JACS Au

Rational design of covalent protein-labeling reagents in complex biological environments requires a molecular-level understanding of how the protein microenvironment governs chemical reactivity; yet, such mechanistic details remain inaccessible to experimental methods alone. In living neurons, Ligand-Directed Acyl Imidazole (LDAI) chemistry has been used to label AMPA receptors as a traceless, affinity-based protein labeling method. Although LDAI labeling reagents have been optimized in the lab, the atomic details of their interactions with the protein and the underlying mechanism remain elusive. In this work, we combined Quantum Mechanical (QM) calculations and molecular dynamics (MD) simulations to propose a detailed reaction mechanism for AMPAR labeling by LDAI reagents and to clarify how the protein microenvironment governs reactivity. Although Lys residues are usually protonated at physiological pH and therefore less nucleophilic in water, our QM results show that Lys labeling is energetically more favorable than competing reactions with Ser or water. MD simulations reveal that PFQX ---the LDAI reagent precursor--- binds dynamically to the GluA2 AMPAR as an antagonist, inducing conformational changes that reshape the local environment of the acyl imidazole (AI) warhead, underscoring that ligand identity strongly affects labeling outcomes. We also identified intra and intermolecular hydrogen bond networks that may contribute to further immobilize and pre-organize the LDAI reagent. Moreover, the probe's chemical nature shapes its interactions with the Ligand Binding Domain (LBD), offering a plausible rationale for the previously experimentally observed ligand-dependent fluorescent response. Taken together, our results establish design principles for exploiting the reagent geometry and binding pocket hydrogen-bonding networks for the rational design of LDAI reagents.

Heterochromatin protein 1 (HP1 is an intrinsic component of heterochromatin domains where it is involved in a diverse set of functions including heterochromatin spreading and organization, chromatin compaction and transcriptional silencing. It has been suggested that HP1 functions through a phase separation mechanism, a process that has been observed in vitro in the presence of N-terminal phosphorylation, nucleic acids and nucleosome arrays. HP1 can also interact with numerous binding partners that contain a specific motif called an HP1 access code (HAC). HACs recognize and bind to an interface formed by the chromoshadow (CSD) domains in the HP1 homodimer, the functional form of the protein. It has been shown that some HP1 binding partners can enhance its phase separation ability while others disrupt the process. Here, we focus on the interactions between HP1 and three binding partners, namely the p150 subunit of the chromatin assembly factor 1 (CAF-1), the N-terminal domain of the lamin B receptor (LBR), and the mitotic protein Shugoshin 1 (Sgo1). Using phase separation assays, we show that CAF-1 prevents HP1 phase separation while LBR and Sgo1 enhance it. Binding assays, mutational studies, NMR spectroscopy and computational analysis allow us to dissect the contributions of the HAC motifs, the charge patterns of the binding partner sequences and the role of N-terminal phosphorylation on HP1 in condensate formation. Our results demonstrate that each binding partner uniquely balances these contributions to modulate the properties of HP1, while electrostatic interactions dominate the regulation of phosphorylated HP1. These results suggest that HP1 binding partners play an important role in the modulation of its properties and the regulation of its functions in distinct biological contexts.

NSD2 is a histone methyltransferase that modifies lysine 36 in histone H3 (H3K36), playing a central role in chromatin organization and transcriptional regulation. Oncogenic mutations, such as E1099K and T1150A in NSD2, have been associated with hyperactive methylation, but the molecular mechanisms underlying this gain of function remain poorly understood. In this study, we performed all-atom molecular dynamics simulations on models of NSD2 bound to the nucleosome for the wild type (WT), E1099K, T1150A, and the E1099K/T1150A double mutant. Analysis of MD simulations reveals that the global dynamics of the enzymes remain unaltered upon mutations. The time-lagged independent component analysis (tICA) and Markov state modeling uncovered fundamental differences in free-energy landscapes among the variants. The WT NSD2 exhibited energetically and kinetically unfavorable transitions between the macrostates along with extended enzyme-substrate distances. On the other hand, the mutant systems demonstrate reduced SAM-H3K36 distances with modified energy landscapes that facilitate transitions or favor prolonged occupancy of catalytically competent states. Importantly, the mutations reorganize the network of intramolecular contacts around the catalytic site, SAM-binding pocket, and histone-binding interface, optimizing substance engagement geometry. These findings demonstrate that oncogenic mutations achieve hyperactivity through strategic reorganization of conformational dynamics rather than simple destabilization, balancing local flexibility with global stability to enhance catalytic efficiency. Our results provide mechanistic insights into NSD2 dysregulation in cancer and establish a framework to develop allosteric inhibitors that target the enzymes dynamic landscape.

