Potential Of Mean Force Research Articles

Evolution equations for open systems and collective variables: Which equation would you like to solve by molecular dynamics simulation?

In molecular dynamics simulations, the Langevin equation is frequently used to model the dynamics of collective variables and of systems coupled to baths. Often, external forces are added to the Langevin equation (e.g., when using targeted or steered molecular dynamics in biomolecular simulation). It is also popular to add derivatives of thermodynamic potentials to the Langevin equation as effective forces (e.g., when using a potential of mean force in a coarse-grained polymer model). These practices can be adventurous. In this article, we recall derivations of different versions of the Langevin equation and we discuss why care is needed if one would like to make changes to the structure of the equation.

The Role of Protonation in the PfMATE Transporter Protein Structural Transitions.

Multi-antimicrobial extrusion (MATE) transporter membrane proteins provide drug and toxin resistivity by expelling compounds from cells. MATE proteins can be pictured as V-shaped. To regulate its functioning, the protein structure can switch between outward-facing (OF) and inward-facing (IF). Pyrococcus furiosus MATE (PfMATE) is the only member of the multidrug/oligosaccharidyl-lipid/polysaccharide (MOP) superfamily that has available both the IF and OF crystal structures. With the availability of both the IF and OF structures, we are able to perform computational investigations to determine how protonation of specific amino acids causes a cascade of changes in the protein conformation that allow PfMATE to change its state from OF to IF in order to regulate its antiporter function. Using a variety of computational and theoretical techniques, we investigated four different systems of IF and OF PfMATE along with the native archaeal lipid bilayer, without or with protonation at the experimentally determined locations within the protein. We performed molecular dynamics (MD) simulations to investigate the flexibility of the four different PfMATE structures and also performed targeted molecular dynamics (TMD) simulations, during which we observed occluded conformations. Our analysis of hydrogen bond changes, potential of mean force, dynamic network analysis, and transfer entropy analysis provides information on how protonation can induce cascading structural changes responsible for the transition between the IF and OF configurations.

Simple model for the fracture of a polymer chain: Single-bond potential of mean force and tension-based rate constants for chain rupture.

A linear chain of N particles connected by Morse bonds with periodic boundaries in a Brownian bath is considered as a model for polymer fracture. The potential of mean force (pomf) with respect to the length of a bond and its energy and entropic components are computed via Langevin Dynamics simulations at various chain elongations λ > 1. A narrow range of λ values is identified over which equilibrium is established between an intact (i) and a fractured (f) state over a pomf barrier. While the barrier and (f) regions of the pomf are well described by a well-known (N - 1)-bond adiabatic approximation, the shape of the (i) region departs from it, exhibiting a bimodal character. A new, 1-bond adiabatic approximation is proposed to explain this. The lower envelope of the two adiabatic approximations provides an excellent description of the pomf. The relationship between (f) states for individual bonds and for the entire chain is elucidated. A new approach, based on analysis of equilibrium tension autocorrelation functions, is developed to extract rate constants for the fracture and reformation of the chain in dependence of λ. Results from it agree with tension relaxation during nonequilibrium simulations initiated at equispaced configurations of the particles. Rate constants for chain fracture conform to a Boltzmann-Arrhenius-Zhurkov dependence on the tension averaged over the intact state of the chain, the activation length being higher than estimated from pomf extrema. These findings constitute a step toward a predictive multiscale simulation scheme for fracture in polymeric materials.

Exploring the covalent inhibition mechanisms of inhibitors with two different warheads acting on SARS-CoV-2 Mpro by QM/MM simulations

SARS-CoV-2 Mpro had been reported to react with covalent inhibitors 14c and C7, containing a vinyl sulfanilamide and chloromethylamide as the warheads, respectively. However, the detailed reaction mechanisms and warhead effects are still unclear. In this study, the initial state of the catalytic dyad Cys145/His41 is determined as neutral during the non-covalent binding, through MM-PBSA free energy calculations. The Potential of Mean Forces (PMFs) have been computed by QM/MM MD method, obtaining the free energy changes from reactants to products. Both reactions follow asynchronous mechanism. Except the similar proton transfer (PT1), subsequently, nucleophilic addition and an additional proton transfer (PT2) for 14c, while an SN2 nucleophilic substitution for C7 are underwent, respectively. The reaction activation barrier and free energy trends both are in consistent with the experimental IC50 results. Our research enhances understanding of the inhibitory mechanism, and provides insights for designing novel and more effective inhibitors targeting SARS-CoV-2 Mpro.

