control K+ channel recognition.
Gaussian accelerated molecular dynamics (GaMD) enhances conformational sampling by adding a smooth boost potential without requiring predefined collective variables, but an engine-integrated implementation has not been available in GROMACS. Here, we implement total-, dihedral-, and dual-boost GaMD in GROMACS 2025.4, including staged energy-statistics collection, GPU-based bias evaluation and force scaling, restart support, and outputs required for cumulant-based free-energy reweighting. The implementation was evaluated using four benchmark systems spanning conformational free energies, protein folding, and ligand recognition. For alanine dipeptide, a reweighted 100 ns GaMD trajectory recovered the major free-energy basins and rotational barriers in overall agreement with a 1000 ns conventional MD simulation. For chignolin and TC5b, all three independent trajectories for each system sampled native-like folded states from extended conformations within 300 ns and 1 μs, respectively; the best TC5b structure had a minimum backbone RMSD of 0.03 nm from the experimental structure. In the benzene–T4 lysozyme system, two of five independent 500 ns trajectories captured both ligand binding and dissociation, yielding a bound pose with a minimum ligand RMSD of 0.06 nm from the crystal structure. Across all four systems, the boost-potential distributions were approximately Gaussian, and second-order cumulant reweighting resolved the expected conformational and binding free-energy basins. These results demonstrate that GROMACS-GaMD provides a practical, GPU-enabled, collective-variable-free enhanced-sampling framework for biomolecular free-energy calculations, protein folding, and ligand-binding studies.
Accurate solvation free energies from molecular dynamics simulations require efficient sampling of coupled slow variables, including solvent coordinates, solute conformational modes, and the alchemical coordinate $\lambda$. Here, we develop a $\lambda$-dynamics framework that combines mass scaling, on-the-fly probability enhanced sampling (OPES), and driven adiabatic free energy dynamics (d-AFED) to address these sampling challenges within a unified protocol. For rigid organic solutes, Hamiltonian replica exchange with mass scaling is first used to quantify the effect of octanol solvent relaxation. Reducing all octanol atomic masses by a factor of ten accelerates convergence by more than fivefold while preserving equilibrium solvation free energies. These calculations then provide reference benchmarks for $\lambda$-OPES, a dual-bias $\lambda$-dynamics strategy that combines the"standard"and"explore"variants of OPES to promote transitions along the alchemical coordinate. This approach reaches convergence on timescales comparable to replica exchange, but without predefined $\lambda$ windows or multiple parallel simulations. For flexible $N$-acetyl amino-acid amide solutes, $\lambda$-OPES is coupled with d-AFED on selected backbone and side-chain dihedrals to enable simultaneous alchemical and conformational enhanced sampling. This combined strategy improves agreement with experimental octanol-water partition coefficients and reduces the mean absolute error from 0.75 log units with $\lambda$-OPES alone to 0.30 log units with $\lambda$-OPES-d-AFED. Overall, this work establishes an integrated enhanced sampling protocol for solvation free energy calculations across rigid organic solutes and flexible peptide-like solutes, and provides a foundation for the application of alchemical free energy methods to larger and more conformationally complex systems.
Gabriela B. Correa, C. Abreu, Nishanth N Nair et al.· 0 citations
These results establish replica-exchange enhanced sampling, particularly T-REMD, as an effective strategy for constructing experimentally validated RNA ensembles and accessing conformations corresponding to rare functional substates.
The results show that while 2AP substitution does not significantly alter stacking propensity, it substantially modulates the free energy landscape, leading to a redistribution of populations among stacking modes and supporting the hypothesis that base stacking quenches 2AP fluorescence and promotes dark state formation.
Revanth Elangovan, Emily Stetson, J. Widom et al.· Physical Chemistry, Chemical...· 0 citations
Understanding how hydration reshapes the structure and conformational flexibility of biomolecular ions is essential for connecting gas-phase spectroscopy to behavior in aqueous environments. Glycine, the simplest amino acid, exhibits rich microsolvation behavior, with competing intra- and intermolecular hydrogen-bonding motifs that evolve with hydration and temperature. Although cryogenic ion spectroscopy has provided detailed measurements of hydrated protonated glycine (GlyH+) clusters, interpreting these spectra and relating them to molecular hydration motifs remains challenging. Here, we develop a data-driven many-body potential energy function for GlyH+-H2O interactions and combine it with replica-exchange molecular dynamics to identify isomeric equilibria, and with temperature-elevated path-integral coarse-graining simulations to model GlyH+(H2O)n clusters, accounting for nuclear quantum effects. This framework captures many-body interactions with high-level ab initio accuracy and enables direct computation of infrared spectra for comparison with experiment. By applying an inverse spectral reconstruction of isomeric ensembles, we quantitatively decompose the experimental spectra into contributions from competing hydration motifs and extract their relative populations. Our results characterize the sequential formation of the first and second solvation shells, quantify the competition between intramolecular and water-mediated hydrogen bonds, and reveal temperature dependence and nuclear quantum effects. Overall, this study provides a transferable approach to understanding the hydration of biomolecular systems across scales, from gas-phase clusters to bulk aqueous solutions.
Zoe A. Solomon, R. Rashmi, Ruihan Zhou et al.· Journal of Physical Chemistr...· 0 citations
These results demonstrate that symmetrical dual-site targeting, combined with dynamic thermodynamic locking, provides a resilient framework to overcome mutational resistance in AChE inhibitors.
Ghazala Muteeb, S. Nilewar, Mohammad Aatif et al.· Pharmaceuticals· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
