Journal of Molecular Biology

Over the past decade, protein design has evolved from a specialized discipline into a broadly accessible approach for engineering and interrogating biological systems. Despite these advances, protein design continues to be a technically challenging task, often requiring knowledge of programming to be able to use and combine the different software packages. To address this challenge, we have developed Prosculpt, an easy-to-use protein design pipeline. Prosculpt integrates RFdiffusion for backbone generation, ProteinMPNN for sequence design and multiple structure-prediction platforms (AF2, AF3, Colabfold, Boltz2). Candidate designs are evaluated using customizable Rosetta-based scoring protocols. Each project is specified through a single configuration file, enabling users with minimal computational expertise to perform sophisticated protein design tasks without writing code, while also allowing advanced users to access the full capabilities of the underlying programs. Prosculpt supports a wide range of applications, including design of symmetric homo-oligomers, design of binders, motif scaffolding, partial diffusion and fixed-backbone sequence redesign. By combining these capabilities within a single, user-friendly platform, Prosculpt provides a practical entry point to modern protein design for both novice and expert users.

More than two thirds of proteins in the human proteome are predicted to contain intrinsically disordered regions (IDRs), which lack stable folded structure. IDRs are critical for biological regulation and organization, as targets for post-translational modifications, and as mediators of biomolecular condensates. To address the pressing need for better structural models enabling functional insight, we developed AlphaFlex to model fully atomistic conformer ensembles for proteins predicted to have IDRs, modeled in the context of AlphaFold folded domains and an implicit bilayer for transmembrane proteins. The AlphaFlex resource provides conformational ensembles of human proteins from the AlphaFold database with identified IDRs in the Protein Ensemble Database that is mirrored in UniProt. This transformative resource of AlphaFlex ensembles provides physically and biologically relevant full-length models for IDR proteins, including scaffold proteins, those with IDR:folded-domain interactions, regulatory and condensate proteins requiring exposed binding elements, conditionally folding IDRs, and transmembrane proteins containing IDRs.

Nuclear organization is dynamic and originates from the fundamental subunit of chromatin, the nucleosome. Post-translational modification of nucleosomal histones, particularly within intrinsically disordered histone tail regions, provides a dynamic regulatory mechanism of accessibility for chromatin-templated processes. While the epigenomic impacts of lysine acetylation and serine phosphorylation in the histone H3 tail are well-known, how these charge-altering post-translational modifications (PTMs) alter nucleosomal tail conformational dynamics remains incompletely characterized. Given that the functional implications of these PTMs are, at least in part, a consequence of modified nucleosome conformation, systematically cataloging the impact of histone PTMs on nucleosome dynamics provides crucial insight into both baseline cellular activity and epigenetic dysregulation that occurs in disease. Previously, our lab demonstrated that arginine citrullination mimetics lead to regional increases in H3 tail dynamics within nucleosome core particles. Here, we performed nuclear magnetic resonance spin relaxation experiments to investigate the effects of lysine acetylation and serine phosphorylation on H3 tail picosecond-nanosecond (ps-ns) dynamics. Using lysine-to-glutamine and serine-to-glutamate mutations as acetyllysine and phosphoserine mimetics, respectively, we found that these PTMs increase ps-ns conformational dynamics regionally around the PTM site, with a position-dependent effect. Additionally, we show that the type of PTM influences the extent of these increases: in general, the effect of mimetics trends in the order of phosphorylation [&le;] acetylation < citrullination, suggesting a tunable method for altering histone tail dynamics. Taken together, these results illustrate the role of nucleosome conformational dynamics in conveying the effects of epigenomic PTMs, elucidating a mechanism of the histone language.

