European Biophysics Journal

Protein oligomerization equilibria are central to many biological processes and are often highly sensitive to environmental conditions such as ionic strength, pH, and ligand binding. Quantitative characterization of these equilibria remains experimentally challenging because stable protein complexes frequently dissociate only at concentrations that are difficult to access with conventional biophysical methods. Fluorescence correlation spectroscopy (FCS) is uniquely suited to this problem, as it provides direct access to diffusion coefficients of fluorescently labeled proteins at nanomolar concentrations. However, the quantitative interpretation of FCS data from oligomeric systems requires a rigorous mathematical framework and careful experimental practice that have not previously been described in sufficient detail to guide implementation. Here, we provide a comprehensive description of the experimental workflow and analytical framework for determining dissociation equilibrium constants by FCS, covering instrument calibration, sample preparation, data quality control, after-pulse correction, and nonlinear least-squares fitting. We discuss common sources of error and provide practical guidance on critical experimental considerations including surface passivation, buffer preparation, equilibration time, and the role of labeling efficiency. Using the homotrimeric sliding clamp PCNA as a model system, we demonstrate the complete workflow under a range of KCl concentrations and show that moderate ionic strength stabilizes the PCNA trimer while very high salt partially destabilizes the complex. The approach is general and applicable to any reversible protein self-association reaction accessible by fluorescence detection at low protein concentrations.

We demonstrate the use of fluorescence correlation spectroscopy (FCS) to characterize fluorescently-labeled protein production. We use cell-free protein synthesis to express the protein YFP-CopB, a fusion of Chlamydia Outer Protein (Cop) B and Yellow Fluorescent Protein (YFP). CopB is a [~]50 kDa protein believed to have a critical role in chlamydial infection.1 After adding a plasmid encoding YFP-CopB to an E. coli cell-free lysate, protein expression begins. We track the cell-free reaction over several hours using the EI-FLEX, a commercial instrument with FCS capability. As protein is expressed over time, YFP-CopB increases in concentration, and the EI-FLEX detects an increase in fluorescent signal above the background of the cell-free lysate. The FCS data collected gives information about the size, aggregation tendencies, rates of production and fluorescent protein maturation, and concentration of the YFP-CopB produced. The use of FCS concurrent with cell-free synthesis presents a simple method to characterize proteins of interest as they are produced without the need for purification.

PURPOSEBenzalkonium chloride (BAK), a common preservative in eye drops, has a major side effect of dry eye. The mechanisms are typically attributed to BAK cytotoxicity. However, due to its surfactant properties, BAK can disrupt the tear film lipid layer (TFLL), leading to dry eye. This study examined the stability and compressibility of the TFLL and the impact of the presence of BAK. METHODSMeibomian gland secretion (meibum, source of the TFLL) was collected from sacrificed cows eyelids. Lipids were extracted by dissolving meibum in chloroform to a final concentration of 1 mg/mL, with one solution additionally containing 0.1 mg/mL BAK. Each solution was overlaid on a water subphase in a Langmuir Trough-Blodgett trough. The changes of surface pressure ({pi}) with area (A) for the lipid film upon compression were monitored, and the corresponding compression modulus (Cs-1) at each data point was determined. RESULTSThe {pi}-A isotherms for meibum lipid monolayers exhibited near-reversible behavior with a smooth profile with a maximum {pi} of approximately 32 mN/m. The Cs-1-{pi} isotherms of the meibum lipid monolayer show that the films are gel-like with a constant compressive modulus of 24-32 mN/m within the surface pressure range of 8-30 mN/m. In contrast, adding BAK dramatically decreased the maximum surface pressure to only 10 mN/m and the compressive modulus to only 2-10 mN/m. CONCLUSIONSThis study demonstrated that BAK disrupts the meibum lipid layer by forming a monolayer with decreased stability and reduced compressive resistance, a mechanism that may underlie its dry-eye side effect yet has largely been neglected.

Single-molecule tracking measures the stochastic motion of individual biomolecules in the cellular environment. Statistical analysis of trajectory ensembles is required to gain insight into the biophysical nature of mobility states and molecular interactions that they reflect. Mobility states can be parameterized by a generalized diffusion coefficient and anomalous exponent. Experimental constraints such as finite track length and localization precision limit how accurately these parameters can be determined. We compare the performance of analysis methods to recover the input parameters from ensembles of simulated single molecule tracks from different states spanning the range of anomalous diffusive behaviors observed in the cell nucleus. We further develop a framework to quantify error rates in the assignment of mobility states to individual molecules based on recall rates and precision. Our analysis shows that single-track analysis methods are superior to bulk methods in their ability to recover parametric descriptors from mixed populations. The most complete description is obtained by combining outputs from different tools. Our work provides a guide to assess the accuracy of analyses and obtain the most accurate parametric description of experimental single particle tracking data. Statement of significanceExperimental single particle tracking data provides rich insight into molecular interactions directly in living cells. But data analysis depends critically on choosing the correct diffusion model and appropriate tools to extract accurate information. Importantly, it is usually not obvious from the output of a method whether the results are accurate or not. In this work, we use ensembles of tracks simulated with fractional Brownian motion methods to characterize the impact of track length and localization precision on analysis outcomes. We elaborate on specific strengths and weaknesses of commonly used and newly developed analysis tools to provide a template for thorough assessment and quantification of error rates in experimental data analysis.