Exploring Free Energy Landscapes for Protein Partitioning into Membrane Domains in All-Atom and Coarse-Grained Simulations.

It is known that membrane environment can impact the structure and function of integral membrane proteins. As such, elucidation of the thermodynamic driving forces governing protein partitioning between membrane domains of varying lipid composition is a fundamental topic in membrane biophysics. Molecular dynamics simulations provide valuable tools for quantitatively characterizing the free energy landscapes governing protein partitioning at the molecular level. In this study, we propose an efficient simulation methodology for the calculation of free energies for the partitioning of transmembrane proteins between liquid-disorder (Ld) and liquid-ordered (Lo) domains in all-atom (AA) phase-separated lipid bilayers. The computed potential of mean force defining the equilibrium partition coefficients is compared for AA and coarse-grained systems. Energy decomposition is used to identify differences in the underlying thermodynamics. Our findings highlight the importance of employing AA models to accurately estimate relevant free energy changes during protein translation between membrane domains.

Direction reverse of the thermo-osmosis for a liquid in a nanochannel

Thermo-osmosis describes the fluid flow due to thermal gradients. Usually, thermo-osmosis for a liquid is from high to low temperature. However, in certain cases, the direction of the thermo-osmosis can be reversed (from low to high temperature), i.e., negative thermo-osmosis, and the underlying mechanism for the direction reverse of the thermo-osmosis is still unclear. In the present paper, we study the direction reverse of thermo-osmosis for a liquid in nanochannels by using molecular dynamics simulations. The research findings indicate that the direction and strength of thermo-osmosis depend significantly on the interaction strength between the solid and liquid. The analysis of the potential mean force distribution along the flow direction reveals that the change from positive to negative thermo-osmosis is linked to a reversal in the slope of the potential mean force distribution. Therefore, the sign of the slope of potential mean force distribution can be used as a criterion to predict the direction of thermo-osmosis. The findings in the present paper pave the way for the application of the thermo-osmosis phenomenon.

Development of Neural Network Potentials for Studying Chemical Behaviors of La3+/Nd3+ Ions in Molten LiCl-KCl-CsCl in Combination with Raman Spectroscopy.

The chemistry of molten salts has attracted great research interest owing to their wide applications in diverse fields. In the pyrochemical reprocessing of spent nuclear fuel or molten salt nuclear reactors, lanthanide elements as the principal fission products bring about changes in the composition and properties of molten salts. Herein, we report a comprehensive study on the coordination chemistry of the representative trivalent lanthanide ions (La3+/Nd3+) in LiCl-KCl-CsCl using a multiscale strategy combining Raman spectroscopy, deep learning, and large-scale molecular dynamics (MD) simulations. The neural network potential (NNP)-based MD and Raman spectroscopy studies revealed that La3+/Nd3+ ions prefer to form persistent octahedron complexes with the six-coordinated species as the dominant species at high temperatures. Compared to LaCl63-, NdCl63- shows higher stability with obviously longer lifetimes in LiCl-KCl-CsCl, as confirmed by the observed stronger interaction of Nd3+-Cl- pairs. The total and partial structure factors further indicated the formation of a more stable network structure in LiCl-KCl-CsCl containing NdCl3. Besides, the temperature exerts a larger influence on the local structures of the La3+ species compared to the Nd3+ analogues. According to the potential mean force calculations, the bond dissociation energies follow the order Ln-Cl > Li-Cl > K-Cl > Cs-Cl in LiCl-KCl-CsCl-LnCl3. The NNP-based large-scale MD simulations have been verified to be an efficient and powerful way in molten salt chemistry research.

Elucidating the Mechanism of Helium Evaporation from Liquid Water.

We investigate the evaporation of trace amounts of helium solvated in liquid water using molecular dynamics simulations and theory. Consistent with experimental observations, we find a super-Maxwellian distribution of kinetic energies of evaporated helium. This excess of kinetic energy over typical thermal expectations is explained by an effective continuum theory of evaporation based on a Fokker-Planck equation, parametrized molecularly by a potential of mean force and position-dependent friction. Using this description, we find that helium evaporation is strongly influenced by the friction near the interface, which is anomalously small near the Gibbs dividing surface due to the ability of the liquid-vapor interface to deform around the gas particle. Our reduced description provides a mechanistic interpretation of trace gas evaporation as the motion of an underdamped particle in a potential subject to a viscous environment that varies rapidly across the air-water interface. From it we predict the temperature dependence of the excess kinetic energy of evaporation, which is yet to be measured.