Protein phosphatase 2A containing the B56{delta} regulatory subunit (PP2A-B56{delta}) is a critical signaling enzyme whose dysregulation is associated with cancer, neurodegenerative disorders, and Jordan's syndrome, a severe intellectual disability disorder caused by mutations in B56{delta}. Unlike other PP2A holoenzymes, PP2A-B56{delta} is regulated through a unique dual autoinhibition mechanism in which the N- and C-arms occlude the catalytic site while a substrate-mimicking short linear motif (SLiM) blocks the substrate-binding pocket. Although disease-associated mutations have been shown to alter enzyme activity, the molecular mechanism underlying activation of PP2A-B56{delta} and the effects of pathogenic mutations remain poorly understood. Here, we combined cryo-electron microscopy (cryo-EM), enhanced-sampling molecular dynamics (MD) simulations, Markov state model (MSM) construction, and transition-state analysis using Transition State identification via Dispersion and vAriational principle Regularized neural networks (TS-DAR) to characterize the conformational landscape of the disease variant E198K. Our cryo-EM analysis identified two distinct structures of E198K: an inactive closed-form with the N/C-arms resolved and an active loose-form in which the N/C-arms become highly flexible and could not be fully resolved. These structures therefore established that activation is governed by conformational changes of the N/C-arms but did not reveal the underlying mechanism. Starting from the inactive closed-form, we generated over 1,600 trajectories with an average length of 1,260 ns combined for E198K and wild-type (WT) PP2A-B56{delta}. TS-DAR identified four metastable states and two major activation pathways connecting inactive and active conformations. We found that activation occurs through progressive loosening of the N/C-arm interface while maintaining the overall holoenzyme architecture, rather than a complete opening of the interface. This mechanism exposes both the catalytic site and substrate-binding pocket. Comparison of E198K and WT revealed that the disease-associated mutation shifts the conformational equilibrium toward active states while leaving the transition-state ensemble largely unchanged. Mechanistically, E198K disrupts a salt-bridge network and weakens interactions between the internal loop and the C-arm that normally stabilize active-site occlusion. The resulting increase in C-arm mobility promotes active-site exposure and explains the elevated catalytic activity of the mutant. Together, these findings establish a previously uncharacterized activation mechanism for PP2A-B56{delta} and provide an atomic-level explanation for how the pathogenic E198K mutation allosterically promotes holoenzyme activation.

CHI3L1 (YKL-40) is a chitinase-like glycoprotein involved in immune regulation, tissue remodeling, and cancer, yet the molecular principles governing its glycan interactions remain incompletely defined. Previous reports suggested that CHI3L1 can bind to chitin oligosaccharides (COS) and glycosaminoglycan (GAG) ligands, however, the molecular basis and binding sites underlying these interactions remain controversial. Here, a combination of biophysical and computational methods is employed to shed light on carbohydrate interactions of the protein and delineate a potential crosstalk between its glycan-binding interfaces. Our results demonstrate that COS and GAGs bind to distinct, non-overlapping sites on CHI3L1. Both ligand classes exhibit a strong dependence of binding affinity on the degree of polymerization. Molecular dynamics simulations, supported by mutational analysis, identify a GAG-binding site centered on residues R144, R145, and K147 and reveal an additional distal interaction site for longer GAG ligands. Biophysical and biochemical assays fail to confirm a previously proposed allo- or orthosteric interaction between both binding sites. However, physiologically relevant protein-protein interactions mediated by the chitin binding site of CHI3L1 are differentially regulated by GAG and COS ligands. COS inhibit binding of galectin-3 to CHI3L1, whereas GAG ligands enhance the affinity between the proteins by ca. 14-fold. Together, these findings establish CHI3L1 as a dual carbohydrate-binding protein with distinct recognition interfaces and reveal a previously unrecognized role for GAGs in modulating CHI3L1-mediated signaling interactions.

