Protein folding and unfolding remain central problems in biological sciences, yet a unified understanding of native folding mechanisms is still lacking due to structural diversity and complex folding pathways. In this work, molecular dynamics simulations were employed to investigate the high-temperature unfolding behavior of a helical protein. The results reveal that unfolding is initiated preferentially in regions characterized by weaker residue-residue interactions, thereby predefining the unfolding pathway at the molecular level. Comparative simulations further demonstrate that confinement within a silicon nitride nanopore significantly accelerates protein unfolding through electrostatic interactions with the pore surface, while simultaneously suppressing refolding. Beyond confinement effects, the chemical environment of the solution plays a decisive regulatory role. Monovalent cations with small hydration shells facilitate unfolding, whereas high electrolyte concentrations or multivalent ions enhance conformational stability via electrostatic screening. With respect to chemical denaturants, urea promotes unfolding in a monotonic manner, while guanidine hydrochloride exhibits a dual effect, accelerating unfolding at moderate concentrations but stabilizing protein conformations at high concentrations due to dominant screening effects. Overall, this study provides a microscopic picture of how temperature, spatial confinement, and solution chemistry cooperatively regulate protein conformational dynamics, offering new insights into the physical basis of protein folding and stability.
The N-terminal domain of anthrax lethal factor (LFN) comprises the first 263 amino acids of lethal factor and is required for binding to oligomeric protective antigen (PA) and subsequent translocation into the host cell cytosol. During entry, LFN must completely unfold to traverse the narrow PA pore φ-clamp and refold in the cytosol to elicit toxicity. Despite containing six proline residues, including one (Pro166) in the native cis conformation, we demonstrate that LFN refolds rapidly from an equilibrium denatured state, independent of slow proline isomerization. Equilibrium urea denaturation experiments monitored by tyrosine fluorescence and circular dichroism at pH 8 and 20 °C revealed reversible two-state unfolding with a conformational stability (ΔG°H2O) of ∼4 kcal/mol. Stopped-flow kinetic studies showed single-phase refolding/unfolding at pH 8, completing in less than 1 s. Chevron analysis exhibited rollover in the unfolding and refolding arms that, when fitted to a two-state mechanism with a broad transition barrier, gave a ΔG° of ∼ 4-5 kcal/mol, consistent with equilibrium results. The lower ΔG° was not due to folding/unfolding to an intermediate state or partial structure, as 15N-HSQC results show complete unfolding at 4 M urea. At pH 5, we observe two phases, a fast phase and a slow phase with activation energies of 11.4 and 18.1 kcal/mol, respectively. Chevron analysis at pH 5 is consistent with the four-state model (U ↔ J ↔ I ↔ N) described by Krantz, with the slow phase we ascribe to slow coupling of subdomains rather than proline isomerization. Our results suggest that the PA-binding domain of LF is optimized for swift refolding upon cytosolic entry, potentially bypassing the need for host chaperones or prolyl isomerases.
Membraneless compartments formed by liquid-liquid phase separation (LLPS) regulate biochemical reactions and play a key role in both physiological and pathological processes, including viral replication. In retroviral systems, the extent of genome folding is critical for the efficient packaging of new viral particles, a process mediated by the nucleocapsid (NC) protein that chaperones RNA folding and assembly. Here, we sought to elucidate how nucleic-acid folding and structural folding influence LLPS and whether an HIV NC-derived peptide (HNP) can modulate this process through chaperone-like activity. To this end, we designed a programmable single-stranded DNA (ssDNA) library spanning varying degrees of folding and palindromic architectures, enabling systematic investigation of how nanoscale structural order governs coacervation. Using circular dichroism, FRET, SAXS, and coarse-grained simulations, we correlate DNA conformations with phase behavior and emergent condensate material properties. We find that interactions with HNP promote DNA folding and that increasing DNA order suppresses LLPS, whereas structural disorder and palindromic linkers that induce DNA dimerization enhance phase separation by facilitating multivalent interactions and in turn increasing condensate viscosity. Together, these findings identify two programmable determinants, local structural order and palindromic dimerization, that govern DNA/peptide condensate behavior, offering mechanistic insight into viral genome organization and guiding principles for tuning the physicochemical and material properties of synthetic condensates.
