Physical Chemistry Chemical Physics

The process of drug unbinding is of immense importance in the field of biophysics and therapeutics. The behavior of these systems is greatly influenced by their thermodynamic and kinetic properties. Therefore, it is crucial to accurately estimate the ligand binding free energies and rate of ligand dissociation, yet these processes are often governed by rare event transitions that lie beyond the reach of standard brute-force molecular dynamics simulations. While enhanced sampling simulations offer a solution, their efficacy is strictly contingent upon the selection of appropriate collective variables (CVs) which is non-trivial for complex systems like protein-ligand complexes. In this study, we present a method to derive optimized CV from transition state region (TS) via an interpretable machine learning (ML) model, Elastic Net. By employing some physically intuitive order parameters, the derived optimized CV from the TS-region greatly accelerate ligand binding-unbinding transitions and achieves rapid free energy surface (FES) convergence across diverse systems including buried and solvent exposed active sites such as Trpsin-benzamidine complex, host-guest systems and sodium epoxidase etc. Intriguingly significant contribution of the ligand hydration is found in the optimized CV which depicts crucial role of solvent in driving ligand binding-unbinding transitions. The estimated binding free energies for different protein-ligand complexes match quite well with experiments, while maintaining a low computational cost. The derived optimized CV is also used to calculate the ligand residence times across different systems and calculated residence times are within the experimental range for all systems, again with very little computational costs. Moreover, we show that the optimized CV constructed from TS region via an interpretable ML model is transferable across diverse systems, offering a robust and scalable framework for drug discovery and investigation of complex biomolecular recognition.

It is valuable to calculate alchemical free energy changes in drug discovery and development. Thermodynamics Integration (TI) has been widely used in computational chemistry for estimating free energy changes with alchemical transformations. However, TI based on usually short Molecular Dynamics (MD) simulations often suffers from insufficient conformational sampling. Here, we have integrated Gaussian accelerated MD and TI (GaMD-TI) to enhance the conformational sampling and improve accuracy of free energy calculations. GaMD-TI has been demonstrated in model systems of alchemical changes in the Valine dipeptide and mutation cycle of the Alanine <-> Valine <-> Isoleucine (AVI) residues. Simulations showed that when GaMD boost potentials followed near-Gaussian distribution, the free energy change could be reweighted accurately through generalized cumulant expansion to the second order. The total free energy change often exhibited faster convergence using Selective GaMD (SGaMD) than using conventional MD (cMD). Accuracy of the free energy estimates from SGaMD-TI simulations was similar to or higher than those from cMD-TI simulations, although the differences were subtle for these small model systems. Meanwhile, dihedral angles in the model systems underwent significantly more frequent conformational transitions in SGaMD than in cMD, indicating improved sampling. Future studies are planned on larger systems with more complicated alchemical changes, such as ligand binding to proteins/nucleic acids and mutations at biomolecular binding interfaces. GaMD-TI should be broadly applicable to alchemical free energy calculations and therapeutic design.

The high energy-efficiency of life is hard to understand only with classical physics. Many efforts have been made to study its mechanism based on quantum mechanics; the progress is nevertheless slow due to lack of experimental evidence with living cells. Here, combining experiments on cells, tissues and mitochondria with a theoretical model, we demonstrate a quantum state of mitochondria, which can be employed to modulate ATP production in living cells. We found an anomalous 71.0-THz oscillation mode only in living cells and tissues, which is highly determined by intact structure of mitochondria, and cannot be assigned to any specific molecules. Based on experimental data, a quantum model of light-matter coupling was introduced to trace the origin of this mode. Our calculations suggest a quantum superposition state of functional mitochondrion that forms by the coupling of light and lipid CH2 bonds in functional cristae, and induces a splitting of the intrinsic CH2 vibration mode of 87 THz to two levels at 71 THz and 103 THz, respectively. The former can be observed only in living cells and tissues; whereas the latter falls in the range (90-110 THz) of biomolecular and water vibrations, thus indistinguishable. Additional experiments revealed this mitochondrial quantum state able to serve as an efficient channel to modulate ATP production. Our findings provide a quantum mechanics view for understanding living cells, and it will be interesting to further explore whether such quantum state could act as a channel for energy metabolism, and even information transmission in life.

