Biophysics and Physicobiology

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.

The development of NIR fluorescent dyes with favorable optical properties is of great importance especially for applications within the field of optical imaging. In this study, we report the design, synthesis and photophysical characterization of novel BODIPY-Xanthene hybrid dyes obtained via Knoevenagel condensation between an asymmetrical BODIPY core and the functionalized xanthene aldehydes intermediates. The synthesized dyes ex-hibit absorption (667 nm) and emission bands (720-722 nm) within the NIR region. Detailed UV-Vis and fluo-rescence studies were performed and molar extinction coefficients and stokes shifts also calculated. Moreover, findings highlighting the influence of structural modifications on the optical behavior of the hybrid dyes and their potential utility in optical imaging applications are reported.

It is important to determine whether native state dynamics drive the misfolding and oligomerization of the prion protein, which are important events in prion disease, and how they are modulated by conformational conversion. Native (N) mouse prion protein (moPrP) is known to form small (OS) and large (OL) oligomers rich in {beta}-sheet, and in this study, photoinduced electron transfer-fluorescence correlation spectroscopy (PET-FCS) has been used to characterize intramolecular dynamics within individual monomeric units in both isolated OS and OL, as well as the diffusion properties of the oligomers. It is estimated that OS and OL comprise of about 15 and 55 monomeric units, respectively. Microsecond dynamics at each of the two regions that are the 1-3 and 2-3 interfaces of native protein are distinct in N, OS and OL, although they occur on very similar timescales. Analysis of the evolution of the distribution of diffusion times, determined using the maximum entropy method, indicates heterogeneity in the oligomerization reaction. Analysis of the change in the fluctuations which occur in two different timescales in the native state ensemble shows that they are damped more at the erstwhile 1-3 interface than the erstwhile 2-3 interface. The difference in the extent of damping at the erstwhile 1-3 and 2-3 interfaces can be explained on the basis of the structural changes known to occur across each region. The changes in dynamics occur concurrently in both regions, indicating that the structural changes accompanying conformational conversion also occur simultaneously during the oligomerization of moPrP.

Amyloid {beta}-protein (A{beta}), which is known for its role in Alzheimer's disease (AD), is also involved in several physiological functions. Of the two predominant isoforms, A{beta}40 and A{beta}42, the latter is more aggregation-prone and more active in health and disease. In the brain, A{beta} interacts with free lipids, which may affect its assembly pathways. Here, thioflavin T (ThT) fluorescence spectroscopy is combined with molecular dynamics (MD) to investigate A{beta}40 and A{beta}42 co-assembly with free dimyristoylphosphatidylcholine (DMPC) and DMPC/cholesterol (CHOL) lipids. ThT measurements at several protein-to-lipid (PL) ratios show isoform- and lipid composition-dependent kinetics of A{beta} fibril formation with clear isoform-dependent lipid effects at a PL ratio of 1:5. Early co-assembly stages of six A{beta}40/A{beta}42 with DMPC and DMPC/CHOL lipids at this PL ratio are then examined by MD. MD results indicate that lipids alter the secondary structure more and interact more avidly with A{beta}40 than with A{beta}42. In turn, A{beta}40 increases the planar order of lipid bicelles more than A{beta}42. Unlike A{beta}40, A{beta}42 decreases the nematic order of CHOL. In DMPC/CHOL lipids, A{beta}42 but not A{beta}40 exhibits two A{beta}-lipid interaction modes associated with mutually exclusive A{beta}42-lipid and A{beta}42-A{beta}42 interactions. Our MD findings provide a plausible explanation for an experimentally observed increase in the lag time for A{beta}40 fibril formation in DMPC lipids and even more so in DMPC/CHOL lipids that contrasts with much smaller effects of lipids on A{beta}42 fibril formation and offer additional atomistic-level insights into A{beta} co-assembly with lipids amenable to experimental testing.

Fluorescent proteins (FPs) are the workhorse of modern-day cellular imaging and biosensing. However, rationally predicting and engineering the photophysical properties of FPs remain challenging, as these are governed by complex three-dimensional microenvironments and post-translational modifications. Here, we present a novel surface-mutation-guided engineering strategy combined with iterative rounds of rational mutagenesis to improve key photophysical properties of red fluorescent proteins (RFPs). This approach generated two bright, monomeric RFP variants from the mFruits lineage, mCranberry and mCranberry2, with quantum yields of 85% and 80%, respectively. Strategic incorporation of charged amino acid residues on the protein surface enhanced fluorescence quantum yield without compromising photostability. Comprehensive photophysical characterization and live-cell microscopy demonstrate enhanced performance of these variants and establish their utility as robust probes for fluorescence imaging. However, the exact mechanism of such improvements is subject to further investigation. Collectively, this work introduces a strategy for optimizing fluorescence properties and provides a framework that may be broadly applicable to other pigment-protein systems such as genetically encoded metal-ion indicators and photosynthetic light-harvesting complexes.