Glutathione peroxidase 4 (GPx4) is the primary enzyme reducing lipid hydroperoxides, preventing membrane oxidative damage and protecting against ferroptosis. GPx4 is known to engage with lipid headgroups through electrostatic interactions, positioning the substrate for reduction. This work reveals and characterizes binding of highly anionic phosphoinositides (PIP lipids) by GPx4. PIPs are vital lipids in human cells and are central to many signaling processes, particularly in cytosolic facing membranes. Lipid overlay assays confirm interactions between GPx4 and phosphorylated PIPs, comparable to known anionic lipid binders. Protein NMR describes the interaction between GPx4 and PIPs within micelles. The greatest resonance shifting occurs with trisphosphorylated PIP, suggesting that higher anionic charge leads to greater binding, a known driver of GPx4 substrate recognition. Preferred anionic interactions were also confirmed with titration and crystallographic structure analysis of inositol phosphate 4 (IP4). A headgroup-binding site on GPx4 is revealed to be proximal to the cationic membrane interaction site. In conjunction with molecular simulations, these results show that PIP lipid interactions allow full engagement of GPx4 with the membrane and positions the headgroup to allow the lipid tail to interact with the catalytic site. Understanding whether GPx4 preferentially interacts with PIPs will allow better understanding of the protective function of this essential enzyme and a mechanism that may protect essential lipid signaling pathways from oxidative damage. SignificanceThis study allows a deeper structural and mechanistic understanding of GPx4, the primary enzyme that reduces lipid hydroperoxides and prevents ferroptosis. Gaining an understanding of phosphoinositide binding to GPx4 reveals a mechanism for potential preservation of these important signaling molecules and for ferroptosis protection. Observation of a specific binding site for headgroup engagement reveals a plausible lipid interaction mode and functional mechanism of this important cytoprotective enzyme.

Mucopolysaccharidosis IIIC (Sanfilippo syndrome type C) is a rare lysosomal storage disorder caused by loss-of-function mutations in HGSNAT, which encodes an enzyme involved in heparan sulfate (HS) degradation, leading to impaired HS catabolism, lysosomal accumulation, and progressive neurodegeneration. Because enzyme replacement therapies have limited penetration across the blood-brain barrier, substrate-reduction therapy represents an alternative therapeutic strategy. Here, N-deacetylase/N-sulfotransferase 1 (NDST1), a key enzyme responsible for HS biosynthesis, was investigated as a potential substrate-reduction target. A structure-based computational pipeline was used to identify and evaluate inhibitors targeting the NDST1 sulfotransferase domain. Approximately 4.1 million drug-like compounds and FDA-approved drugs were screened by molecular docking, followed by pharmacokinetic filtering, molecular dynamics simulations, and MM/PBSA binding free energy calculations. In parallel, peptide binders targeting the same site were generated using diffusion-based protein design and evaluated using molecular dynamics and MM/GBSA analysis. Four chemically distinct small-molecule scaffolds and three peptide candidates were identified as stable binders to the NDST1 active site. The lead small-molecule candidate exhibited a predicted binding free energy of -13.36 {+/-} 5.87 kcal mol-1. These provide a focused set of candidates for further investigation and support the feasibility of targeting NDST1 as a substrate-reduction strategy for MPS IIIC.

Chemically similar post-translational modifications can mediate distinct biological functions, but how proteins distinguish between them remains unclear. Sulfotyrosine (sTyr) and phosphotyrosine (pTyr) exemplify this problem because they have similar sizes, local geometries, and electrostatic properties but function in different biological contexts. Here, we used the monoclonal antibody PSG2, which recognizes sTyr independently of the surrounding peptide sequence, to examine how a protein distinguishes these modifications. The crystal structure of PSG2 bound to an sTyr-containing peptide revealed a deep electropositive pocket with no modeled water molecules in direct contact with the sulfate group. Gas-phase density functional theory calculations favored pTyr over sTyr, showing that direct protein-ligand interactions alone are insufficient to explain PSG2 selectivity. Explicit first-shell hydration calculations showed that pTyr has a larger desolvation penalty than sTyr, and accounting for this difference reversed the calculated energetic order. Isothermal titration calorimetry showed favorable enthalpic and entropic contributions to sTyr binding, whereas no detectable heat signal was observed for pTyr. These results show that PSG2 distinguishes sTyr from pTyr through the balance between direct protein-ligand interactions and ligand desolvation.