Amylose contributes to starch crystallinity, but the stability of packed amylose double helices in water at elevated temperature remains insufficiently characterized. Here, we used molecular dynamics simulations to test whether chain length affects the short-timescale stability of A-type amylose oligomers in water. Six systems differing in chain length (6, 12, or 24 glucose units per chain) and oligomer size (isolated double strand or dodecamer of six double strands) were simulated, and five independent 1-s production runs were analyzed for each simulated condition. Oligomers with six glucose units showed structural collapse accompanied by increased water penetration. By contrast, dodecamers with 12 or 24 glucose units largely retained packed double-helical organization over the simulated timescale, although fraying was observed at their ends. These results indicate that chain length and lateral packing strongly affect the early structural response of amylose-like crystalline segments in hot water. The present simulations do not establish the ultimate fate of longer oligomers at longer timescales, but they identify a relative stability difference that is relevant to molecular interpretations of hydration-driven disordering in starch.

Nanoplastic contamination is increasingly recognized as a biochemical stressor, yet the molecular determinants governing how polymer fragment size dictates protein-level interactions remain poorly understood. Here, we combine molecular docking and all-atom molecular dynamics simulations to characterize the interaction of polyethylene (PE) oligomers of increasing length (n = 3, 5, 7, and 14 repeat units) with human catalase, a tetrameric heme enzyme central to cellular antioxidant defense. Single-chain simulations reveal that short PE fragments (3-, 5-, and 7-mer) migrate from an initial domain-connector pose toward a heme-proximal, previously characterized inhibitor-binding site, whereas the 14-mer remains kinetically confined to a peripheral surface site, implicating short-chain PE as a potential catalase inhibitor. In multichain corona systems, backbone dynamics show a non-monotonic, chain-length-dependent destabilization, with the 3- and 5-mer inducing the greatest structural perturbation and the 14-mer best preserving native-like dynamics despite forming an extensive, percolating surface network across all four subunits. MM-PBSA free energy decomposition identifies van der Waals interactions as the dominant thermodynamic driver of binding, while electrostatic surface mapping indicates that cationic surface patches instead govern long-range spatial targeting of PE chains. These findings establish a framework linking nanoplastic fragment size to protein-level toxicity, with direct implications for assessing the biochemical risk of environmentally weathered polyethylene.

G protein-coupled receptors (GPCRs) represent the largest membrane protein family in the human body and the major targets of FDA-approved medications. Unlike some other physiological proteins, GPCRs are highly plastic and often exist as collections of conformational ensembles in the environment to exert their function. Therefore, understanding how a GPCR adopts different conformational ensembles in response to ligands and signaling partners is essential for drug development. 19F-NMR has emerged as one of the most promising tools in this regard; however, a well-established 19F-labeling system is still lacking, including an effective 19F probe that meets both environmental susceptibility and NMR sensitivity requirements, even though progress has been made dramatically in recent years. Thus, this manuscript reports a novel conformational probe (4-(bromomethyl)-ethoxy-2-(trifluoromethyl)benzene, BTMB) that offers paramount benefits for future GPCR conformational dynamics studies. To rationalize the mechanism behind BTMB's superiority for future probe development, we performed MD simulations, referenced to the current state-of-the-art probe, BTFMA. Our study suggests that the spatial proximity of aromatic residues significantly influences the chemical shift dispersion and linewidths of related 19F-probe-profiled conformational states, as well as the rigidity and compactness of -CF3 in the target protein.