Protein engineering often relies on separate models for related developability properties, limiting efficiency and transfer across tasks. We present Prot2Prop, a multitask framework based on a frozen ProstT5 encoder with shared and task-specific adapters for joint prediction of six protein properties: material production, solubility, temperature stability, aggregation propensity, expression yield, and folding stability. Across held-out test data, Prot2Prop achieved strong performance on both classification and regression tasks, including AUROC values ranging from 0.86 to 0.98 for classification endpoints and Spearman correlations ranging from 0.73 to 0.86 for regression endpoints. The model achieved particularly strong performance for temperature stability (AUROC = 0.98) and aggregation propensity (Spearman = 0.86). Post-hoc calibration further improved regression accuracy, reducing folding stability MAE from 0.67 to 0.48. These results demonstrate that parameter-efficient multitask adaptation of protein language models can provide accurate and unified prediction of diverse protein developability properties. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/735009v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@d0eea6org.highwire.dtl.DTLVardef@e3f482org.highwire.dtl.DTLVardef@1c98656org.highwire.dtl.DTLVardef@192a93b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Molecular chaperones are known for their role in preventing protein aggregation and assisting proteins in reaching their structurally functional state. DNAJB6, a J-domain protein that partners with Hsp70s and nucleotide exchange factors, is very potent in preventing amyloid formation of proteins with large intrinsically disordered regions (IDRs), including several disease-associated proteins. Complementary to this, we recently demonstrated a role for DNAJB6 in surveilling FG-Nucleoporins (FG-Nups) phase transitions and highlighted its role in nuclear pore complex assembly. We expand on this by showing that this activity of phase state surveillance is directed to several FG-Nups and shared with the closely related DNAJB2 and DNAJB8. We demonstrate that the surveillance mechanism of DNAJB6 is encoded in an unusually highly conserved IDR that promotes the formation of stable, gel-like assemblies of the chaperone itself. These assemblies likely provide a stable environment that can outcompete stable homotypic FG-Nup interactions and instead favors multivalent heterotypic chaperone:FG-Nup interactions. The evolutionary conservation of the DNAJB6-IDR, mutant analyses from both experimental in vitro and in cell data, and multiscale molecular dynamics simulations suggest that the sequence space for encoding stable gel-like assemblies is narrow and optimized to avoid self-aggregation while providing potent anti-amyloidogenic capacity.

Human aquaporins (AQPs) are essential membrane channels, yet their inherent hydrophobicity complicates structural and functional studies. We present the systematic application of the QTY code to human AQPs, integrating it with AlphaFold 3 structure prediction to design and validate that four-representative human AQPs (AQP1, AQP3, AQP4, AQP7) can be converted into water-soluble analogs while maintaining their conformation. This approach features a novel platform for editing challenging membrane proteins. The QTY code was applied to the transmembrane regions of the selected four AQPs. Subsequently, the water-soluble QTY analogs of the four AQPs were predicted using AlphaFold 3. The predicted structures were superposed with CyroEM- or X-ray-determined native structures in PyMOL. Further analyses included root-mean-square deviation (RMSD) calculations, visualization of hydrophobic surface reduction, and inspection of conserved protein-ligand binding ability. After applying the QTY code, sequence changes between native AQPs and their QTY analogs was significant (42.86-48.80%). Nevertheless, their structures superposed well in analyses, with only slight deviations (RMSD < 0.6 [A]). In addition, the surface hydrophobicity of all QTY-edited AQPs was significantly reduced. Importantly, molecular contacts between the cholesterol ligand and protein were largely preserved for both native AQP1 and its QTY analog. Finally, all AlphaFold3-predicted structures for AQPs have high confidence values (pLDDT > 90; pTM ~0.83), supporting the reliability of the predicted structures. The findings demonstrate that membrane protein hydrophobicity can be edited and reduced without compromising fold integrity or functional architecture. Integration of the QTY code with AlphaFold 3 affords a high-throughput platform for designing water-soluble, structurally faithful analogs of challenging membrane proteins. Such a strategy can provide a potent platform for detergent-free biochemical studies and water-soluble analogs for therapeutic monoclonal antibody discoveries, thus advancing research of this pharmacologically important protein family.