Changing Your Martini Can Still Give You a Hangover.

The Martini 3.0 coarse-grained force field, which was parametrized to better capture transferability in top-down coarse-grained models, is analyzed to assess its accuracy in representing thermodynamic and structural properties with respect to the underlying atomistic representation of the system. These results are compared to those obtained following the principles of statistical mechanics that start from the same underlying atomistic system. To this end, the potentials of mean force for lateral association in Martini 3.0 binary lipid bilayers are decomposed into their entropic and enthalpic components and compared to those of corresponding atomistic bilayers that have been projected onto equivalent coarse-grained mappings but evolved under the fully atomistic forces. This is accomplished by applying the reversible work theorem to lateral pair correlation functions between coarse-grained lipid beads taken at a range of different temperatures. The entropy-enthalpy decompositions provide a metric by which the underlying statistical mechanical properties of Martini can be investigated. Overall, Martini 3.0 is found to fail to properly partition entropy and enthalpy for the PMFs compared to the mapped all-atom results, despite changes made to the force field from the Martini 2.0 version. This outcome points to the fact that the development of more accurate top-down coarse-grained models such as Martini will likely necessitate temperature-dependent terms in the corresponding CG force-field; although necessary, this may not be sufficient to improve Martini. In addition to the entropy-enthalpy decompositions, Martini 3.0 produces an incorrect undulation spectrum, in particular at intermediate length scales of biophysical pertinence.

Unwinding DNA strands by single-walled carbon nanotubes: Molecular docking and MD simulation approach

Despite the growing research into the use of carbon nano-tubes (CNTs) in science and medicine, concerns about their potential toxicity remain insufficiently studied. This study utilizes molecular docking calculations combined by molecular dynamics simulations to investigate the dynamic intricacies of the interaction between single-walled carbon nanotubes (swCNTs) and double-stranded DNA (dsDNA). By examining the influence of swCNT characteristics such as length, radius, and chirality, our findings shed light on the complex interplay that shapes the binding affinity and stability of the dsDNA-swCNT complex. Molecular docking results identify a zigzag swCNT, with a radius of 0.16 Å and a length of 38 Å, as exhibiting the highest binding affinity with dsDNA (−23.9 kcal/mol). Comprehensive analyses, spanning docking results, binding energies, RMSD, radius of gyration, and potential of mean force (PMF) profiles, provide a detailed understanding of the denaturation dynamics. The PMF profiles reveal the thermodynamic feasibility of the DNA-CNT interaction, outlining distinct energy landscapes and barriers: when the selected swCNT binds within the dsDNA groove, the system becomes trapped at the first and second local energy minima, occurring at 1.48 nm and 1.00 nm, respectively. Intramolecular hydrogen bond calculations show a significant reduction, affirming the denaturing effect of swCNTs on DNA. Furthermore, the study reveals a significant reduction in the binding affinity of Ethidium Bromide (EB) to dsDNA following its interaction with swCNT, with a decrease in EB binding to dsDNA of approximately 13.2 %. This research offers valuable insights into the toxic effects of swCNTs on dsDNA, contributing to a rationalization of the cancerous potential of swCNTs.

Theoretical Investigation into Polymorphic Transformation between β-HMX and δ-HMX by Finite Temperature String

Polymorphic transformation is important in chemical industries, in particular, in those involving explosive molecular crystals. However, due to simulating challenges in the rare event method and collective variables, understanding the transformation mechanism of molecular crystals with a complex structure at the molecular level is poor. In this work, with the constructed order parameters (OPs) and K-means clustering algorithm, the potential of mean force (PMF) along the minimum free-energy path connecting β-HMX and δ-HMX was calculated by the finite temperature string method in the collective variables (SMCV), the free-energy profile and nucleation kinetics were obtained by Markovian milestoning with Voronoi tessellations, and the temperature effect on nucleation was also clarified. The barriers of transformation were affected by the finite-size effects. The configuration with the lower potential barrier in the PMF corresponded to the critical nucleus. The time and free-energy barrier of the polymorphic transformation were reduced as the temperature increased, which was explained by the pre-exponential factor and nucleation rate. Thus, the polymorphic transformation of HMX could be controlled by the temperatures, as is consistent with previous experimental results. Finally, the HMX polymorph dependency of the impact sensitivity was discussed. This work provides an effective way to reveal the polymorphic transformation of the molecular crystal with a cyclic molecular structure, and further to prepare the desired explosive by controlling the transformation temperature.