Lipid nanoparticles (LNPs) are one of the leading platforms for delivering nucleic acid therapeutics, yet their efficacy is limited by physicochemical interactions with the extracellular matrix (ECM) that trap the particles before they reach target cells. PEGylated nanoparticles mitigate these interactions by forming a protective steric layer on their surfaces. However, there is a lack of a predictive tool that gives mechanistic insights about how PEG surface density governs the underlying interaction and results in enhanced diffusive transport of LNPs through the ECM. Here, we present a multiscale hierarchical computational framework that couples all-atom constant pH molecular dynamics (CpHMD) with a highly coarse-grained model of the complete LNP within a crosslinked hyaluronic acid (HA) network. These atomistic simulations resolve the free energy of interaction between the LNP surface and HA chains across varying PEG lipid compositions, and integrate these free energy profiles to inform the coarse-grained simulations of LNP transport through the matrix. This work highlights that even a slightly PEGylated surface depletes the near-contact shell between the LNP and HA chains, which disrupts their adhesive interactions. These protective PEG layers produce a sharp, non-linear enhancement in LNP diffusivities, with just 1% PEG increasing the diffusivity nearly eight-fold relative to bare LNPs, which remain trapped in the matrix structures. This work provides a quantitative estimate of how PEG surface density governs LNP transport through the ECM, which offers predictive guidance for engineering LNP surface properties in target-specific drug delivery.

The High Mobility Group Box 1 (HMGB1) protein performs multiple essential functions in the body, ranging from DNA regulation to the activation and mediation of immune responses. However, HMGB1 has been also implicated in several pathological conditions, such as rheumatoid arthritis, sepsis, autoimmune diseases, tumors, and Alzheimer's disease. As a result, HMGB1 is of increasing interest as a therapeutic target. Binding to heparin has been reported to inhibit HMGB1's pathological activity during sepsis in clinical settings. In this work, we compare the interactions of HMGB1 with heparin and its' synthetic analog linear polyglycerol sulfate (lPGS) from the viewpoint of stability and changes to association behavior. This analysis focuses on thermal stability, secondary-structure changes, and particle-size evolution using nano-differential scanning fluorimetry (nanoDSF), circular dichroism spectroscopy (CD), and dynamic light scattering (DLS).

Far-Red (FR) Light Photoacclimation (FaRLiP) enables cyanobacteria to extend photosynthetic activity into the far-red region by extensively remodelling Photosystem I (PSI), including the replacement of several core subunits with paralogs that coordinate the red-shifted chlorophyll f (Chl f). The binding positions of Chls f are still a matter of debate, with the most recent structural findings supporting the location of a single Chl f molecule within the reaction centre (RC) at the so-called A-1B site. This was in turn suggested to strongly affect electron transfer (ET) directionality leading to an almost monodirectional transfer along the B branch in FR-PSI RC. Here, we directly probe ET in FR-PSI by characterising the photogenerated [P700A1-] spin-correlated radical pair using complementary pulse and Time-Resolved (TR) Electron Paramagnetic Resonance (EPR) spectroscopy at cryogenic temperature. Electron spin-echo decay kinetics are distinctly biexponential, indicating the formation of two charge-separated states. Consistently, out-of-phase ESEEM traces are quantitatively described by two modulation frequencies arising from different dipolar interactions, while TR-EPR spectra are accurately simulated by the combined contributions of [P700A1A-] and [P700A1B-] radical pairs. These results provide direct spectroscopic evidence that both the A and B branches remain photochemically active in FR-PSI. The conservation of bidirectional ET, even when considering the presence of a single Chl f molecule in the RC, further implies that the two radical pairs originate from a common primary electron donor. This finding identifies P700 as the most likely primary donor and argues against a mechanism in which the RC Chl f initiates charge separation.