Oxidation of cysteine thiols to sulfonate groups (-SO3-) by reactive oxygen species can regulate protein function. Near the end of inflammation, this modification in the extracellular HMGB1 protein abolishes its proinflammatory activity. Using NMR spectroscopy, we investigated how thiol-to-sulfonate oxidation switches HMGB1's function. Our data show that the oxidation of cysteine 106 (C106) induces unfolding of the HMGB1 B-box domain. In contrast, other chemical modifications, such as S-glutathionylation, at the same cysteine did not have this effect, highlighting the unique impact of thiol-to-sulfonate oxidation. Employing 13C direct-detected NMR, we characterized the oxidized B-box domain. NMR data confirmed global unfolding but revealed residual α-helical propensity near the second and third helices. NMR paramagnetic relaxation enhancement data revealed electrostatic impacts of the C106 thiol-to-sulfonate oxidation. To test whether unfolding is driven by negative charge in a hydrophobic environment, we analyzed the C106D variant, as aspartate electrostatically mimics cysteine sulfonate. However, the C106D variant remained folded, even though NMR confirmed a negative charge at D106. Further NMR experiments showed that the -SO3- group at residue 106 drastically slows down the protein folding kinetics, compared with the -COO- group at the same position, suggesting that -SO3- introduces a large desolvation penalty for protein folding. This study illuminates protein unfolding via thiol-to-sulfonate oxidation of a cysteine residue in a hydrophobic environment as a mechanism for protein functional switching. Since HMGB1 is a therapeutic target for inflammatory diseases, understanding this inactivation mechanism offers insight for designing covalent inhibitors.
Soft radially contracting actuators, inspired by biological circular muscles, enable diverse robotic functions, including manipulation, gut simulation, locomotion, and haptics. The combination of electrohydraulic actuation with radially contracting actuators holds promise for the development of high-performance radial contraction in a compact form factor. In this paper, we introduce an electrohydraulic folding ring actuator (EFRA) that utilizes folding motion to actively close its inner lumen. The EFRA is lightweight (∼25.9 g) and compact, consisting of a triangular ring with sides of ∼65 mm. Under 7 kV actuation, the EFRA achieves a high contraction ratio of 0.89 sustained over 5 s of actuation. This performance is enabled by the multiple synchronously bending segments in the folding mechanism, which enhances radial contraction compared with prior electrohydraulic radially contracting actuator designs. The EFRA also produces ∼0.96 N of inward-directed force measured at a single inner vertex under 7 kV actuation, yielding high force output relative to its low mass. Finally, we demonstrate the advantages of the high performance and compact nature of the EFRA in multiple applications, including robotic manipulation, locomotion, as well as an artificial robotic sphincter.
Biologically functional RNAs operate near marginal stability, and their rugged free-energy landscapes and profound structural dynamics - typically not captured by structural biology experiments - play decisive roles. Atomistic molecular dynamics (MD) simulations provide a unique means to characterize these features. However, the applicability of atomistic MD is currently limited by accessible simulation time scales and, most importantly, by force-field (FF) accuracy. Folding free energies (ΔG°fold) of small RNA motifs represent well-defined targets for quantitative benchmarking of RNA FFs. In practice, however, obtaining thermodynamic estimates that are sufficiently robust for direct comparison with experimental data remains highly challenging, even for small RNA systems, and many published studies rely on sampling that is not fully converged. Here, we systematically assess the performance of widely used advanced enhanced sampling techniques using the 8-mer r(gcGAGAgc) tetraloop as a representative benchmark system. We test temperature replica exchange (T-REMD), two solute-tempering variants of replica exchange (REST2 and REHT), as well as well-tempered metadynamics and on-the-fly probability enhanced sampling combined with solute tempering (ST-MetaD and ST-OPES). Among the tested approaches, T-REMD proves to be the most robust, yielding reproducible folding equilibria and consistent estimates of ΔG°fold after approximately 20 μs of simulation time, independent of the initial folded or unfolded conformational ensemble. Our results provide practical guidelines for selecting sampling protocols suitable for quantitative RNA benchmarks and lay the foundation for systematic validation and future refinement of RNA FFs.