Prion diseases are neurodegenerative disorders associated with the structural conversion of the cellular prion protein (PrPc) into its misfolded infectious isoform (PrPSc). Despite substantial efforts, no disease-modifying therapy or cure is currently available. Here, we present an integrated computational-experimental pipeline for the rational design of cyclic peptides targeting PrPc to inhibit its pathogenic conversion. Starting from crystal structures of antibody-bound mouse PrPc, we develop a rational design strategy combined with iterative molecular dynamics simulations and sequence optimization to generate peptides with enhanced binding and structural impact. Three candidates were selected for experimental validation. Our results show that PH1 (49YGPDPSDSYT58, antibody numbering) that binds stably to the &alpha2-&alpha3 interface most effectively reduced PrPSc levels in GT1-7 cells, essentially by inducing allosteric rearrangements that reinforce the intramolecular helical bundle. PL1 (89GQSNTKPYT97) and PL2 (89RQSNTWPYT97) binding the &beta1-&alpha1/&alpha3 junction exerted more modest effects due to the potential competition of the flexible tail to bind at this site. These results establish a mechanistic link between peptide-induced stabilization of PrPc and inhibition of prion propagation and provide a generalizable framework for designing conformational stabilizers of aggregation-prone proteins.

The cryptococcal polysaccharide capsule is a unique eukaryotic virulence factor that is a target for the immune system and the development of therapeutic antibodies. Our understanding of capsular architecture is limited to a few studies suggesting that metal dications play a role. In this work we explore a mechanism of cryptococcal aggregation that depends on calcium phosphate precipitation. We describe the chemical and biophysical properties of calcium interaction with the predominant cryptococcal polysaccharide, glucuronoxylomannan (GXM). We show that cell aggregation is a pH-dependent and occurs in a calcium dose-dependent manner. Furthermore, this cellular aggregation phenomenon as well as interpolymer capsular polysaccharide interactions are unique to calcium dications and do not occur with other mono- or dications as shown by size exclusion chromatography and circular dichroism. Diffusion ordered spectroscopy nuclear magnetic resonance and ab-initio calculations support complexation of calcium with glucuronic acid (GlcA). The ab-initio calculations also suggest that calcium ions can complex up to four GlcA monomers. Not only does calcium act as a scaffold for the cryptococcal capsule, interacting with up to four glucuronic acid residues of GXM, but calcium phosphate treatment of cells reduces the anti-phagocytic properties of the capsule, promoting ingestion by macrophages and altering antibody interactions with the capsule. This work advances our understanding of the cryptococcal capsule, its biophysical properties, by providing a model for the critical role of calcium interactions with capsular polymers of Cryptococcus neoformans including important impacts at the host-cell interface.

Cyclin-dependent kinases (CDKs) control eukaryotic cell-cycle progression by phosphorylating specific substrates with substrate recognition often involving cyclin-specific docking interactions. However, in minimal cell cycle control systems driven by a single cyclin-CDK complex, how docking interactions contribute to the differential timing of substrate phosphorylation remains unclear. Here, we used AlphaFold-Multimer to systematically predict interactions between the fission yeast mitotic cyclin-CDK fusion Cdc13-L-Cdc2 and its known in vivo CDK substrates. We found that many substrates are predicted to interact with the cyclin hydrophobic patch, and have identified a previously uncharacterised docking motif, [FVIPWGLAM](x)xER[LMV] (ERL motif), with features consistent with an atypical RxL motif. We show that ERL motifs can functionally substitute for canonical RxL motifs to promote phosphorylation of a model CDK substrate by Cdc13-Cdc2, while the S-phase cyclin-CDK Cig2-Cdc2 was found to preferentially phosphorylate substrates containing canonical RxL motifs. Finally, we investigated whether Cdc13-L-Cdc2 is predicted to preferentially bind DNA replication substrates over mitotic substrates but found no evidence of differential binding. These results reveal diversity in cyclin-CDK substrate recognition beyond established docking motifs.