Influenza A virus continues to impose a major global health and economic burden through seasonal epidemics and occasional pandemics, highlighting the critical need for continued antiviral development. As the latest addition to anti-influenza therapy, baloxavir marboxil (BXM) targets the highly conserved PA N-terminal endonuclease domain (PAN), blocking the cap-snatching process essential for viral transcription initiation. However, the rapid emergence of resistance mutations significantly reduces BXM susceptibility and compromises its clinical efficacy. Understanding the dynamics underlying resistance through computational modeling has been hindered by the complex electronic properties of the bimetallic catalytic center within the PAN active site, posing a challenge for accurate parameterization. Therefore, in this study, we systematically benchmarked metal-parameterization strategies for molecular dynamics (MD) simulations, including non-bonded, bonded, and hybrid models, using wild-type PAN in both apo and drug-bound states. Identification of reliable parameterization schemes enabled MD simulations of five clinically relevant mutants, I38T/F/M, A36V, and E23K, revealing how each reshapes the conformational landscape to modulate drug binding modes. Together, our results provide a path toward modeling complex sites in metalloenzymes and a mechanistic foundation for vulnerabilities in PAN to guide structure-based optimization of next-generation inhibitors. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/731895v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1a9474borg.highwire.dtl.DTLVardef@87b0a7org.highwire.dtl.DTLVardef@5edb9borg.highwire.dtl.DTLVardef@1a3be21_HPS_FORMAT_FIGEXP M_FIG C_FIG

Understanding protein structural dynamics is central to elucidating biological function and guiding therapeutic discovery. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) typically offers peptide-level, and sometimes residue-level, time-dependent insights into protein structure, conformational dynamics and/or ligand binding. Yet, translating HDX-MS data into atomic-resolution insights and deriving mechanistic understanding remains a key challenge. Integrative strategies which utilize HDX-MS to inform computational modeling or simulations, traditionally leverage HDX-MS data with physics-based approaches through the calculation of protection factors models. Here, we developed MInt-HDX, a hybrid physics-based, machine- learning framework trained on differential HDX-MS signatures across 11 protein-ligand systems or 1032 individual peptides, using eXtreme Gradient Boosting (XGBoost) to guide small-molecule ligand docking and pose selection. By leveraging XGBoost-predicted interacting residues with three-dimensional clustering and convex-hull geometric algorithms, MInt-HDX first generates HDX-guided candidate docking sites in 3D for physics-based molecular docking and then, following docking, employs HDX-MS-informed XGBoost filtering and scoring functions for ligand- pose ranking. MInt-HDX was validated across 3 protein-ligand systems, consistently resulting in Ligand-RMSD within 3 [A] of the crystallographic ligand conformation, individual steps of MInt- HDX were optimized and its overall performance was assessed against HDX-MS data quality factors and benchmarked against common physics-based and machine learning based docking approaches. Together, this work highlights how machine learning, informed by HDX-MS and aided by physics-based approaches, can bridge the gap between solution-phase HDX-MS data and structural modeling to accelerate protein-ligand discovery pipelines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/738285v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1f7d1dorg.highwire.dtl.DTLVardef@14f074aorg.highwire.dtl.DTLVardef@167a9b1org.highwire.dtl.DTLVardef@b5c502_HPS_FORMAT_FIGEXP M_FIG C_FIG

Molecular recognition by intrinsically disordered regions (IDRs) is widely thought to involve coupled folding and binding, yet the sequence features that regulate this transition remain underexplored. Here we show that helix 8 (H8), a disordered C-terminal segment of the SCF ubiquitin ligase adaptor Skp1, is intrinsically prevented from forming a stable helix by its own sequence grammar. Using an integrative approach to dissect its conformational dynamics, we find that H8 frequently nucleates helical structure but rarely propagates into a fully formed stable helix, populating instead a shallow metastable basin of helical intermediates. Contrary to conventional models of helix-coil exchange, where nucleation is rate limiting, helix initiation in H8 is readily accessible, while propagation is selectively suppressed by a glutamate-rich acidic patch. This acidic segment acts as a charge-sensitive conformational rheostat that limits helix extension and maintains H8 in a predominantly disordered state. As a result, H8 transiently samples partially helical conformations on the microsecond timescale without committing to a stable fold. We propose that this propagation-limited mechanism preserves conformational flexibility while maintaining recognition competence across a structurally diverse family of F-box binding partners. More broadly, our findings suggest that charged- hydrophobic-charged sequence patterning can encode conditional, context-dependent structure as a general organisational principle in intrinsically disordered proteomes.