Proteins fold through dynamic intermediates that dictate their routes to functional structures, with ensembles predominantly displaying heterogeneity across nanosecond-to-microsecond timescales. Directly observing these states in solution remains challenging as single-molecule methods often require technically demanding microfluidics, surface attachment that alters behavior, or denaturants that distort natural energy landscapes. Here we introduce NEXT-FRET, a solution-based single-molecule platform combining single-molecule FRET (smFRET) with time-varying Gaussian mixture modeling to resolve how diffusing proteins populate and interconvert between conformations under near-native conditions. By incorporating prior equilibrium information into time-dependent analysis, NEXT-FRET requires a few molecules per condition and accessible instrumentation, enabling application in the presence of chaperones and aggregation-prone precursors. We apply NEXT-FRET to the Escherichia coli Maltose-Binding Protein (MBP) and pre-MBP to reveal a long-sought closed on-pathway intermediate that exchanges with both native and unfolded states. The signal peptide raises the barrier selectively for the intermediate-to-native transition. Profiling interactions with chaperones shows that each stabilizes nonnative conformations distinctively, generating kinetic traps. These findings demonstrate that sequence features and proteostasis factors actively reshape the folding landscape. By following molecules out of equilibrium, NEXT-FRET reveals intermediates invisible at equilibrium. This reflects the inherent nonequilibrium character of cells, which maintain order through ongoing energy exchange and dissipation, with fluctuations governing the kinetics and connectivity of biomolecular states. By exposing transient intermediates and quantifying kinetic flows, NEXT-FRET offers a scalable strategy to interrogate nonequilibrium dynamics, providing mechanistic insights into protein (mis)folding, enzyme catalysis, ligand binding and broader biomolecular reactions with implications for biotechnology and therapeutics.
The spontaneous transition from α-helix to β-sheet in proteins is a transformative structural event essential for diverse biological functions, yet its dysregulation is a hallmark of protein misfolding diseases. Controlling this transition with molecular precision remains a significant challenge in chemical biology. Here, we report the development of lysine-targeted small hydrophobic chemical constructs (HCCs) designed to bypass native folding pathways and induce α-to-β structural remodeling across a spectrum of model proteins. Through a screening of four HCCs, we identified an activated N,N-dimethyl leucine derivative as a potent, dose-dependent inducer of this conformational switch. Using ion mobility-mass spectrometry and Fourier transform infrared spectroscopy, we demonstrate that these chemical modifications effectively recapitulate the transition from helical architectures to β-sheet-rich assemblies. Beyond structural remodeling, we show that this chemically induced transition drives significant functional shifts, including the precise modulation of cytochrome c catalytic activity and the regulation of amyloidogenic aggregation in lysozyme. Our findings establish HCCs as a versatile platform for interrogating protein conformational landscapes and provide a synthetic strategy to manipulate protein topology. This approach opens new avenues for protein engineering and offers deep insights into the fundamental principles governing protein homeostasis and the molecular basis of proteotoxicity.
During the third trimester, the cerebral cortex undergoes rapid surface expansion and folding, processes disrupted by preterm birth and associated with later cognitive problems. Although atypical cortical folding has been observed early in extremely preterm children, it remains unclear which alterations persist into mid-childhood and how they relate to cognition. Cognitive outcomes are heterogeneous but it remains unclear whether children with cognitive problems show distinct structural network-level organisation. We compared cortical morphometrics at 10 years between extremely-preterm and term-born children, examined associations with cognition at 12 years, and assessed whether structural covariance differed between extremely preterm children with and without cognitive problems. Cortical morphometrics were examined in 54 extremely-preterm (25 ± 1.0 weeks) and 38 term-born (40 ± 1.1 weeks) children using structural MRI processed with FreeSurfer, and cognition was assessed at 12 years using Wechsler Intelligence Scale for Children. PCA was applied to all cortical morphometric measures to examine associations with cognitive outcomes. Extremely preterm children showed widespread cortical thinning, altered surface area, and region-specific sulcal depth differences, shallower in parietal and orbitofrontal, deeper in cingulate and postcentral regions (β = -1.15 to 1.42; all q < 0.05). Gyrification was lower in orbitofrontal, temporal, and parietal cortices (β = -0.51 to -1.07; all q < 0.05). Four principal components of cortical morphology at 10 years (PC4, PC8, PC11, and PC13) were associated with later cognitive outcomes. Extremely preterm children with cognitive problems exhibited distinct structural covariance and hub organisation. These findings suggest lasting cortical reorganisation after extremely preterm birth and support multivariate cortical patterns as markers of later cognitive risk.
