The Journal of Physical Chemistry B

N-linked glycosylation is known to modulate the catalytic function of human carbonic anhydrase (HCA) IX, yet its influence on the underlying free-energy landscape remains largely unexplored. In the present work, we combine extensive all-atom molecular dynamics simulations with kinetic transition network analysis to investigate the effect of glycosylation on the conformational organization of the catalytic domain of HCA IX in both monomeric and dimeric forms. The multidimensional conformational space is discretized into distinct free energy minima using the distribution of reciprocal interatomic distances (DRID), and the effective barriers separating them are estimated using the max flow-min cut formalism. The corresponding free energy landscapes are visualized in terms of disconnectivity graphs, which provide a faithful representation of underlying kinetics. Minimum free energy paths, mean first passage times, as well as frustration metrics are computed to further quantify the effect of glycosylation on landscape topography. Unglycosylated systems are found to exhibit predominantly funnel-like landscapes, with a limited number of metastable states in the vicinity of the native protein fold. In contrast, glycosylation enhances landscape complexity, resulting in a wide array of relaxation timescales. Strikingly, the two glycan chains affect the landscape topography in distinct ways, despite having closely matching sequences. Dimerization couples the glycan chain dynamics, with transitions between key metastable states involving coordinated motions of both the chains. Our work illustrates that interpretation in terms of disconnectivity graphs and transition networks could reveal important insights into the organization of glycoprotein energy landscapes.

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.

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.

Electrostatic interactions often play a role in determining the thermodynamic and kinetic properties of protein-protein interactions. However, the role of long-range electrostatic interactions in intrinsically disordered protein (IDP) binding is less clear, as they often bind in multiple steps including initial formation of a disordered encounter complex, followed by rearrangement into the bound state. We varied the salt concentration to probe the role of long-range electrostatic interactions in the binding of the highly charged AbpSH3 domain and the oppositely charged IDP ArkA. Using isothermal titration calorimetry, we observe that salt enthalpically destabilizes the bound complex. Molecular dynamics and NMR experiments reveal that salt has little effect on the bound state structure. However, simulations show that salt destabilizes the encounter complex intermediate, which primarily affects the association rate as measured by NMR. Consistent with these results, salt has the largest stabilizing effect on the apo SH3 domain, as cations substitute for the transient and long-range electrostatic interactions that can form with ArkA in the complex. We reveal a detailed picture of how a highly charged domain uses long-range, fuzzy, electrostatic interactions to help reach the bound state, a mechanism that is likely common among other highly charged domains that bind IDPs. TOC Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/741257v1_ufig1.gif" ALT="Figure 1000"> View larger version (21K): org.highwire.dtl.DTLVardef@dfc7acorg.highwire.dtl.DTLVardef@1ae0438org.highwire.dtl.DTLVardef@19704adorg.highwire.dtl.DTLVardef@1b40b15_HPS_FORMAT_FIGEXP M_FIG C_FIG

Molecular flexibility governs how molecules behave, reorganize, and respond to their environment. Although experiments measure molar entropy for small molecules and molecular dynamics (MD) simulations capture molecular motions, quantifying configuration entropy and the concerted internal motions such as torsion rotations, angle bending, and their couplings are central to understanding thermodynamic behavior but remains challenging. To dissect these contributions, we used MD trajectories and developed an internal coordinate PC-entropy (iPC-entropy) method to probe the origins of entropy and reveal how specific motions shape the thermodynamic landscape. The studies accurately captured molar entropy, identified key torsional motions as major contributors, and uncovered a critical angle-torsion coupling in which angle bending was strongly correlated with torsional rotation, a coupling that increases nonlinearly with molecular size. Evaluating entropic changes upon protein-ligand binding reveals that dominant entropic penalty arises from ligand dihedral rigidification rather than protein reorganization and highlights the specific dihedral rotations that become restricted. We also suggest systematic corrections for approaches considering solely rotamers to reliably reproduce the relative entropic penalty in computer-aided drug discovery. Together, our findings elucidate the molecular origins of entropy and entropy changes. In addition, we can quantify and illustrate the internal motions that strongly shape binding thermodynamics, thereby offering mechanistic insights to guide drug development.