Fluorescent base analogues have proven to be valuable probes of RNA structure. Pyrrolocytosine (pC), an analogue of cytosine, exhibits highly environment-sensitive fluorescence within RNA and is strongly quenched in hydrogen-bonded contexts. In this work, we incorporated pC into the aptamer domain of the B. subtilis guanine riboswitch to determine if this quenching mechanism could allow for sensing of RNA-small molecule interactions. We utilized complementary fluorescence spectroscopy methods to under-stand the functional impacts and ligand-sensitivity of pC substitutions distal to and within the binding pocket. We found that pC substitution within a static structural region exhibits the expected ligand-independent fluorescence properties. When placed in the ligand binding pocket, pC exhibits a moderately decreased affinity for the ligands guanine (G) and hypoxanthine (Hx) while maintaining high specificity for G. We found that pC behaves as a turn-off sensor, with distinct changes in fluorescence upon G or Hx binding. These differences are dependent on the number of hydrogen bonds formed with pC and are resolvable in both time-dependent and steady-state fluorescence measurements. Our results show that pC can be used to study RNA-small molecule interactions and can discriminate between similar ligands even when they have identical binding modes.

Finite-bandgap charge-based FET biosensors are known to be insensitive to electronic tunneling noise in the semiconductor and interference from weakly-charged proteins in physiological samples. However, their signal is still corrupted by pH fluctuations and condensing counterions in the bulk electrolyte. Here, we demonstrate that electrolyte noise is screened by the Stern layer beyond the linear Debye-Huckel limit, when the interfacial potential drop is larger than the thermal voltage. Using a fully nonlinear Gouy-Chapman-Stern (GCS) theory, a universal calibration curve is derived and shown to collapse the low-noise FET signals for miRNA, extracellular vesicles (EV), and protein, captured either directly or through silica and magnetic nanoparticle charge reporters, over eleven decades of analyte concentration. The theory involves the dissociation constant KD and a gain parameter {chi}, which represents the competing effects of the reporter charge and buffer Debye screening that must be large to produce the low-noise GCS condition. The limit of detection (LOD) is shown to be KD/{chi}, which can be optimized by varying the probe density, charge reporter, and buffer solution. An optimized hybridization buffer then yields {chi} ~ 22 (LOD ~1 pM) for miRNA detection, and multivalent capture reduces KD by four orders of magnitude for EV detection (relative to protein detection) with {chi} ~ 34 (LOD ~10 fM).

The structural flexibility of RNA is essential for forming ribonucleoprotein (RNP) complexes, which regulate diverse biological processes. This intrinsic property permits RNA to act as a dynamic scaffold along the assembly pathway as it folds into a specific structure for initial recognition by protein and undergoes conformational rearrangements for functional maturation as a complex. Yet, RNA flexibility and RNP multicomponent assembly create significant obstacles for traditional structural methods. To overcome these challenges, we applied recently developed ABEL-FRET spectroscopy to measure tether-free single-molecule Forster resonance energy transfer (smFRET) over extended observation times. Furthermore, ABEL-FRET enables the unique ability for simultaneous measurements of ultrahigh resolution smFRET and hydrodynamic size of individual complexes, which offers distinct advantages for studying dynamic RNA molecules that undergo assembly via sequential binding events. Using ABEL-FRET, we explored how the guide RNA (gRNA) of CRISPR genome editing system folds and modulates its structural flexibility to carry out the roles required for each assembly state from its unbound apo form to the functional Cas9 RNP state for target DNA cleavage. Multi-perspective view of gRNA structure gained by probing its two primary functional domains enabled to capture dramatic changes in gRNA flexibility that are highly dependent on its specific structural domains as well as assembly states. Collectively, our work with ABEL-FRET highlights the intrinsic link between the structural flexibility of RNA and its functionality in RNP assembly.