Modified nucleotide bases like 5-methylcytosine (m5C) and N1-methyl-pseudouridine (m1Ψ) are widely used to enhance stability and reduce immunogenicity in therapeutic RNAs, yet their impact on RNA tertiary structure remains unclear. Here we investigate how these modifications influence folding and function in both a synthetic RNA origami nanostructure and the natural Tetrahymena ribozyme. Using cryo-EM, FRET, and biochemical assays, we find that modified bases impede proper maturation of RNA origami by stabilizing alternative coaxial stacking at key junctions, leading to dimerization. In the ribozyme, modifications shift the equilibrium between open and closed conformations, altering catalytic activity in a temperature-dependent manner. These effects arise primarily from changes in base-stacking energetics rather than base pairing. Our findings reveal that base modifications reshape RNA folding landscapes and structure-function relationships, underscoring the need to consider structural consequences when designing modified RNAs for synthetic biology and therapeutic applications.
The yield and quality of mRNA synthesized by in vitro transcription (IVT) are highly dependent on reaction components. While Mg2+ is a well-established cofactor, the role of anions remain less explored. This study investigates the regulatory effects and mechanisms of the chaotropic salt sodium perchlorate (NaClO4) on IVT process, focusing on mRNA yield and double-stranded RNA (dsRNA) formation. Experimentally, introducing 50 mM NaClO4 in IVT achieves up to 85% reduction in dsRNA, while doubling the mRNA yield. This regulatory performance is superior to high-concentration urea, which requires 400 mM to achieve a similar dsRNA inhibitory effect and provides negligible yield enhancement. To elucidate the distinct regulatory mechanisms of NaClO₄ and urea, molecular dynamics simulations were performed. Results indicate that urea molecules abundantly bind to RNA, blocking base pairing and inhibiting RNA folding, whereas ClO4- ions bind minimally but raise the electrostatic energy barrier for RNA folding, both mechanisms reduce the dsRNA formation. Furthermore, urea disrupts the hydration layer around the DNA template and interferes with its recognition by T7 RNA polymerase, while ClO4- has negligible impact. Conformational analysis on T7 RNA polymerase-DNA complex shows that low NaClO4 concentrations promote enzyme's active pocket contraction, enhancing binding; higher concentrations, however, lead to displacement of a key residue (Trp 422), impairing promoter recognition. This explains the non-monotonic variation in mRNA yield with increasing NaClO4 concentrations: beyond a critical concentration, transcription efficiency declines and may fail completely. These findings provide crucial insights for optimizing IVT systems by tailoring anion selection and concentration.
Codon usage bias has a crucial impact on the translation efficiency and cotranslational folding of proteins, necessitating the algorithmic development of codon optimization/harmonization methods, particularly for heterologous recombinant protein expression. Codon harmonization is especially valuable for proteins sensitive to translation rates because it can potentially replicate native translation speeds, preserving proper folding and maintaining protein activity. This work proposes a Monte Carlo-based codon harmonization algorithm, MoSAiC (Monte Carlo-based Simulated Annealing for Linked Codons), for the harmonization of a set of linked codons, which differs from conventional codon harmonization by focusing on the codon sets rather than individual ones. Our MoSAiC demonstrates robust computational performance on ribosomal proteins (S18, S15, S10, and L11) as model systems. Among them, the harmonized gene of RP S18 was expressed and compared with the expression of the wild-type gene. The harmonized gene clearly yielded a larger quantity of the protein, from which the amount of the soluble protein was also significant. These results underscored the potential of the linked codon harmonization approach to enhance the expression and functionality of sensitive proteins, setting the stage for more efficient production of recombinant proteins in various biotechnological and pharmaceutical applications.
Intrinsically disordered proteins populate heterogeneous conformational ensembles that are challenging to characterise. While all-atom molecular dynamics simulations can provide detailed insights into dynamic ensembles, achieving sufficient sampling remains difficult. Here, we show that On-the-fly Probability Enhanced Sampling (OPES) in the multithermal ensemble enables efficient generation of atomistic ensembles for disordered peptides and proteins ranging from 15 to 71 residues in length. OPES achieves multithermal sampling within a single simulation replica, without replica exchange or extensive parameter tuning. Across multiple systems, OPES yields reweighted ensembles broadly consistent with replica-exchange with solute tempering (REST2) and unbiased simulations, while accelerating convergence and enabling broader exploration of low-population conformational states. Applied to the intrinsically disordered transcriptional coactivator ACTR, OPES reveals transiently structured states in which multiple α-helices involved in partner binding fold cooperatively and form tertiary contacts. These rare, partially structured conformations are reversibly sampled during the simulations, are consistent with extensive NMR and SAXS data, and could facilitate folding-upon-binding through conformational selection. They may also represent viable targets for drug design or for engineering disordered proteins with customised conformational landscapes. More broadly, our results establish OPES multithermal sampling as a robust and accessible approach for uncovering functionally relevant conformations in intrinsically disordered proteins.