Lipid nanoparticles (LNPs) are a leading drug delivery platform for mRNA or other nucleic acid-based therapeutics. LNP platforms are typically composed of ionizable aminolipids, phospholipids, sterols, and lipids tagged with polyethylene glycol. The ionizable aminolipids are typically cationic at low pH, allowing them to encapsulate negatively charged mRNA. The pH at which the ionizable head groups change charge states, the apparent pKa, is crucial to understand the characteristics and formulation of LNP. However, this is difficult to measure as the apparent pKa differs from the pKa of the aminolipids in bulk solution due to the complex chemical and charge environment. In this study, we use molecular dynamics (MD) simulations with alchemical free energy perturbation to calculate the pKa shift as a function of lipid composition, treating LNP-like and vesicle-like environments. Our results show that the pH-dependent structure of the systems affects the trends in pKa shifts in complex ways, driven by factors including surface electrostatics and lipid internalization. Our all-atom simulation protocol allows us to efficiently estimate the apparent pKa of LNP-like models formed with novel ionizable aminolipids and estimate how it will change with composition.

The methylation of cytosines at the 5th position (d5mC) is one of the most common epigenetic modifications, and alterations in methylation profile of cells are known to be involved in progression of many diseases including cancer. Increased stability of DNA accompanied by decreased flexibility upon methylation is thought to be a reason behind methylation profiles. The effects of d5mC on DNA stability and structure were investigated via systematic changes in the number and position of d5mCs in DDD. Our results revealed that d5mC substitutions changed DNA conformation and increased the stability only slightly. Next, the effect of DNA methylation on DNA-small molecule interactions was investigated using DDD and fully methylated analogue, DDD8. All the molecules examined (EtBr, Dox, Net and Hoe) had slightly higher affinity to DDD8 compared to DDD. Conversely, their effect, especially Doxs, on DDD structure was more pronounced. Further investigations via MD simulations revealed high selectivity of Dox towards a single intercalation site where the methoxy group of Dox interacts with the methyl group of d5mC and that of two precedent dT to create a highly stable hydrophobic cluster. Hydrophobic cluster formation was not observed upon Dox binding to DDD. Our results rationalize the increased stability of DDD8 over DDD, and open new routes for the design of drugs targeting epigenetic modifications. We suggest, the design of drugs that can engage in hydrophobic interactions with methyl groups in the major groove of a 5-dTdTd5mCdG-3 sequence might lead the way in specific targeting of hypermethylated regions in cancer cells.

1.Surface functionality and pH play a decisive role in governing the structural dynamics, hydration, and drug-binding behaviour of dendrimers. Here, all-atom molecular dynamics (MD) simulations were performed on five generations of PAMAM (G1-G5) and PETIM (G2-G6) dendrimers with O-core and N-core architectures, functionalized with amine, carboxylic acid, or sugar terminal groups under different protonation states. Protonation of the tertiary branch-point amines expands the dendrimer structure, increases internal porosity and hydration, and enhances structural fluctuations across both families. In contrast, non-protonated amine -NH2 (NP) and carboxylic acid -COOH (NP) terminated dendrimers, together with deprotonated carboxylate-COO- (DeP) systems, retain comparatively compact conformations. Sugar-functionalized dendrimers ({beta}-galactose-terminated PETIM and D-glucose-terminated PAMAM) are most hydrated and structurally rigid, whereas amine-terminated dendrimers exhibit the greatest conformational dynamics. PAMAM dendrimers with -NH2, -NH3+, and -COO- terminal groups are generally more hydrated than their PETIM counterparts. However, {beta}-galactose-terminated PETIM dendrimers are more hydrophilic than D-glucose-terminated PAMAM dendrimers. N-core PETIM dendrimers also adopt more compact and spherical conformations than equivalent O-core PETIM dendrimers. Drug-binding MD simulations show that curcumin binding is dominated by van der Waals (vdW) interactions, whereas doxorubicin complexation is primarily driven by electrostatic interactions. Among the investigated surface functionalities, -NH2 (NP), -NH3+ (P), -COOH (NP), and -COO- (DeP) terminations exhibit the most favourable drug-binding characteristics. Except for deprotonated carboxylate systems, curcumin binds more strongly than doxorubicin. Overall, these findings establish molecular-level relationships between surface functionality, protonation state, dendrimer architecture, and drug-binding behaviour, providing design principles for pH-responsive dendrimer nanocarriers with enhanced drug-loading and controlled-release performance. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/742721v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@119bf29org.highwire.dtl.DTLVardef@1554d86org.highwire.dtl.DTLVardef@154a254org.highwire.dtl.DTLVardef@16d5c5b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Photoprotection against excess energy is essential for the survival of photosynthetic organisms under adverse conditions. In plants, excess energy can be dissipated as heat through non-photochemical quenching (NPQ) of chlorophyll fluorescence, involving the trimeric light-harvesting complex II (LHCII), the major antenna of photosystem II. How NPQ affects antenna proteins remains debated, especially as most studies focus on short-lived components artificially induced in vitro. Here, we characterize the effects of qH, a long-lived NPQ component, on the fluorescence properties of natively quenched LHCII. Single-molecule fluorescence measurements, combined with biochemical and biophysical ensemble approaches, reveal a larger and more quenched subpopulation of LHCII trimers exhibiting fluorescence intermittency in samples with qH compared to those without. This behavior is linked to a small conformational change that stabilizes a quenched state, enhancing photoprotection at the antenna level. These findings provide new insights into sustained NPQ and its role in regulating energy dissipation under natural light conditions.