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.

Umbrella sampling is widely used to estimate biomolecular free energy landscapes and relative folding stabilities. Although equilibration is a critical component of umbrella sampling workflows, the impact of equilibration length on thermodynamic predictions remains poorly understood. Here, we investigate the effect of equilibration length on relative folding free energy predictions for four RNA hairpins with loop sequences GUGAAA, CUGGGA, GUAAUA, and UUAAUU with helical stems of three base pairs. Umbrella sampling simulations were performed using an end-to-end distance reaction coordinate spanning 15-45 [A], where equilibrium simulations (windows) were spaced at roughly 1 [A] intervals. In these calculations, the hairpin stem-loops were allowed to equilibrate in an end-to-end distance window and then the coordinates were transferred to the next larger end-to-end distance window to equilibrate. Two equilibration lengths, 2 ns and 100 ns per window, were followed by 600 ns of production sampling. Potential of mean force (PMF) profiles were reconstructed using the Weighted Histogram Analysis Method (WHAM) and used to calculate pairwise free energy differences with thermodynamic cycles. Increasing the equilibration length produced substantial, sequence-dependent changes in the reconstructed free energy landscapes. The 100 ns protocol generated markedly flatter PMFs for GUGAAA and UUAAUU and pronounced reshaping of the free energy landscape for GUAAUA. These changes were accompanied by reductions in hydrogen-bonding and stacking interactions, particularly within the intermediate regions of the reaction coordinate. The resulting thermodynamic predictions, as free energy change differences, were therefore highly sensitive to equilibration length. Across nearly all hairpin pairs, the 100 ns equilibration yielded substantially larger magnitude free energy change difference values than the corresponding 2 ns equilibration, with differences that greatly exceeded replica-to-replica variability. Comparison with optical melting measurements and nearest-neighbor thermodynamic predictions revealed that 2 ns equilibration times more closely agreed with experimental values than those obtained using 100 ns equilibration. These findings demonstrate that longer equilibration can systematically alter the structural ensembles sampled during umbrella sampling and amplify predicted stability differences without improving agreement with experiment. More widely, our results highlighted equilibration length as a critical and nontrivial parameter in RNA free energy calculations and demonstrate that increased equilibration does not necessarily lead to more accurate thermodynamic predictions.

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 binding affinity of a ligand to a protein is influenced by the protonation and tautomeric states of both partners. However, this relationship remains under-investigated due to the limited availability of computational tools capable of considering all charge and tautomer states in a scalable manner to study clinically relevant systems. Here, we use Multi-Conformation Continuum Electrostatics (MCCE) to calculate the protonation and tautomer distributions of nine kinase domains bound to 18 FDA-approved inhibitors while considering their Boltzmann-ensemble. Our simulations show that protein net charge and proton distribution remain largely stable even upon binding charged inhibitors. Our results find that individual inhibitor charges are dynamic, frequently increasing, or decreasing upon binding a specific protein target. Kinase-inhibitor binding significantly shifts the relative probabilities of low-energy states ({Delta}G < 2.5 kcal/mol), though it does not recruit higher-energy conformers into the bound population. Our consideration of all possible charge states and tautomers enable us to identify when tautomer have significant significant free binding energy differentials (3-6kcal/mol). In turn, we find that minority species can become the dominant component in the bound state, emphasizing the necessity of considering ensemble-wide protonation and tautomer states to accurately predict protein-ligand binding energetics.