Transition-metal ion Forster resonance energy transfer (tmFRET) measures short-range distances and conformational changes in proteins, but its distance sensitivity depends on the donor-acceptor pair. Here, we establish the metal-chelating noncanonical amino acid bipyridylalanine (bpyA) as a flexible, genetically encoded acceptor platform whose Forster distance (R0) can be tuned without changing protein labeling. Cu2+, Cu2+ complexed with nitrilotriacetic acid (NTA), and Fe2+ form distinct acceptors at the same bpyA site, allowing distance sensitivity to be adjusted by changing the solution conditions. We incorporated bpyA at two sites in maltose binding protein (MBP) and labeled nearby engineered cysteines with the donor fluorophore BODIPY. The resulting [Cu(bpyA)]2+, [CuNTA(bpyA)]2+, and [Fe(bpyA)]2+ acceptors provided R0 values ranging from 13.9 to 21.2 [A]. Analysis of time-resolved tmFRET data recovered donor-acceptor distance distributions and maltose-dependent changes consistent with structural predictions. At the 237/295 site pair, both copper and iron acceptors resolved the maltose-dependent decrease in distance. At the 309/322 site pair, [Cu(bpyA)]2+ did not appreciably resolve the distance increase, whereas adding NTA shifted R0 toward shorter distances and enabled detection of an increase from 12.1 to 14.4 [A]. These results demonstrate that a single bpyA-labeled protein preparation supports multiple tmFRET acceptors, providing a cysteine-independent acceptor-labeling strategy with adjustable distance sensitivity.

Background: Chronic low-grade inflammation and gut microbiota dysbiosis contribute to metabolic syndrome (MS). Huanglian Wendan Decoction (HLWDD) is a defined multi-herbal formulation used in Chinese medicine, but its effects on gut microbiota-associated metabolism and NLRP3 inflammasome signaling remain unclear. Objective: This study evaluated the pharmacological effects and candidate absorbed bioactive constituents of HLWDD in experimental MS. Methods: A high-fat, high-sugar diet-induced rat model of MS was assessed using metabolic, biochemical, histological, molecular, and multi-omics endpoints. Gut metagenomics, untargeted metabolomics of liver and colonic contents, liver transcriptomics, and UPLC-HRMS/MS analysis of serum-absorbed constituents were integrated with network pharmacology and molecular docking. Baicalin was further evaluated in PA-BSA-treated HepG2 cells. Results: HLWDD ameliorated obesity, dyslipidemia, hepatic steatosis, and systemic inflammation and attenuated NLRP3 inflammasome-related signaling. Multi-omics analysis identified nine shared differential metabolites and a strong positive association between Faecalibacterium and butyrate. Thirty-two serum-absorbed constituents were tentatively identified. Baicalin showed favorable predicted interactions with NLRP3 (-5.82 kcal/mol) and CASP1 (-5.41 kcal/mol) and concentration-dependently suppressed NLRP3 inflammasome-related signaling in HepG2 cells; the highest concentration increased intracellular butyrate. Conclusion: HLWDD ameliorated metabolic and inflammatory abnormalities in experimental MS in association with restoration of gut-liver metabolic homeostasis and attenuation of NLRP3 inflammasome signaling. Baicalin emerged as a candidate absorbed bioactive constituent.

Cardiac amyloidosis is caused by deposits of misfolded proteins in the heart and can lead to heart failure. Histological confirmation typically involves staining tissue sections with Congo red and examining them under polarized light for apple-green birefringence; however, achieving an interpretable, label-free, and observer-independent assessment remains challenging. Here we show that Pearson kurtosis of channel intensities within the amide I window provides an interpretable, fitting-free contrast for cardiac amyloid in unstained human cardiac tissue sections from ten participants imaged by ultrabroadband multiplex coherent anti-Stokes Raman scattering (CARS). In a discovery participant, high-kurtosis regions corresponded with Congo red-positive tissue in two CARS-histology pairs of adjacent sections (descriptive spatial AUCs, 0.79 and 0.73). Across 15 fields from nine additional participants, field-level kurtosis values did not overlap between severe-deposition and Congo red-negative tissue fields. Among the descriptors examined, kurtosis showed the largest standardized participant-level separation. Exploratory multivariate curve resolution yielded a deposit-associated component with aromatic-residue features shared with reagent transthyretin. In one field from the discovery participant, the second harmonic generation (SHG) signal, acquired simultaneously with CARS, showed a broadly inverse spatial pattern relative to the amide I kurtosis map, revealing distinct tissue-architectural contrast. Together, these findings support a potential label-free approach to detecting cardiac amyloid deposits that combines amide I kurtosis derived from broadband CARS with SHG-derived architectural contrast.