Tutorial on Umbrella Sampling Simulation with a Combined QM/MM Potential: The Potential of Mean Force for an SN2 Reaction in Water.

We present a tutorial to carry out umbrella-sampling free-energy simulations with a combined quantum mechanical and molecular mechanical (QM/MM) potential, which may also be used in a computational or biophysical chemistry curriculum for first-year graduate and undergraduate students. In this article, we choose the Type II SN2 Menshutkin reaction between ammonia and chloromethane to construct the potential of mean force (PMF) for the reaction in aqueous solution. In this exercise, we wish to accomplish three tasks: (1) an understanding of the concept of PMF and the umbrella-sampling free-energy simulation method, (2) the use of a combined QM/MM potential in molecular dynamics simulation of chemical reactions, and (3) an understanding of solvent effects and intermolecular interactions on chemical reactions through comparison with gas-phase results. Analysis of the simulation results allows students to appreciate the difference between the transition state along a PMF from statistical simulations versus the optimized saddle point in the gas phase, the shift of transition state with respect to solvation, and the significance of electronic polarization. Through this tutorial, students will gain the necessary skills to carry out free energy simulations of chemical reactions in solution and in enzymes both in a classroom and in the laboratory.

Absorption of Polypropylene in Dipalmitoylphosphatidylcholine Membranes: The Role of Molecular Weight and Initial Configuration of Polymer Chains.

We study by molecular dynamics simulations the absorption of polypropylene (PP) chains within a dipalmitoylphosphatidylcholine (DPPC) lipid membrane in aqueous solvent. DPPC represents the most abundant phospholipid in biological membranes, while PP is one of the most common synthetic polymers diffused in the anthropic environment. By following in detail the absorption process, and the corresponding structural modification undergone by the membrane, we show how the initial configuration and the PP molecular weight determine the overall behavior of the system. Specifically, if PP chains initially lie on the DPPC surface, they are fully absorbed; likewise, polymers initially included within the membrane cannot escape from. On the other hand, if polymers are placed sufficiently apart from the membrane, they have time to join together and coalesce into a few nanoparticles. At contact, such nanoparticles may completely dissolve (for low molecular weight) and then be absorbed. For high molecular weight, not all of them dissolve, and therefore the system attains a condition in which some of the chains are absorbed, while others form a residual nanoparticle staying outside (but in contact with) the membrane. Such a state─albeit energetically unfavorable with respect to a condition in which all PP chains are absorbed─remains stable, at the least over a substantial simulation time, extending in our study up to 1.6 μs. The tendency for polymers to spontaneously form aggregates, which then prefer to stay in contact with the membrane, is further corroborated by calculation of the DPPC-nanoparticle potential of mean force.

Molecular permeation through large pore channels: computational approaches and insights.

Computational methods such as molecular dynamics (MD) have illuminated how single-atom ions permeate membrane channels and how selectivity among them is achieved. Much less is understood about molecular permeation through eukaryotic channels that mediate the flux of small molecules (e.g. connexins, pannexins, LRRC8s, CALHMs). Here we describe computational methods that have been profitably employed to explore the movements of molecules through wide pores, revealing mechanistic insights, guiding experiments, and suggesting testable hypotheses. This review illustrates MD techniques such as voltage-driven flux, potential of mean force, and mean first-passage-time calculations, as applied to molecular permeation through wide pores. These techniques have enabled detailed and quantitative modeling of molecular interactions and movement of permeants at the atomic level. We highlight novel contributors to the transit of molecules through these wide pathways. In particular, the flexibility and anisotropic nature of permeant molecules, coupled with the dynamics of pore-lining residues, lead to bespoke permeation dynamics. As more eukaryotic large-pore channel structures and functional data become available, these insights and approaches will be important for understanding the physical principles underlying molecular permeation and as guides for experimental design.