Investigating the conformational dynamics of intrinsically disordered proteins (IDPs) is essential to understanding how their structural heterogeneity underlies function and how their dysregulation contributes to diseases. Here, we utilized an MspA nanopore-based approach for studying the conformational dynamics and interactions of IDPs at the single-molecule level. The platform was demonstrated using the intrinsically disordered transactivation domain of tumor suppressor p53 (p53-TAD), one of the important proteins in cancer biology. We showed that MspA can stably capture p53-TAD and resolve up to six distinct current states with frequent interconversions, revealing a rich conformational landscape. The nanopore also detected the effect of a cancer-associated double mutational variant, N29K/N30D. Combining experiments with steered molecular dynamics simulations, we showed that the mutant sampled compact conformational states more frequently than wild type, consistent with previous NMR studies. Importantly, the MspA platform enabled direct monitoring of E3 ligase MDM2 binding to p53-TAD and resolved how this interaction is inhibited by anti-cancer compound epigallocatechin gallate (EGCG). Notably, EGCG stabilizes one of the six states sampled by p53-TAD, providing a mechanistic explanation for its inhibitory effect. Together, these findings demonstrate the promise of the nanopore platform for label-free monitoring of IDP conformational dynamics, modulation, binding and inhibition at single-molecule resolution.

RNA interactions are a key contributor to the formation and disassembly of intracellular protein condensates. Although some proteins utilize specific RNA-binding domains, these processes can also be mediated by charge interactions with intrinsically disordered regions. Due to the dynamic nature of these systems, investigating the underlying specificity and stoichiometry remains challenging. Here, we demonstrate that single-molecule mass measurements with mass photometry can capture RNA-protein interactions in phase-separated protein systems. Using the approach to investigate RNA-mediated phase shifts of tau condensates, we find that increasing the RNA concentration, which promotes phase re-entry, results in RNA-mediated tau multimerization, where each tau monomer binds a linear RNA sequence of approximately 30 nucleotides. Solution NMR and native mass spectrometry confirm the formation of stable complexes between RNA and the basic proline-rich and repeat domains of tau, which have a net charge of -29. Our findings demonstrate that mass photometry can distinguish between charge neutralization, which drives coacervation, and complex formation, which mediates phase re-entry, making it a highly complementary tool for the study of RNA-mediated phase separation.

The non-amyloid-{beta} component (NAC) region of the Parkinson's-associated protein -synuclein plays a key role in its pathogenic aggregation, motivating the development of molecules that target this critical region. Here, we show that a minimal NAC-derived motif, 66VGGAVVT72, can be reprogrammed through backbone engineering to modulate -synuclein aggregation. Backbone thioamide substitution of this peptide enhances its interactions with -synuclein fibrils and accelerates aggregation, whereas N-methylation disrupts {beta}-sheet hydrogen bonding and inhibits fibrillization. Strikingly, combining these modifications yields hybrid peptides that inhibit the fibrillization of full-length -synuclein at sub-stoichiometric concentrations. Consistent with in vitro results, these backbone-modified peptides can also reduce seeded -synuclein aggregation in cells. These results establish that minimal amyloidogenic sequences can be systematically tuned from aggregation promoters to inhibitors through backbone-level perturbations, particularly thioamide incorporation.