Biomolecular condensates are condensed assemblies of biomolecules that form through the process of liquid phase separation. Condensates in biology typically function as membraneless organelles, providing compartmentalization in the absence of a dividing lipid membrane. The molecular make-up of different condensates includes diverse multivalent proteins and nucleic acids as the primary drivers, many of them including significant fractions of intrinsically disordered regions (IDRs). To date, the sequence to phase separation relationship of IDRs has focused largely on one protein at a time, studying single-component condensate formation, or single-component partitioning into condensates. The co-phase separation and mixing of two or more IDRs is considerably more complex as both sequences can vary widely in their self- and cross-interactions, as well as their relative abundance in solution. It is unclear that a rule which predicts how a single sequence behaves will also predict what happens when two sequences are mixed. In this study, we disentangle the influence of sequence from that of composition using a set of 18 LAF-1 RGG variants that keep the same length and amino-acid composition and change only the order of the residues. This lets us vary charge patterning and, to a lesser extent, hydropathy patterning while keeping protein composition fixed. By themselves, the sequences phase separation and single-chain compaction are controlled by their degree of charge and hydropathy patterning. Within single-component condensed phases, each sequence adopts a more extended conformational ensemble, due to a more favorable, selfsolvated environment. We find that mixing two IDRs together into a condensate causes this universal scaling behavior to break, impacted by the relative interactions of the two components and overall composition of the slab. We find two different qualitative behaviors, one characterized by cooperative co-condensation when both sequences are subcritical, and the other by scaffold-client behavior when one sequence is supercritical. The scaffold-client systems generally show a high degree of demixing, while the co-condensing systems are generally quite well-mixed in the dense phase. This is surprising because even in cases where both partners have significantly different patterning parameters, they still mix. Thus, the descriptor that predicts a sequence's behavior alone can help indicate whether it will mix with or separate from a second component, but it does not fully determine the outcome on its own.

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

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.

Monobodies are fibronectin type-III-based binding proteins that specifically bind target proteins and regulate their functions. We previously identified monobodies that selectively recognize either the OPEN or CLOSED conformation of adenylate kinase (Adk), revealing that monobodies can discriminate distinct conformational states of a target protein. However, the molecular basis of OPEN-form recognition has remained unclear because the structure of the complex between an OPEN-form-specific monobody and Adk had not been determined. To address this issue, we determined the crystal structure of the complex between Adk and the OPEN-form-specific monobody OP-4, employing hierarchical clustering analysis of X-ray diffraction datasets. The structure revealed that OP-4 binds to the surface formed by the expanded LID and CORE domains of Adk. Mutations in the interface residues reduced the OP- 4-binding affinity, indicating that the crystallographically identified interface is also relevant in solution. In particular, R123 mutations markedly impaired OP-4 binding. Molecular dynamics simulations further suggested that the R123-D159-R156 hydrogen-bond network is retained in solution and may contribute to efficient complex formation. These findings establish the structural basis for monobody OP-4 binding to open-form Adk and identify the R123-centered interaction network as a key determinant of complex formation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/742914v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@4b529org.highwire.dtl.DTLVardef@1119ffcorg.highwire.dtl.DTLVardef@1e9469org.highwire.dtl.DTLVardef@1a17eaf_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe crystal structure of the OPEN-form adenylate kinase/monobody OP-4 complex was successfully determined. C_LIO_LIThe crystal structure revealed that OP-4 binds to surface formed by the expanded LID and CORE domains in adenylate kinase. C_LIO_LIIsothermal titration calorimetry measurements for adenylate kinase mutants confirmed that the binding modes observed in solution are consistent with those observed in the crystal structure. C_LIO_LIMolecular dynamics simulations suggested that the R123-D159-R156 hydrogen bond network prior to OP-4 binding is important for complex formation. C_LI

Carotenoids are structurally diverse isoprenoid pigments that play central roles in photosynthesis, photoprotection, membrane organization, and cellular signaling. Despite their biological and technological importance, atomistic simulations of carotenoids remain limited by the lack of a transferable force field spanning the chemical diversity of naturally occurring compounds, including glycosylated and acylated derivatives. Here we present CARS (CARotenoidS), a transferable force field for carotenoids that integrates seamlessly with the AMBER family of biomolecular force fields. Parameters were systematically optimized against 22 957 r2SCAN-3c reference energies for 25 representative molecular fragments, yielding an accurate description of polyene conformational energetics, ring rotations, and molecular geometries. Across diverse validation sets, CARS substantially outperforms GAFF2 and provides improved agreement with quantum-chemical reference data for glycosylated and acylated carotenoids. For zeaxanthin, CARS also surpasses OPLS-AA, CGenFF, and previously published carotenoid-specific parameters set in reproducing conformational energetics and structural properties. Two complementary parameter sets are provided: CARS for glycosylated and non-lipidated carotenoids, and CARS+Lipid21 for carotenoids containing saturated or monounsaturated lipid chains. By providing the first unified and transferable parameterization covering the structural diversity of natural carotenoids while remaining fully compatible with established AMBER force fields, CARS removes the need for molecule-specific reparameterization and enables reliable molecular simulations of carotenoids in proteins, membranes, and other complex biological assemblies.