Fluorescent molecular rotors for sensing local microviscosity have become indispensable tools for better understanding the mechanisms of living systems. Current probes relay on intensity or lifetime measurements, while ratiometric molecular rotors are lacking. Here, we introduce a new design concept of molecular rotor using xanthene scaffold with freely rotating 9-aryl group. We studied three rhodamine derivatives, where 2-carboxyphenyl group was replaced with 4-methoxyphenyl, 2-thienyl and 2-benzofuryl. We found that five membered 9-aryl ring provides two major effects. First, free rotation of thienyl derivative, confirmed by theoretical calculations, makes it classical molecular rotor with intensity and lifetime-based response to viscosity. Second, benzofuryl derivative exhibits second emission band in near-infrared region and fluorescence ratiometric response to viscosity. Theoretical calculations suggest that the benzofuryl derivative can attain planar conformation in the excited state, which explains appearance of the NIR emitting band. Both new dyes efficiently target mitochondria, while the 9-benzofuryl derivative enable quantitative ratiometric measurement of viscosity of inner mitochondrial membrane. Ratiometric imaging revealed mitochondria heterogeneity with local viscosity values ranging from 250 to 460 cP. Oxidative stress induced significant rise in the local viscosity in mitochondria in addition to their morphological changes. Overall, we propose a concept that converts bright rhodamine dyes into molecules rotors with a valuable ratiometric response to viscosity, which opens a bunch of potential biological applications.

Nitric oxide (NO) is a key signaling molecule that regulates diverse physiological responses, including adaptation to hypoxia in plants. Although stabilization of group-VII ETHYLENE RESPONSE FACTOR (ERFVII) transcription factors under low O2 is known to be facilitated by the N-dragon pathway, whether NO directly mediates N-terminal cysteine (Cys) oxidation to regulate ERFVII stability remains unresolved. Here, we combined genetic, computational, and structural approaches to investigate NOs role in proteasomal degradation of ERFVII during flooding stress. Arabidopsis mutants with elevated S-Nitrosoglutathione (GSNO) levels compromised ERFVII activation during dark submergence but increased expression of genes encoding N-degron pathway enzymes. Although direct detection of in vivo NO-mediated S-nitrosylated proteins remains technically challenging, the GPS-SNO 1.0 tool predicted the conserved N-terminal second Cys residue as a high-confidence S-nitrosylation site. Structural modeling using the Schrodinger Suite 2024-4 further revealed that conversion of the Cys thiol (Cys-SH) to S-nitrosothiol (Cys-SNO) induced notable conformational changes in ERFVII TFs. Molecular docking further demonstrated that Cys-SNO-modified ERFVII peptides exhibited stronger binding affinities and altered interaction networks with N-degron pathway enzymes, supporting a role for NO-mediated structural remodeling in ERFVII degradation. Elevated GSNO also disrupted energy balance efficiency for overcoming O2 deficiency, altered the expression of sugar starvation-responsive genes, and impaired ATP binding capacity of Cys-SNO ERFVII proteins, as evidenced by docking and molecular dynamics simulations. Collectively, these results support a model in which NO-mediated modification of the conserved N-terminal Cys promotes ERFVII degradation, thereby linking NO signaling to hypoxia-responsive transcriptional regulation and metabolic adaptation during flooding stress.