Unveiling gas transport mechanisms in tunable MXene nanochannels: Insights from molecular dynamics simulations

MXene-based membranes have shown tremendous potential in gas separation applications. Here, molecular dynamics (MD) simulations are used to investigate the effects of varying the structural parameters of Ti₃C₂O₂ nanochannels on the permeation and separation performance of H₂, CO₂, N₂, and CH₄ gases. The results demonstrate that the interlayer spacing significantly influences gas permeability, with wider channels generally exhibiting higher permeance. Channel length, however, has a relatively minor impact on permeability, varying by gas species. Potential of mean force (PMF) analysis reveals that CO₂ molecules face a notable energy barrier at the channel entrance and have the strongest interactions with the MXene interface within the channel, potentially leading to blockage. Spatial density analysis further confirms this CO₂ blockage phenomenon, which diminishes as the interlayer spacing increases. In terms of gas separation selectivity, H₂/CH₄ and H₂/CO₂ mixtures exhibit high selectivity, with maximum values of 41.08 and 27.06, respectively. Notably, the H₂/CO₂ system exhibits a positive correlation between permeability and selectivity, breaking the traditional permeability-selectivity trade-off. This anomalous behavior can be attributed to the CO₂ blockage effect. This study provides theoretical guidance for the design and optimization of MXene-based membrane materials in practical applications.

Depletion forces beyond the diluted limit

The determination of the effective interactions in many-body systems still possesses a tremendous challenge in Condensed Matter Physics. The problem mainly resides in the fact that, on the one hand, there is not a unique route to obtain the effective forces between the ”observable” constituents and, on the other hand, one typically considers that the diluted limit of those components always corresponds to the effective forces at all particle concentrations. In the particular case of colloidal dispersions, it is very important to have experimental, theoretical, and computational tools that allow us to determine, accurately and without using significant approximations, the effective interactions between colloids. In this contribution, we report on a detailed study of depletion potentials in colloidal mixtures at finite concentration, namely, binary and ternary mixtures of disks (in two dimensions or 2D) and spheres (in three dimensions or 3D). To this end, the depletion forces between the large colloidal species are determined through a recently developed scheme based on the so-called contraction of the description, which has been extended and built at the level of the bare forces, i.e., we basically consider that all particles interact through the bare potentials and the net force acting on a given particle is determined by the second’s Newton law. This scheme can be easily adapted to Molecular Dynamics simulations. To verify the physical consistency of the formalism, we explicitly show that in the diluted limit of large particles, the resulting depletion potential reproduces correctly the AO-Vrij limit. As further proof of the accuracy of the results, a comparison of the structure of the large colloids in the whole mixture with the one that results using exclusively the depletion potential is carried out. In 3D, the results are explicitly compared with the potential of mean force and those obtained with the integral equations formalism. We also report a new colloidal stability mechanism based on the use of two different species of depletant agents at low and equal concentrations. Although we highlight the fact that the depletion potential depends on the concentration of the large species, we show that this dependence can be eliminated when the colloidal dispersion is open to a reservoir of small particles, i.e., when the chemical potential of small particles is fixed. Finally, we report the effects of polydispersity on the depletion interaction between large colloids.

State transitions of coupled Gi-protein: Insights into internal water channel dynamics within dopamine receptor D3 from in silico submolecular analyses

Dopamine is a crucial neurotransmitter in the central nervous system (CNS) that facilitates communication among neurons. Activation of dopamine receptors in the CNS regulates key functions such as movement, cognition, and emotion. Disruption of these receptors can result in severe neurological diseases. Although recent research has elucidated the structure of D3R in complex with Gi-protein, revealing the binding and activation mechanisms, the precise conformational changes induced by G-protein activation and GDP/GTP exchange remain unclear. In this study, atomic-level long-term molecular dynamics (MD) simulations were employed to investigate the dynamics of D3R in complex with different states of Gi-protein and β-arrestin. Our simulations revealed distinct molecular switches within D3R and fluctuations in the distance between Ras and helical domains of G-protein across different G-protein-D3R states. Notably, the D3R-GTP-Gi state exhibited increased activity compared with the D3R-empty-Gi state. Additionally, analyses of potential of mean force (PMF) and free energy landscapes for various systems revealed the formation of a continuous water channel exclusively in the D3R-Gi-GTP state. Furthermore, allosteric communication pathways were proposed for active D3R bound to Gi-protein. This study offers insights into the activation mechanism when Gi-protein interacts with active D3R, potentially aiding in developing selective drugs targeting the dopaminergic system.