Calreticulin mutations in myeloproliferative neoplasms result in the replacement of the C-terminus acidic sequence with a positively charged tail that causes pathological activation of the thrombopoietin. The two canonical variants are Type-1 and Type-2. The remaining are mainly classified as Type-1 or Type-2 like based on the wild type sequence retained. Here, we performed in silico biophysicochemical analyses of 76 CALR exon 9 frameshift variants by their sequence and predicted biophysical properties, complemented by structural modeling of the mutant homodimers. Beyond confirming the Type-1 versus Type-2 distinction, we found that the Type 1-like variants form a continuum of charge architecture along which two reproducible subgroups can be identified, rather than sharply separated classes. This work refines the conventional mechanism-based classification into a charge-resolved framework and provides testable hypotheses linking novel-tail chemistry to receptor activation in CALR-mutant neoplasms and paves the way for improved targeted therapies based on individual mutants characteristics

Solvent accessible surface area (SASA) is widely used to describe protein stability, ligand binding, mutation effects, and protein-protein interfaces. As structural biology workloads expand to predicted-structure collections, trajectories, and large assemblies, SASA tools must combine reproducible calculation with high throughput, low memory use, and workflow-friendly input handling. We present zsasa, a Zig-based SASA engine with command-line and Python interfaces. zsasa implements the established Shrake-Rupley and Lee-Richards algorithms, provides exact f64/f32 modes and an optional bitmask approximation, and supports batch and trajectory workflows, compressed structure inputs, and configurable atom classification including Chemical Component Dictionary (CCD)-based radii for non-standard components. In matched Shrake-Rupley validation on 4,370 Escherichia coli AlphaFold Database structures, exact double-precision zsasa reproduced FreeSASA total SASA values to near numerical identity. In 10-thread batch benchmarks on the E. coli and 23,586-structure human AlphaFold collections, zsasa was 2.94x faster than a FreeSASA batch wrapper in exact f64 mode and up to 9.70x faster in bitmask mode, with roughly 4-8x lower peak memory. Trajectory benchmarks exceeded 1,000 frames/s at tens of megabytes of peak memory, and a 4.5-million-atom PDB stress-test file completed in under five seconds. These results support zsasa as a practical tool for reproducible, low-memory generation of surface-derived structural features at large scale. zsasa is available under the MIT License at https://github.com/N283T/zsasa.

MotivationDesigning multichain protein complexes requires coordinating the folding of component proteins with the formation of their interfaces. The existing methods, however, remain limited in their ability to satisfy these requirements simultaneously, especially for trimeric and tetrameric complexes. As an important practical scenario, designing a binder that bridges two target proteins into a ternary complex requires flexibility in the relative arrangement of the two targets, adding an additional challenge to existing design methods. ResultsWe present ComplexDesign, a hallucination-based approach for multichain protein design. ComplexDesign performs structure-prediction-guided sequence optimization to simultaneously fold each protein chain and form inter-chain interactions that bind them together. To provide the flexibility required to appropriately arrange these target proteins, ComplexDesign introduces a specialized masking mechanism that enables exploration of possible relative arrangements rather than being limited to the predefined ones. Across a comprehensive set of benchmarks with various chain lengths, ComplexDesign outperformed existing methods in the unconditional design of dimers, trimers, and tetramers, achieving a high design success rate exceeding 50%, supporting its capability for multichain complex design. Furthermore, in the case of multi-target binder design, ComplexDesign produced high-confidence, self-consistent ternary complexes for 8 out of 10 target pairs. These results establish ComplexDesign as an effective tool for multichain protein design, with particular utility for designing binders that bridge two target proteins. Availability and implementationThe source code of ComplexDesign will be made publicly available upon publication.