Light-gated K+ channelrhodopsins (KCRs) are recognized as an ideal neuronal silencing tool in optogenetics. KCRs contain functionally important residues for a light-driven H+ pump bacteriorhodopsin, but their roles have been unclear. Utilizing electrophysiological methods, we demonstrate that KCRs function as a light-driven H+ pump in the absence of K+. Transport experiments using pH electrodes further elucidated the function of the H+-pump, which operates even in the presence of K+. The hypothesis that the H+ pump exerts a blocking effect on K+ transport in KCRs has been postulated. Furthermore, we ascertained that there was conversion of KCRs from the H+ pump into the H+ channel by light, yet this conversion was never reversed. However, the addition of K+ resulted in the formation of the K+ channel. KCRs exhibit three distinct functional states, H+ pump, H+ channel, and K+ channel. These multifaceted functions are modulated by environmental ions and light.

Phenylketonuria (PKU) is an autosomal recessive disorder caused by PAH gene defects and can cause irreversible neurological damage as early as the fetal period; however, non-invasive prenatal monitoring methods are lacking. In this study, Pah+/- female mice were mated with Pah+/-; male mice and wild-type male mice, respectively. Urine samples were collected longitudinally from pregnant mice at 10 time points during gestation from Day 1 to Day 19. Data-independent acquisition (DIA) quantitative proteomics combined with GO/KEGG analysis, WGCNA, and a dual-strategy LASSO-random forest approach was used to screen candidate biomarkers. The results showed that stable differentially expressed proteins between groups were detectable as early as Day 1, and the differences persisted throughout gestation and exhibited temporal dynamics. Permutation tests indicated that the probability of random generation of the differential protein combination was low (0.04-0.06), suggesting that it was not randomly generated. The intersection of the two strategies yielded five proteins, GINM1, PRG4, LY6A, NTM, and YIPF3, and after including GLO1, a total of six candidate biomarkers were obtained. The candidate proteins had interaction or co-expression associations with 14 proteins involved in PKU mechanisms, with GLO1 serving as a network hub. This study found that the maternal urine proteome can non-invasively reflect the systemic response induced by fetal-origin PKU, providing proof of concept and candidate biomarker resources for non-invasive early-pregnancy screening of PKU.

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.

Carbohydrates are essential molecules involved in a wide range of biological processes. While their structural representation in the Protein Data Bank (PDB) has been hindered due to their highly diverse and flexible nature, advancements on X-ray crystallography and CryoEM are accelerating the obtaining of their experimental structures, which in turn supports improved analyses of their structural properties, such as the role of their non-chair conformations on biological processes. In this context, the current work provides a comprehensive and up to date overview of carbohydrate structures within the PDB through classification, quantification, and characterization of monosaccharides and glycan chains, incorporating Cremer-Pople puckering coordinates to evaluate pyranose conformations. Our findings show that, even with a steep increase in CryoEM structures including more complex oligosaccharides, carbohydrate data remains concentrate dinsmallglycanchains, with a about 4% of non-chair conformation sintopresolution structures. Free energy landscapes for the pyranose ring in the presence and absence of nine different binding proteins, including both enzymes and non-enzymes, reinforce the preferred stability of chairs and the rarity of conformational induction upon binding.

Stimulator of interferon genes (STING) provides an informative model system for developing methods to extract and compare residue-pair fluctuation patterns from molecular dynamics (MD) trajectories. We combined a one-dimensional convolutional autoencoder trained on apo STING with temporal mean pooling, Mahalanobis-distance clustering, and residue-pair similarity networks to compare apo, ligand-bound, and SAVI-associated multi-mutant datasets using 25-dimensional latent descriptors. Networks constructed from clusters capturing state-dependent fluctuation patterns showed lid-dominated organization in the ligand-bound dataset and a1b1-enriched, structurally distributed relationships involving residue 281 in the multi-mutant dataset. These findings identify contrasting residue-pair fluctuation signatures in the analyzed trajectories and provide an interpretable framework for generating hypotheses about ligand-associated and mutation-associated dynamic allostery.