Pulmonary fibrosis is a chronic and relentlessly progressive interstitial lung disease characterized by irreversible scarring of the lung parenchyma, for which no curative therapies currently exist. Heat shock protein 47 (HSP47), a collagen-specific molecular chaperone essential for proper collagen folding and secretion, has emerged as a compelling therapeutic target to mitigate pathological collagen deposition. To identify inhibitors of the HSP47-collagen interaction, we comprehensively screened a marine microorganism extract library. Initial screening revealed 16 extracts with inhibitory activity, and subsequent secondary screening narrowed these down to seven candidates. Among them, one extract exhibited potent, concentration-dependent inhibition of HSP47 activity and markedly suppressed collagen synthesis in lung fibroblasts at low concentrations. This lead extract was fractionated using high-performance liquid chromatography, and bioactive components were subsequently isolated. Mass spectrometric analysis identified the active compounds as C14- and C15-surfactin, cyclic lipopeptides produced by Bacillus subtilis. Treatment with surfactin significantly attenuated collagen production in pulmonary fibroblasts without altering HSP47 expression, suggesting inhibition through disruption of the HSP47-collagen interaction. Furthermore, oral administration of surfactin markedly reduced lung hydroxyproline content, demonstrating substantial antifibrotic efficacy in vivo. Collectively, surfactin are novel inhibitors of the HSP47-collagen interaction with promising therapeutic potential for pulmonary fibrosis treatment.
This paper proposes an extension of the traditional Central Dogma of molecular biology to a more dynamic model termed the Central Dogma cycle (CDC) and a broader network called the Central Dogma cyclic network (CDCN). While the Central Dogma is necessary for genetic information flow, it is insufficient to fully explain cellular memory, decision-making, and information management. The CDC incorporates additional well-established steps such as protein folding and networking, highlighting the cyclical nature of biological information flow. I propose that this cyclic architecture functions as a key mechanism for cellular memory, drawing analogies to memory functions in computers, such as input, read, write, execute, and erase. Within the CDCN, interconnected metabolic and signaling pathways act as logic-enabled processors that bridge DNA mutations to phenotypes. This model reframes heredity beyond nucleic acid sequences and evolution as the optimization of memory-bearing networks. It is extensible to broader biological systems such as physiological feedback loops. Understanding cellular memory through this cyclic network model offers a unified perspective on heredity, adaptation to the environment, cell processes, and the disruptions of information flow in disease pathology.
All folded proteins continuously fluctuate between their low-energy native structures and higher-energy conformations that can be partially or fully unfolded. These rare states influence protein function1,2, interactions3, aggregation4-7 and immunogenicity8,9, yet they remain far less understood than protein native states. Although native protein structures are now often predictable with impressive accuracy, conformational fluctuations and their energies remain largely invisible10 and unpredictable11-14, and experimental challenges have prevented large-scale measurements that could improve machine learning and physics-based modelling. Here we introduce a multiplexed experimental approach to analyse the energies of conformational fluctuations for hundreds of protein domains in parallel using intact protein hydrogen-deuterium exchange mass spectrometry. We analysed 5,778 domains 28-64 amino acids in length, revealing hidden variation in conformational fluctuations, even between sequences sharing the same fold and global folding stability. Site-resolved hydrogen exchange nuclear magnetic resonance analysis of 13 domains showed that these fluctuations often involve entire secondary structural elements with lower stability than the overall fold. Computational modelling of our domains identified structural features that correlated with the experimentally observed fluctuations, enabling us to design mutations that stabilized low-stability structural segments. Our dataset enables new machine-learning-based analysis of protein energy landscapes, and our experimental approach promises to profile these landscapes at considerable scale.
Quantitative interpretation of ChIP-seq data is instrumental to derive insight into chromatin and transcription factor biology. Here we developed ChIP-FRiP, an end-to-end pipeline enabling systematic comparison of pairwise protein positioning, and applied it to the study of cohesin. In mammalian interphase, loop extruding cohesin complexes are positioned by CTCF barriers to generate locus-specific 3D genome folding patterns. Many aspects of our understanding of cohesin loop extrusion come from interpreting the amount of cohesin ChIP-seq signal at CTCF barriers, which has been reported to change variably after perturbing cohesin co-factors, such as NIPBL, PDS5A/B, and WAPL. Using ChIP-FRiP to homogeneously process 140 cohesin ChIP-seq datasets from 13 publicly available studies, we observed substantial variation attributable to technical effects, obscuring biological interpretability. To better understand how technical considerations, such as antibody specificity, influence apparent cohesin binding patterns, we integrated technical aspects of ChIP-seq into biophysical simulations of loop extrusion. Leveraging a simple biochemical model for background ChIP-seq signal, we derived a strategy to estimate and correct for the background using paired spike-in ChIP-seq data from wild-type and depletion conditions. Our results establish a framework for reliable comparative analysis, demonstrating that accurate background correction is requisite for interpreting the roles of cohesin cofactors in cohesin positioning.