The aggregation of Tau protein into straight filaments (SFs) and paired helical filaments (PHFs) is central to Alzheimers disease (AD) pathology and a key target for therapeutic inhibition. Graphene quantum dots (GQDs) are biocompatible nanomaterials that have shown promise in inhibiting amyloidogenic protein aggregation across related neurological pathologies. The effect of GQD functionalization on interactions with Tau aggregates (TAs) is poorly understood, though recent evidence suggests that anionic GQDs are effective TA inhibitors. In this study, we survey how GQD functionalization influences binding to SFs and PHFs to guide future development of therapeutic GQDs. We identify binding sites in SFs and PHFs, dock our GQD library to these sites, and perform molecular dynamics simulations on promising complexes, totaling 28 {micro}s of sampling. We discover that anionic GQDs preferentially bind to the positively charged SF large protofilament interface, whereas in PHFs, anionic GQDs have a modest binding preference for the C-shaped curve region. Binding of GQDs at the C-shaped curve in both TAs induces distinct protofilament conformational dynamics resembling a pinching motion to capture the GQD. Together, these binding modes may represent early intermediates of the TA disaggregation mechanism. We find that functional groups capable of possessing a negative charge (e.g., COO-, O-, and S-) produce impressive binding affinities. We propose that enriching these functionalizations during GQD synthesis and preparation, particularly sulfur as it is less studied, may yield more potent TA inhibitors and generalize to other amyloid pathologies with positively charged fibril cores. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/741532v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@78f560org.highwire.dtl.DTLVardef@135834eorg.highwire.dtl.DTLVardef@3f9025org.highwire.dtl.DTLVardef@110ade3_HPS_FORMAT_FIGEXP M_FIG C_FIG

This present work shows that E-hook fragments possess functional structure differences governed by electrostatic interactions and sequence composition. The acidic C-terminal tails of tubulin, known as E-hooks, play a central role in regulating interactions between microtubules and motor proteins, microtubule-associated proteins, and enzymatic modifiers. Despite their functional importance, the intrinsic structural properties of these peptide segments remain poorly characterized due to their intrinsically disordered nature. In this work, we present quantum-mechanically optimized structures of hexamer peptides derived from {beta}-tubulin E-hook sequences. Density functional theory calculations were used to optimize peptide geometries using progressively larger basis sets. From the optimized geometries we calculated theoretical Raman spectra, Ramachandran backbone dihedral distributions, and measured radii of gyration to resolve composition dependent structural tendencies. The combined Raman and conformational analyses provide a systematic computational approach for comparing simulated and experimental Raman spectra of tubulin E-hooks and other intrinsically disordered proteins and offer insight into how E-hooks contribute to the recognition mechanisms underlying the tubulin code.

The rising incidence of invasive fungal diseases emphasizes the need for novel therapeutic strategies, including membrane-targeting antifungal agents, which require representative lipid models for detailed molecular-level studies. In this work, we propose a consensus quinary fungal plasma membrane model based on lipidomic literature data, specifically PC:PE:PI:PA:PS phospholipid model with ratio of 44:29:13:8:6. Using a bottom-up approach, we characterized the biophysical properties of this system - with particular emphasis on mechanical parameters such as bending rigidity and area compressibility - by combining molecular dynamics simulations with experimental flicker-noise and ATR-FTIR spectroscopies. Furthermore, we investigated the effect of two key non-phospholipid components: ergosterol and triacylglycerols. Biophysical analysis revealed that DPPI and its specific interactions with DSPS induced the most substantial deviations in baseline membrane parameters, particularly area per lipid, membrane thickness, and area compressibility, while DSPS influenced bending rigidity change and DLiPA primarily affected lipid packing defects. In addition, ergosterol and TGs were found to influence all of the investigated parameters to different degree. Notably, the overall biophysical profile of the proposed FPMM closely mimicked that of natural vesicles derived from yeast lipid extracts, establishing this model may provide a reliable platform for studying fungal membrane biophysics and lipid-targeting interactions.