Human LonP1 is an ATP-dependent mitochondrial protease that degrades damaged or redundant proteins. Indiscriminate proteolysis by LonP1 is limited through tight coordination of substrate recognition, unfolding, translocation and catalytic cleavage, yet the role of ATP hydrolysis in these individual steps remains unclear. Here, we show that LonP1 binds substrates and cleaves peptide bonds without ATP hydrolysis, whereas degradation of folded proteins strictly depends on ATP-driven unfolding and translocation. Initial substrate binding opens a closed ADP-bound resting state, enabling nucleotide exchange and stimulating ATPase activity. The opening also increases accessibility of the proteolytic chamber, modestly enhancing peptidase activity. Maximal peptidase activity is observed in a transition-state mimic stabilised by ADP{middle dot}AlF, in which substrate is engaged within the translocation channel. Cryo-EM analysis reveals that in this state the proteolytic active sites are no longer occluded, linking ATP-driven substrate translocation to full proteolytic activation. Together, these findings reveal how LonP1 prevents indiscriminate proteolysis during substrate selection by ensuring that efficient proteolysis occurs only in substrate-translocating states. Model of the conformational landscape and functional cycle of LonP1Schematic overview of LonP1 states and their inter-conversion. State transitions are modulated by substrate, nucleotide occupancy, temperature, and inhibitors. Key distinguishing features include the presence or absence of the lateral gap, nucleotide state, substrate engagement within the A-tunnel, and the handedness of the ATPase (A) domains. Additional indicators include the compactness of the proteolytic (P) domain and the presence of substrate density within the N-terminal (N) domain or at the coiled-coil domain (CCD) as well as the position of a loop within the catalytic centre. The depicted cryo-EM structures represent a model of a continuous conformational landscape and correspond to the closest matching biological states and positions within the reaction cycle, but may also capture transient intermediates or conformations stabilised by experimental conditions. The shown atomic models correspond to the states highlighted in larger font (R-state: PDB 7NGL; P1-state: PDB 7NFY; P2-state: PDB 7NGC; closed LonP1-ADP-substrate: PDB 9CC1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/733973v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@16e0491org.highwire.dtl.DTLVardef@1ee02b1org.highwire.dtl.DTLVardef@f2b47aorg.highwire.dtl.DTLVardef@26f6b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Tropomyosins are coiled-coil dimers that polymerize head-to-tail along actin filaments. They stabilize distinct filament populations and regulate the access of myosins and actin-binding proteins in both muscle and non-muscle contexts. Despite their central regulatory role, how filament length and isoform identity of different tropomyosin homologues might modulate actin affinity is not completely understood, especially across species. Here, we present a stepwise computational docking pipeline combining AlphaFold2-Multimer coiled-coil models, experimentally informed residue-level restraints, and pseudo-energy analysis via PPCheck to build and evaluate actin-tropomyosin co-polymer models for three isoforms: human TPM1 (hTPM1; 284 residues), human TPM4 (hTPM4; 248 residues), and Schizosaccharomyces pombe Cdc8 (SpCdc8; 161 residues). Interface energetics reveal a consistent hierarchy in which the shortest filament, SpCdc8, achieves the most stabilizing and residue-rich actin contacts, consistent with reduced cumulative geometric penalty along the actin helix. Among human isoforms, hTPM1 forms stronger interfaces with actin than hTPM4. The hTPM1-actin model also exhibits higher contact density and additional energetic hotspots, in agreement with the experimentally established slower exchange kinetics of TPM1 isoforms on actin filaments relative to TPM4. Hotspot mapping identifies conserved acidic residues at equivalent positions across all three isoforms, emphasizing the importance of electrostatic anchor points in maintaining interface integrity across diverse evolutionary contexts. Modeling of four temperature-sensitive SpCdc8 mutations (A18T, R21H, E31K and E129K) reveals that these substitutions substantially destabilize the coiled-coil dimer without significantly affecting actin interactions, suggesting that subtle regulatory failure arises from compromised longitudinal cable continuity rather than from direct loss of actin affinity. Taken together, our results support a hierarchical model of tropomyosin dimer stability, actin-tropomyosin recognition in which filament length imposes a geometric baseline on interface stability, onto which isoform-specific sequence evolution superimposes functional tuning. The tropomyosin homologues we studied appear to retain conserved electrostatic hotspots thereby providing a common structural scaffold across tissues and organisms.