Dexamethasone is a glucocorticoid analogue and acts like the hormone cortisol, which is secreted from the adrenal glands. Its prolonged use may alter glucose metabolism. This review is a detailed summary of the underlying molecular mechanism of dexamethasone induced Insulin Resistance and Diabetes Mellitus. A decade of review journals retrieved from Scopus, ScienceDirect, PubMed, and Web of Science databases are systematically analyzed to examine various mechanisms involved in dexamethasone-induced metabolic syndrome. This in vivo model is suitable for studying Diabetes. Impaired insulin sensitivity is a biological response to insulin stimulation in target tissues. This review describes the underlying Dexamethasone-induced Insulin Resistance through multiple molecular mechanisms including decreased expression of glucose transporter protein 1 and 2 (GLUT 1and GLUT 2), glycogen synthase, increased expression of FK506 binding protein 5 (FKBP5), Cx36 protein, GSK-3, altered metabolism, and GLUT 4 transporter expression, mitochondrial dysfunction, defective glucose uptake, inflammation, insulin receptor mutations, stimulation of protein kinase C, oxygen species induced stress, protein folding stress, endothelial dysfunction, suppression of phosphatidylinositol 3 kinase (P13K) activity associated with IRS-1. Significant metabolic alterations triggered by dexamethasone treatment interposed with typical blood sugar homeostasis. Future research should concentrate on methods to avoid insulin resistance caused by dexamethasone without compromising the pharmacotherapeutic effect. Living with insulin resistance in the long run can lead to type 2 diabetes along with other complications. In discriminate use of Dexamethasone is the culprit behind the development of abnormal insulin action. Overall, a better insight in this regard is the need of the hour. Furthermore, work is essential towards the development of new molecules to provide a better substitute in the Reck.
From the initial discovery of FK506 binding protein 12 (FKBP12), the FKBP familial group of proteins have since been identified to be highly conserved proteins within eukaryotes. As functional proteins, the isoforms of FKBPs display a myriad of functions within the systemic environment. FKBP proteins are known to possess roles in apoptosis, cancer, cardiac support, cell development, neuronal function, protein folding and trafficking, cell receptor signalling and transcriptional control, whilst conserved across multiple types of tissues and subcellular components. Of the 16 member FKBP family, FKBP51 and FKBP52 are the only members that exhibit a diverse role in the regulation of steroid hormone receptors. Beyond their involvement in receptor signalling, binding and nuclear translocation, studies have implicated FKBP51 and FKBP52 in the pathogenesis of a variety of hormone dependent diseases and cancers. Furthermore, selective inhibition of FKBP51 has advanced considerably, whereas FKBP52 selectivity remains an ongoing challenge. This review summarises the current mechanistic understanding of the FKBP protein family, with a focus on the roles of FKBP51 and FKBP52 in steroid hormone-driven cancers, highlighting key knowledge gaps, translational biomarkers, pre-clinical efforts and clinical progress.
Knotted proteins possess complex topologies that impose unique constraints on folding and unfolding. Whether the knot persists during denaturation and how its conformation reorganizes, however, remain unresolved. Here, we investigated the knotted protein 1O6D using site-specific fluorescence resonance energy transfer (FRET) and time-resolved fluorescence anisotropy (TRFA). The combined data support a staged denaturation process. At low denaturant concentrations, the knotted architecture undergoes progressive loosening accompanied by spatially nonuniform local rearrangement and C-terminal-directed reorganization. TRFA further reveals distinct site-dependent dynamical responses, including nonmonotonic anisotropy changes at W120 and W127, consistent with transient confinement within a motion-restricted intermediate microenvironment. At higher denaturant concentrations, the protein expands substantially, yet the FRET-derived distances and apparent thermodynamic parameters remain more consistent with a topologically constrained denatured ensemble than with a fully extended random coil. These results provide site-resolved evidence for asymmetric relaxation and persistence of a loosened but still tied topological state.