An in silico design method of a peptide bioreceptor for cortisol using molecular modelling techniques

Cortisol is established as a reliable biomarker for stress prompting intensified research in developing wearable sensors to detect it via eccrine sweat. Since cortisol is present in sweat in trace quantities, typically 8–140 ng/mL, developing such biosensors necessitates the design of bioreceptors with appropriate sensitivity and selectivity. In this work, we present a systematic biomimetic methodology and a semi-automated high-throughput screening tool which enables rapid selection of bioreceptors as compared to ab initio design of peptides via computational peptidology. Candidate proteins from databases are selected via molecular docking and ranked according to their binding affinities by conducting automated AutoDock Vina scoring simulations. These candidate proteins are then validated via full atomistic steered molecular dynamics computations including umbrella sampling to estimate the potential of mean force using GROMACS version 2022.6. These explicit molecular dynamic calculations are carried out in an eccrine sweat environment taking into consideration the protein dynamics and solvent effects. Subsequently, we present a candidate baseline peptide bioreceptor selected as a contiguous sequence of amino acids from the selected protein binding pocket favourably interacting with the target ligand (i.e., cortisol) from the active binding site of the proteins and maintaining its tertiary structure. A unique cysteine residue introduced at the N-terminus allows orientation-specific surface immobilization of the peptide onto the gold electrodes and to ensure exposure of the binding site. Comparative binding affinity simulations of this peptide with the target ligand along with commonly interfering species e.g., progesterone, testosterone and glucose are also presented to demonstrate the validity of this proposed peptide as a candidate baseline bioreceptor for future cortisol biosensor development.

Controlled released dynamics of methotrexate from chitosan-based capsules: A detailed energy landscape analysis

Polymeric membranes are extensively used to construct vehicles for various drug delivery applications. In this study, we investigated the potential of chitosan-based membranes as a carrier for the controlled release of methotrexate (MTX), a widely used drug in cancer treatment. The chitosan (CS) chains were cross-linked with sodium tripolyphosphate (STPP) to form a rigid matrix capable of encapsulating MTX. Molecular dynamics simulations were employed to assess the performance of the CS-based membranes in releasing MTX upon exposure to water. We have calculated the potential of mean force to understand the energy landscape in the aqueous medium or ethanol-water solution. We have observed that the free energy in the ethanol-water solution reduced to ∼52.4 kcal/mol as compared to an aqueous solution. In addition, we have shown the effect of the concentration of STPP on the binding of CS with MTX. Understanding how STPP concentration affects MTX release is crucial for designing drug delivery systems. By adjusting the concentration of STPP, one can fine-tune the release profile of the drug. We have also shown the comparative study of energy requirement to release a drug molecule from the CS matrix with and without STPP molecules. The pair correlation displayed that the water molecules have a stronger interaction with the STPP molecules compared to CS chains and MTX molecules. Our findings indicate that the CS nanoparticles exhibit promising characteristics for controlled drug release, making them a potential candidate for improving the efficacy and safety of MTX therapy in cancer treatment.

Water–triglyceride interfaces limit permeability and diffusion of aroma molecules in butter

AbstractInsight into the dynamics of aroma molecules in bulk phases and at water–triglyceride interfaces is crucial for elucidating the aroma release mechanisms in complex dairy products such as butter. This study employs classical, all‐atom molecular dynamics simulations with umbrella sampling to investigate the energetics and kinetics of key aroma‐active compounds, including diacetyl, ‐decalactone, and butyric acid, at interfaces of 1,3‐dipalmitoyl‐2‐oleoylglycerol (POP) in water. The chemical properties of aroma compounds, including polarity, hydrogen bonding, and van der Waals interactions, play a pivotal role in their interaction with interfacial molecules, resulting in unique profiles of the potential of mean force and diffusivity. In particular, ‐decalactone preferentially resides at the interface and accumulates in the triglyceride phase. Aroma permeability through the complexly organized water–triglyceride interface significantly decreases from ‐decalactone to butyric acid, with a less pronounced reduction for diacetyl. Surprisingly, this trend in aroma permeability at interfaces does not coincide with trends in aroma diffusion within both pure bulk phases. This discrepancy is attributed to local, heterogeneous molecular structuring at water–triglyceride interfaces, impeding the interfacial permeation processes and leading to local aroma confinement.Practical Application: Employing a water–POP interface as a case study, the methodology investigates aroma compound diffusion within bulk phases, delineating limitations in aroma permeability in dairy products with extended water–triglyceride interfaces. This is a substep in the aroma release process, contributing to the interpretation of perception studies by sensory panels in human sensory experiments and fostering a deeper understanding of the intricate dynamics inherent to individual compounds.