Biophysics is a rapidly advancing field with an incredible breadth of topics. Thus, undergraduate biophysics instructors have to strategize and decide what topics they will cover in their courses. Educational institutions utilize a variety of biophysics textbooks. A common deficiency of each of the existing texts is that it serves well a given set of topics (theory, illustrations, practice problems) and leaves out other areas. A typical example includes good theory and problems for thermodynamics and kinetics while presenting molecular dynamics and various spectroscopic methods in a lacking or outdated way. The authors of this manuscript teach a capstone Biophysical Chemistry three-quarter series (Western Washington University/WWU, Bellingham, WA) which ideally should resonate with the general and major-specific courses the students take within their major at WWU. To achieve this goal and to enrich the traditional lecture-based delivery, the instructors have developed and brought together key pedagogical elements: purpose-built online textbook with a uniform structure of the academic content and practice problems, a study sample (oligopeptide) of biophysical significance with a growing set of experimental and computational data and student-centric in-class activities including computer labs. Our Biophysical series emphasizes concepts and methods of computational structural biology (Molecular Dynamics) and spectroscopic approaches (IR, UV and NMR). Here we describe the details of our integrative approach, summarize key outcomes and chart ways to advance the biophysical chemistry series further. Our textbook can be found through LibreText.

Engulfment and Cell Motility protein 1 (ELMO1) regulates cell migration, phagocytosis, and cytoskeletal remodeling, positioning it as a compelling therapeutic target across kidney diseases, oncology, enteric infections and inflammation. Despite this potential, no approved therapeutics or clinically validated small-molecule modulators of ELMO1 currently exist. ELMO1 functions by forming a complex with DOCK180 (or DOCK2) to activate the small GTPase Rac1, and the recent structural resolution of the ELMO1/DOCK2 complex now provides an opportunity to target this protein-protein interface directly. Here, we present the first investigation into the druggability of the ELMO1/DOCK2 complex and report the initial virtual screening to identify small-molecule inhibitors of this interaction. Molecular dynamics (MD) and free energy level (FEL) studies were carried out to validate the potential of the predicted hits. This work establishes a computational framework for the development of the first generation of ELMO1-targeted therapeutics. In addition to demonstrating the drugability of ELMO1, this work introduces two open-source Python tools for the rapid analysis and visualization of protein-protein interaction and ligand-protein MD trajectories from DESMOND output files. These tools are designed to be broadly accessible, offering practical utility to the wider DESMOND user community.

Directional anisotropy in electron density provides key information about chemical bonding that is not readily accessible from conventional electron-density maps. Here, a model-independent framework is presented for decomposing experimental structure factors into angular components using spherical harmonics. Reciprocal-space projection onto spherical harmonics followed by standard Fourier synthesis yields angularly filtered density maps. The{ell} = 0 component captures the isotropic part of the density, while the{ell} = 1 components resemble px, py and pz-like dipolar functions that highlight directional electronic structure. Applications to high-resolution datasets, including urea, the Gly-Ala dipeptide and a 0.97 [A]{beta}-lactamase structure, reveal chemically interpretable dipolar features associated with carbonyl and amide bonds, N-H interactions and aromatic{pi} systems. Quantitative analysis using bond-centred sampling demonstrates stable dipolar signatures that remain detectable under moderate resolution truncation. These results establish spherical-harmonic angular decomposition as a practical framework for extracting directional electronic information from crystallographic electron-density maps. SynopsisAngular decomposition of experimental structure factors reveals dipolar anisotropy and directional electron-density features that are directly meaningful for chemical interpretation.