The inhibitor of {kappa}B kinase (IKK) complex integrates diverse cellular inflammatory responses, and induces transcription factor NF-{kappa}B. The molecular mechanism by which IKK becomes catalytically active in response to signaling remains unclear despite structural knowledge of the individual IKK1/, IKK2/{beta}, and NEMO/IKK{gamma} protein components within its hetero-oligomeric assembly. Cryo-EM of the IKK2/{beta} homodimer bound to an associating NEMO/IKK{gamma} protein fragment, reveals multiple conformers. Mutual exclusivity of dimeric conformers, canonical versus alternate, is reflected in and dependent upon order-to-disorder transition of the canonical 6-helical bundle dimerization interface. Correlation of this unusual structural plasticity of IKK2/{beta} with its biochemical and cellular activities suggests mechanistic possibilities for how association with its partner scaffold protein NEMO/IKK{gamma} and polyubiquitin chains might dictate catalytic activation of IKK through distinct IKK2/{beta} conformers.

Computational predictors of protein-binding sites within intrinsically disordered regions (IDRs) show highly inconsistent performance across high-quality benchmark datasets. To understand the origins of these discrepancies, we systematically compared predictors across three independent test sets: two CAID datasets updated with the latest DisProt annotations and a composite dataset (DBs) assembled from DIBS, FuzDB, IDEAL, and MFIB. Predictors trained predominantly on DisProt data achieved substantially higher AUCs on the CAID sets but performed poorly on the DBs. In contrast, predictors trained on older, low-quality PDB-based datasets showed balanced performance across all sets, with a slight preference for DBs. Predictors with mixed training exposure displayed intermediate behavior. Through controlled experiments using identical CNN architectures and feature analysis, we demonstrate that the dominant factor driving these performance differences is the intrinsic disorder propensity of the binding sites themselves. Binding residues in DisProt-based datasets exhibit markedly higher average disorder propensity scores than those in PDB-derived datasets. This previously unrecognized selection bias -- literature studies preferentially characterizing more disordered binding sites, while PDB-derived annotations capture less disordered ones -- effectively splits IDR-protein binding sites into two distinct categories. Predictors optimized on one category therefore generalize poorly to the other. Binding-site length and sequence conservation play only minor or negligible roles in explaining the observed inconsistencies. These findings highlight a critical limitation in current benchmarking practices and training strategies for IDR-binding site prediction, underscoring the need for more balanced and disorder-aware reference datasets. Finally, the diagnostic techniques introduced here could prove valuable beyond the specific application examined in this study.

The unique solvent milieu found in biomolecular condensates can control cellular enzymatic reactions and shift reaction kinetics by modulating reactant concentrations, structural dynamics, and enzyme activities. Here we explore the interplay of multiple regulatory factors within a condensate to control poly(A) RNA deadenylation, the first and rate-limiting step in mRNA turnover. The deadenylase CNOT7, a subunit of the CCR4-NOT deadenylation complex, localizes to cytoplasmic RNA granules and shows increased degradation activity in vitro in condensates formed by the C-terminal low complexity disordered region of CAPRIN1, a component of RNA granules. We use a combination of enzymatic assays, kinetic modeling, microscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, and molecular dynamics simulations to deconvolute and define the components that underlie this enhancement. We found that enzyme and RNA are concentrated in condensates relative to buffer, which increases CNOT7 activity, while the equilibrium between CNOT7's active and inactive states remains unchanged. The concentration-dependent increase in enzymatic rates is counterbalanced by a substantial decrease in the enzyme's catalytic efficiency, likely due to slower diffusion of CNOT7 and RNA within the condensates, which lessens the probability of enzyme-substrate complex formation. Molecular dynamics simulations reveal CNOT7-CAPRIN1 interactions that rely on conserved CAPRIN1 sequence features, hinting at an evolutionarily conserved role for CAPRIN1 condensation. With this quantitative kinetic analysis, we describe the multifaceted mechanism behind regulation of CNOT7 deadenylation by a condensate environment.