Translation initiation is a critical stage of protein synthesis in prokaryotes, where ribosomes assemble on mRNA to begin decoding genetic information. The interactions between ribosomal RNA (rRNA) and mRNA significantly influence this process, with features like ribosomal binding site (RBS) affecting ribosomal dynamics. However, direct experimental validation of these types of interaction is yet to be provided. In this study, we developed an optimized small sub-unit sequencing (SSU-seq) protocol for Escherichia coli, enabling the detailed examination of ribosomal complexes and subunits dynamics. Unlike Ribo-seq, which primarily maps fully assembled ribosomes, SSU-seq captures both ribosomal subunits and intact ribosomes, offering a comprehensive view of translation initiation and elongation events. By integrating experimental data with predictive models, our study advances the understanding of translation regulation in prokaryotes and underscores the utility of SSU-seq in decoding the complexities of ribosome-mRNA interactions. Our analysis reveals distinct patterns of small subunit distribution across the entire mRNAs with higher density near positions with stronger rRNA-mRNA hybridization. The results may suggest that rRNA-mRNA hybridization positions along the entire transcript facilitate efficient start codon recognition by maintaining proximity between the small subunit and the mRNA.

With its unique spatiotemporal resolution at the single-molecule level, Forster resonance energy transfer (FRET) is a powerful tool for investigating biomolecular conformational dynamics and function. However, early photobleaching remains a key limitation restricting the achievable observation time and therefore the information gain and application range of single-molecule FRET. Here, we establish nanophotonic DyeCycling, which overcomes photobleaching by reversible fluorophore binding and efficient background suppression using zero-mode waveguides. Nanoscale conformational changes are sensitively resolved from milliseconds up to the hour range, enabling robust kinetic analyses at the single-molecule level. As a result, outlier molecules reflecting static heterogeneity and time-dependent kinetics within individual molecules reflecting dynamic heterogeneity are reliably resolved. The versatility of DyeCycling is demonstrated using DNA and protein systems. Altogether, nanophotonic DyeCycling extends smFRET observations beyond the conventional photobleaching limit, revealing previously inaccessible kinetic effects and providing deeper insight into biomolecular systems with multiple states and rates.

The modeling of aroma release in food science is a complex, multidisciplinary field integrating mass transfer theory and principles of physical chemistry. While mechanistic models have long been used to understand volatile release, their practical adoption has been hindered because existing implementations are often private, "in-house" tools that lack reproducibility and extensibility. This paper introduces digimouth, an open-source Python framework designed to provide a unified, modular, and reproducible environment for simulating and fitting aroma release kinetics. A key innovation of digimouth is its handling of events and stages. Events represent discrete, instantaneous changes in the system (such as opening a bottle or swallowing), while stages allow for multi-phase simulations where experimental conditions or physical dynamics change over time. To demonstrate the tool's utility, the authors implemented established in vitro convection models and performed sensitivity analyses on parameters such as air-water partition coefficients and mass transfer coefficients. The package also includes an optimization module based on the least-squares method to fit parameters to experimental data. Validation against real-time data from Proton Transfer Reaction-Time of Flight- Mass Spectrometry (PTR-ToF-MS) shows a satisfactory fit, with an average error of approximately 2%. Ultimately, digimouth facilitates robust model development and hypothesis testing, offering the food science community a collaborative tool to better understand the mechanisms of flavor release.

The perception of flavor during food consumption is a complex process governed by the dynamic release of aroma compounds, which is influenced by the interaction between the food matrix and human physiology. While mechanistic models have been developed to simulate these phenomena, their practical application has often been limited by the lack of flexible software tools capable of integrating diverse food structures and real-time physiological data. This study addresses this gap by incorporating in vivo mechanistic models for both liquid foods and melting solid matrices in a modular Python-based framework: digimouth. The modeling approach treats the oral, pharyngeal, and nasal cavities as a series of interconnected reactors with mass transfer governed by ordinary differential equations (ODEs). These models explicitly integrate key physiological parameters, including salivary flow, bidirectional respiratory airflow, and discrete events such as mastication and swallowing. For solid foods, the framework incorporates additional mechanisms for matrix dissolution, temperature-dependent melting, and dynamic surface area change. The models were validated using experimental data from 30 subjects who consumed aroma solutions and flavored gelatin gummy discs while monitored by PTR-MS (Proton Transfer Reaction - Mass Spectrometry). The simulations successfully reproduced the main kinetic features and release profiles observed experimentally for both types of matrices. Despite some limitations related to the self-reporting of physiological events and the non-inclusion of initial orthonasal mass transfer in the models, the developed software package proved to be a robust and evolutive tool. It offers a foundation for exploring inter-individual variability and the impact of complex food structures on sensory perception.