G protein-coupled receptors (GPCRs) are important targets for drug discovery because they are the largest and most diverse family of membrane proteins in the human body. As exemplified by {beta}2-adrenergic receptor ({beta}2AR), which is a typical class-A GPCRs, they are prone to denaturation and inactivation after solubilization. Although diverse techniques have been developed, current structural and functional analyses are still limited to proteins with relatively stable and high expression. However, some mutant variants and misfolded proteins involved in diseases have extremely low expression levels and may be difficult to analyze. To overcome these limitations, we established a novel analytical platform for evaluating the ligand-binding ability of full-length {beta}2AR as a model at the single-molecule level without purification and addressing challenges such as membrane proteins with low expression levels and structural instability. This method enables the direct use of unpurified receptors immediately after solubilization and allows us to use only a small amount of sample ([~]10 ng) for observation and to distinguish between specific and nonspecific ligand binding by fitting. Furthermore, we unveiled the physical properties of detergents on the structural stability of solubilized receptors and found that the lateral pressure within detergent micelles affects ligand-binding ability. Detergents that provided a fluid microenvironment were able to maintain ligand-binding ability for several days even after solubilization; conversely, detergents that provided a rigid microenvironment caused the protein to lose its activity earlier. Our method could be a promising tool for the structural and functional analysis of membrane proteins untargeted until now. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/740883v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1ca0ed1org.highwire.dtl.DTLVardef@92e757org.highwire.dtl.DTLVardef@9223edorg.highwire.dtl.DTLVardef@74a100_HPS_FORMAT_FIGEXP M_FIG C_FIG

Biomolecular condensates formed by intrinsically disordered proteins (IDPs) are often described using stickers-and-spacers models, in which specific sticker motifs form reversible crosslinks and spacer regions modulate phase behavior. Recent theory predicts that heterogeneous nonspecific spacer interactions can promote condensation but may also disrupt sticker-mediated organization. Here, we develop an off-lattice coarse-grained stickers-and-spacers polymer model for continuous molecular dynamics simulations and implement it in the GPU-accelerated OpenABC package. The model uses a directional sticker-sticker interaction to encode limited valency through interaction geometry, producing effectively one-to-one sticker binding without explicit bond assignment. Simulations of one-component systems show that sticker affinity and multivalency promote porous, network-like condensates, while nonspecific spacer interactions can also drive phase separation but produce more compact, spacer-dominated dense phases. When both interaction types are present, strong spacer heterogeneity reduces sticker conversion, suppresses sticker mobility, and disrupts the sticker-mediated network. In two-component systems, specific sticker interactions buffer client recruitment into host condensates, while nonspecific spacer interactions produce reservoir-dependent uptake. These results support a tradeoff in which spacer heterogeneity promotes condensation at the cost of condensate organization and compositional robustness, providing a physical rationale for the suppression of promiscuous spacer interactions in low-complexity IDP regions.

Nucleotide modifications of the tRNA anticodon can affect protein translation fidelity and speed. Chemical modifications of the anticodon nucleotide 34 are regulated under cellular stress and associated with several translational defects and pathologies. Here, we investigate how these modifications influence A-site codon recognition interactions and their coupling to the CAR site that lies adjacent to nucleotide 34 in the ribosome. The conserved three-residue CAR interface hydrogen bonds in a sequence-dependent manner to the mRNA +1 codon 3-adjacent to the A-site codon and is implicated in tuning translational speed. The C of CAR is pi-stacked with the nucleotide 34 of the A site tRNA anticodon. The A site and the CAR site influence each others hydrogen bonding and stacking interactions, and these codon-adjacency effects potentially provide a layer of regulation affecting translational fidelity and kinetics. Through molecular dynamics simulations of a subsystem of a translocating ribosome IRES-model, we observed that nucleotide 34 modifications affect the hydrogen bonding and stacking interactions at the A site and CAR site as well as CARs influence on the A site interactions. Integrating these results with gene sequence and ribosome profiling analyses, we propose that nucleotide 34 modifications help modulate CARs sequence-dependent tuning of translation in response to cellular stress. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/740946v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@fb5a2eorg.highwire.dtl.DTLVardef@1dda97eorg.highwire.dtl.DTLVardef@1a29441org.highwire.dtl.DTLVardef@b353f0_HPS_FORMAT_FIGEXP M_FIG C_FIG