Phosphorylation of the CLOCK/BMAL1 complex is a reversible post-translational modification that plays a central role in regulating circadian oscillations; however, its underlying mechanistic basis remains poorly understood. Although biochemical studies have shown that phosphorylation modulates CLOCK/BMAL1 binding to DNA, yet it remains unclear whether these effects are confined to local perturbation or also propagate through allosteric effects. Moreover, the influence of phosphorylation on histone dynamics and transcription factor-nucleosome interactions has not been systematically investigated. Here, we address these questions using atomistic trajectories obtained through backmapping of coarse-grained molecular dynamics simulations based on the recently resolved cryoEM structure of the CLOCK/BMAL1 and nucleosome complex. We investigated three experimentally identified phosphorylation states: CLOCK bHLHS38/42, BMAL1 bHLHS78, and simultaneous phosphorylation of both proteins. Our results demonstrate that phosphorylation regulates CLOCK and BMAL1 asymmetrically. Whereas phosphorylation weakens the interaction of the modified bHLH domain with the E-box, BMAL1 phosphorylation simultaneously enhances DNA engagement by the CLOCK bHLH domain, an effect that persists in the doubly phosphorylated complex and identifies BMAL1 phosphorylation as the dominant regulatory event. Steered pulling simulations further demonstrate that phosphorylation equalizes the mechanical stability of CLOCK and BMAL1 interactions with DNA. Beyond modulating DNA binding, phosphorylation remodels protein histone interactions by altering contacts between the CLOCK PASB domain and histone H3 and between the BMAL1 PASA domain and the H2A/H2B acidic patch, while simultaneously rewiring residue-correlation and allosteric communication networks throughout the heterodimer. Importantly, phosphorylation increases the separation between the CLOCK HI loop and the H31 L1 elbow, supporting a structural model in which phosphorylation acts as a priming event that provides a more permissive environment for CRY1 recruitment to the chromatin-bound CLOCK/BMAL1 complex, thereby facilitating transcriptional repression. Collectively, our findings reveal that phosphorylation regulates the CLOCK/BMAL1 complex through coordinated remodeling of DNA binding, nucleosome interactions, and long-range allosteric communication, providing a mechanistic framework for circadian transcriptional repression and a foundation for the rational design of therapeutics targeting the molecular circadian clock.

Coarse-grained protein force fields enable simulations of biomolecular systems at length and time scales that are difficult to access with atomistic models, but achieving transferability across folded, intrinsically disordered, and multidomain proteins remains challenging. A central difficulty is that one-bead-per-residue models must represent chemically specific residue interactions while also absorbing solvent-mediated and many-body effects into a simplified energy function. Here, we present MOFF2, a transferable coarse-grained protein force field that combines residue-pair-specific interactions with a density-dependent many-body potential. MOFF2 is optimized using a two-stage strategy: bottom-up parameter learning from heterogeneous reference ensembles followed by refinement against experimental conformational observables. The resulting model provides balanced performance across ordered proteins, intrinsically disordered proteins, and multidomain proteins, and predicts condensate saturation-concentration trends for A1-LCD variant systems. Analysis of the learned parameters reveals chemically interpretable interaction patterns and density-dependent effects that explain the models improved transferability. These results demonstrate that combining a generalized coarse-grained energy function with data-driven optimization can produce a practical and interpretable force field for protein conformational and condensate simulations.

Phase separation (PS) of the low-complexity domain (LCD) of TDP-43 is linked to pathogenic aggregates in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP). Here, we show that extensive phosphorylation of the LCD C-terminus redirects its self-assembly. Coarse-grained Monte Carlo simulations predicted that 12 Ser phosphorylations partition the 148-residue LCD into a hydrophobic N-terminal and highly charged C-terminal block, favoring finite-sized micellization over macroscopic PS. In vitro, LCD phosphorylated by casein kinase 1 delta (CK1{delta}; mean of 12 phosphorylations by native mass spectrometry) and phosphomimetic 12D/12DD mutants formed spherical nanoparticles ({approx} 20-50 nm) above a low-micromolar critical micelle concentration, whereas the unphosphorylated LCD underwent reversible PS that matured into fibrils. Increasing ionic strength shifted the mutants toward anisotropic morphologies (worm-like 12D micelles and rigid 12DD nanocylinders). Turbidity assays and confocal imaging directly visualized the absence of PS in the phosphorylated form. Negative-stain and cryo-EM confirmed the spherical micellar architecture for the phosphorylated LCD and 12D/12DD mimics. Our data identify phosphorylation as a molecular switch tuning macrophase separation and fibril formation of TDP-43 LCD, providing a framework for an aggregation-protective role through microphase separation into size-limited micelles. Whether these assemblies are stable or kinetically trapped on pathological timescales remains unclear.