Neutron scattering is a powerful technique to investigate atomic structures and molecular dynamics of proteins at the nano-scale. When it comes to dynamics, incoherent and coherent scattering respectively provide information on the single and collective dynamics of nuclei. In proteins, hydrogen has the highest incoherent cross-section, and it is common practice to overlook the contribution of coherent terms stemming from all nuclei. However, the fast collective dynamics of heavier nuclei could also be studied if coherent scattering and incoherent scattering were experimentally separated. The recent advent of polarized neutron spectroscopy with sufficient flux and energy resolution has made it possible, and opens new perspectives to investigate the relative importance of coherent scattering and the information it provides on biological samples. The present study reports on the use of polarized quasi-elastic neutron scattering (QENS) and the application of a minimalistic model adapted to both individual and collective dynamics. Using a perdeuterated green fluorescent protein as a model globular protein, the study provides an interpretation of the dynamical parameters obtained with QENS, and a comparative study of the Elastic Coherent and Incoherent Scattering Factor. Based on both experiments and calculations, we discuss the relative importance of distinct and self components of coherent scattering, which is often wrongly assumed to be representative of collective dynamics only. The results highlight the current impediments rendering complicated a straightforward analysis of fast collective dynamics in hydrated protein samples.

Nanodiscs and bicelles are widely used as membrane mimetics for structural studies of membrane-associated systems. Studies have reported that their magnetic alignment behavior and phase stability are highly sensitive to composition and temperature. In this study, we systematically investigate the effects of cholesterol on bicelle formation and magnetic alignment in DMPC + 0.2 glycyrrhizic acid (GA) systems using a combined 31P and 14N solid-state NMR experimental and simulation-based approach. Temperature dependent 31P NMR spectra reveal a clear transition from vesicle dominant to aligned bicelles/nanodsics phase, while 1N quadrupolar splitting and lineshape analysis provides quantitative insights into heterogeneous lipid bilayer populations, distinguishing large aligned nanodiscs (B(L)), small nanodiscs (B(S)), and isotropic/random components (B(R)). A strong correlation is observed between the 31P derived bicelle fraction and the 14N B(L) population, confirming that macroscopic alignment in the presence of an external magnetic field directly reflects the growth of large, well-ordered nanodiscs. Cholesterol is found to play a critical dual role by modulating membrane order and curvature. At low cholesterol concentration (0 to 5 mole percent), nanodiscs alignment occurs gradually with increasing temperature, while at higher cholesterol concentration (15 to 25 mole percent), the alignment is delayed and accompanied by broader spectral features, indicating structural heterogeneity. Notably, 10 mole percent cholesterol consistently provides the optimal balance, enabling efficient temperature dependent conversion to aligned bicelles while maintaining high B(L) populations (about 70-80 percentage) and minimal isotropic fractions. In contrast, higher cholesterol maintains significant B(S) and B(R) populations, even at elevated temperature. The 14N quadrupolar coupling (Cq is approximately 8.5 to 9.2 kHz for aligned nanodiscs) remains nearly invariant across compositions, showing that cholesterol does not change local headgroup dynamics but instead redistributes lipid populations. These findings establish a combined 31P and 14N solid -state NMR approach provides a valuable platform for quantitatively correlating membrane structure, dynamics, and alignment, offering practical guidelines for optimizing bicelle systems for high resolution solid-state NMR studies of membrane associated biomolecules.