Peroxiredoxin 2 (Prdx2) mediates redox signaling by transferring oxidative equivalents to target proteins such as STAT3, a redox-sensitive transcription factor implicated in inflammation and cancer. Although this interaction has been demonstrated in cells, reconstituting the Prdx2:STAT3 complex in vitro remains challenging due to its transient and redox-dependent nature. Here we test various conditions to stabilize the complex between taggless Prdx2 and the core fragment of STAT3 (CF-STAT3), including oxidants, detergents, the facilitator Annexin A2, anaerobic environments, and CovalX crosslinking. Complex formation was assessed via mass photometry, analytical size-exclusion chromatography (SEC), SEC-MALS, and electron microscopy (EM). No stable complex was observed under standard conditions. Anaerobic environments briefly stabilized the interaction, but cryo-EM could not resolve the structure. CovalX crosslinking yielded short-lived but homogeneous complexes. We found that Prdx2 is highly susceptible to hyperoxidation at its peroxidatic cysteine, particularly in the presence of DTT or excess H2O2, resulting in loss of function. Maintaining non-reducing conditions during purification preserved Prdx2 in an oxidation-competent state, promoting formation of the disulfide bond between the peroxidatic and resolving cysteines and thereby enabling reproducible detection of a weak complex with CF-STAT3. Our findings establish a framework for studying redox-relay protein complexes in vitro and highlight the importance of oxidation state management during protein handling.

Small-angle X-ray or neutron scattering (SAXS/SANS) analysis of large unilamellar vesicles (LUVs) is often limited by high-dimensional bilayer models and the lack of dedicated, statistically rigorous workflows. Here, we introduce SAS_MoCa, an open-source Python package that integrates a compositional scattering density profile (SDP) description of lipid bilayers with a separated form factor (SFF) treatment of vesicle size and polydispersity, and couples these highly parameterized models to an adaptive thermodynamic simulated annealing algorithm formulated within a constrained Bayesian framework. SAS_MoCa enables users to incorporate quantitative prior information from, e.g., previous SAXS/SANS studies, dynamic light scattering, NMR, or molecular simulations, and returns full posterior parameter distributions, uncertainties (reported as medians and median absolute deviations) and correlations even from single SAXS curves. Validation on POPC, POPE and DMPC SAXS-only data demonstrates that the method yields reproducible structural parameters with uncertainties comparable to joint SAXS/contrast-variation SANS analyses. The modular architecture of SAS_MoCa facilitates extension to additional lipid systems and future joint SAXS/SANS or SANS-only applications.

Human RNA Polymerase II (Pol II) is characterized by a dense layer of over 775 post-translational modifications (PTMs) that form a dynamic, rewritable regulatory architecture integrating large numbers of cellular signals to coordinate transcription initiation, elongation, termination, and co-transcriptional RNA processing. While genomic information has been extensively catalogued, the potential information capacity associated with Pol II PTM patterns has remained largely unquantified. Here, we analyze the PTM sites across the human Pol II complex (Rpb1-Rpb12) and estimate the state-space information capacity using Shannon entropy theory. We first provide a theoretical upper bound of ~707.98 bits per Pol II molecule (~88.50 bytes) corresponding to ~5.68 x 107 bits per nucleus (~7.10 MB), assuming ~80,200 Pol II molecules per cell. We distinguish this maximal capacity from a conservative, kinetically addressable estimate of ~114.88 bits per molecule (~1.15 MB per nucleus), reflecting physiological kinetic constraints and site coupling that restrict the simultaneously addressable PTM state space in vivo. Finally, we show that major PTM classes (phosphorylation, proline isomerization, O-GlcNAcylation and ubiquitination) operate over distinct lifetimes, from seconds to minutes and hours-scale processes, supporting a multi-timescale biochemical architecture of this enzyme. Together, these results provide a quantitative information framework that distinguishes maximal PTM state-space capacity from kinetically addressable physiological regulatory capacity, supporting a view of Pol II PTM patterning as a high-dimensional, dynamically reconfigurable, multi-timescale regulatory information layer. HighlightsA systems-level framework quantifies regulatory information in Pol II PTMs Known PTM modification sites provide 707.98 bits per Pol II as a regulatory upper bound Physiological kinetic constraints reduce accessible regulatory capacity to 114.88 bits Distinct PTM modification classes define fast, intermediate, and slow regulatory layers Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/734958v1_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@1cd7a8aorg.highwire.dtl.DTLVardef@128387forg.highwire.dtl.DTLVardef@1952adaorg.highwire.dtl.DTLVardef@307b22_HPS_FORMAT_FIGEXP M_FIG C_FIG