Biomolecular condensates exhibit spontaneous electrochemical microenvironments characterized by asymmetric ion distributions and pH gradients that emerge from protein-sequence-dependent charge regulation. Despite their biological importance, mechanistic understanding of these microenvironments has been constrained by the absence of computationally tractable frameworks capable of treating proton exchange, counterion partitioning, and buffer equilibria on consistent thermodynamic footing. Here, we introduce the buffered Charge-Regulation Monte Carlo (b-CR-MC) framework, which couples grand-canonical exchange of ions and buffer species with explicit charge regulation of titratable residues. By extending the CR-MC ion-merging strategy to multicomponent reservoirs and employing the Restricted Primitive Model, b-CR-MC achieves computational efficiency while maintaining thermodynamic rigor, with quantitative agreement to the more expensive generalized G-RxMC approach. Applied to full-length FUS (net positive) and PGL-3 (net negative) under physiological conditions, the framework reveals sequence-dependent pH gradients: the dense phase of FUS exhibits an alkaline shift, while PGL-3 exhibits an acidic shift, in both cases driving the condensate interior toward the protein's isoelectric point. Slab-geometry simulations further resolve the Donnan potential and continuous ion profiles across the condensate interface, confirming the direction and magnitude of these electrochemical shifts. Additionally, we identify spatially resolved buffer depletion within dense phases, establishing that dynamic charge regulation is a primary determinant rather than a secondary correction to condensate electrochemistry. By establishing a sequence-resolved, thermodynamically consistent computational platform, b-CR-MC enables quantitative prediction of how mutations and post-translational modifications reprogram condensate microenvironments across biological and pathophysiological contexts.

Here, we report the purification and characterization of a haloacid dehalogenase type II (HAD-II) enzyme capable of direct and cell-free enzymatic defluorination by cleaving the resilient C-F bond in perfluorooctanoic acid (PFOA). While conventional remediation strategies rely on energy-intensive chemical/thermal methods, biological alternatives are limited by long whole-microbiome incubations and poorly understood metabolic pathways. We discovered a novel HAD-II enzyme from Achromobacter mucicolens found in PFAS-contaminated lacustrine sediment, providing evidence of real-time microbial adaptation. Within 24-hour incubation, the system released approximately 0.55 ppm fluoride (17% yield) from a 5ppm PFOA (equivalent to maximum fluoride of 3.24 ppm) in recombinant enzyme assays. Structural and phylogenetic analyses reveal that the newly discovered HAD-II belongs to a deeply divergent lineage sharing only 25% sequence identity with the previously characterized Delftia homologue while preserving the core HAD-like catalytic fold. Comparative molecular docking further elucidated this functional divergence, demonstrating that PFOA adopts a productive binding orientation near the conserved catalytic Asp15 within the A. mucicolens active-site pocket, whereas the Delftia counterpart forces non-productive binding outside the catalytic site. Together, our work unveils a previously unrecognized Achromobacter-associated dehalogenase that mediates PFAS defluorination despite severe sequence divergence, offering a critical new paradigm for targeted biological remediation.

Calcium oxalates are naturally occurring minerals, with the monohydrate form CaC2O4xH2O (COM) being the most stable. COM contains two crystallographically different water sites. We investigate the details of water internal dynamics in the high and low temperature phases of COM using 17O central transition solid-state NMR line shapes, as well as laboratory and rotating frame relaxation rates. The measurements were performed either under static or magic angle spinning conditions and in a wide temperature range from 343 to 180 K. The combination of all measurements allows for precise constraints on motional mechanisms, rate constants, and amplitudes of motions. The high temperature phase is dominated by large-angle fluctuations with an amplitude of about 100 degrees, identical in both sites. During the phase transition between 323 to 300 K, these large-angle jumps freeze out in one of the water sites, while remaining active in the other. In the low temperature phase from 280 to 180 K, small-angle fluctuations of 2-8 degrees in amplitude dominate the relaxation. Transverse relaxation rates also point to the existence of a very slow collective rocking motion down to about 220-200 K.