Molecular dynamics simulations of nucleic acids are performed using a solvent-buffer distance of 10 [A] between the solute surface and the simulation box boundary. Although this cell size has been extensively explored in protein simulations, its implications for nucleic acid dynamics are not well understood. Nucleic acids are elongated, highly charged, and flexible structures with hydration and dynamical properties distinct from those of proteins and therefore, they may require different solvent-layer considerations in simulations. In this study, we investigated the effect of simulation cell size on nucleic acid dynamics by simulating a 30-base-pair double-helical nucleic acid structure and its two single-stranded forms using solvent-buffer distances of 3, 5, 10, 15, and 20 [A]. Smaller cells may impose restricted hydration, molecular crowding, and periodic image interactions. However, larger cells provide solvent space for conformational relaxation. A total of 45 s of molecular dynamics simulations were performed (3 structures x 5 cell sizes x 3 replicates x 1 s). Our results show that while the commonly used 10 [A] buffer may be sufficient to maintain the stability of the double-stranded nucleic acid, larger cells are required to capture the conformational dynamics of single-stranded structures. In both, increasing the cell size to 15 or 20 [A] enables broader conformational sampling. The first hydration shell exhibits reduced crowding in the 20 [A] cell, consistent with more relaxed conformations. At larger cell sizes, single-stranded nucleic acids adopt compact, self-associated conformations for stability. Together, this study presents physical insight into how simulation cell size and solvent environment influence nucleic acid dynamics.

Poly-L-Lysine (PLL) mediates the non-specific adhesion of cells and is commonly used in Atomic Force Microscopy (AFM) measurements, to ensure that cells remain attached to the substrate. However, it is acknowledged that adhesion affects the measured mechanical properties, in particular in the case Red Blood Cells (RBCs). This results in a wide range of Youngs modulus E reported in the literature. The present study aims at providing a systematic approach to the impact of non-specific adhesion on the rheology of RBCs. It provides a correlation between the topography profile of adherent RBCs and their rheology, from weak (cPLL = 10-3 mg/mL) to strong-adhesion (cPLL = 100 mg/mL) regimes. Using RICM and AFM, we find that there is a continuum of RBC shapes promoted by adhesion, from concave to dome-shaped, as predicted by the theory of vesicle adhesion. Their elastic properties discriminate them into two populations depending on adhesion strength, where stiffer RBCs (E {gtrsim} 100 Pa) correlate with dome-shaped cells. These findings are supported by rheology measurements of the dynamic complex shear modulus G*(f): while the storage modulus increases with cell-substrate adhesion, reflective of an increased membrane shear modulus, the loss modulus remains unchanged. Finally, further analysis inspired by membrane theory shows that different deformation modes may be triggered during indentation of either weakly or strongly adhering RBCs, illustrating the limits of the Hertz model.

The widespread use of synthetic food dyes, such as Acid Yellow 23 (AY 23), in the food, cosmetics, and pharmaceutical industries raises questions about their potential effects on biological systems and public health. The concentration-dependent interaction between AY 23 and bovine serum albumin (BSA), a crucial model protein for understanding pharmacokinetics and protein-ligand behaviour, was examined in this study. We demonstrate that, under physiological conditions, increasing dye concentrations from 50 M to 200 M results in notable conformational changes, increased surface hydrophobicity, and protein aggregation using a multimodal biophysical approach that includes fluorescence spectroscopy. Direct visualisation verified these structural changes and aggregate formation, whereas hemolytic assay confirmed the high hemolytic nature of AY 23-induced fibrils. Additionally, this study provides a mechanistic basis for the toxicological effects of AY 23, underscoring the implications of food dyes for public health.

Surface factors that contribute to the virulence of Staphylococcus aureus have become therapeutic targets in the treatment of illness associated with this bacterium. Staphylococcal protein A (SpA) is a well-known contributor to S. aureus toxicity and virulence, although relatively little is known about protein A and how its biological function has evolved. SpA is displayed on the surface of the bacterium and contains 5 nearly identical helical ({approx} 60 aa) domains that bind antibodies with high affinity (Kd {approx} 10 nM). The folding free energies of only domains E and B have been determined. In this study we used intrinsic fluorescence detected denaturation to measure the folding thermodynamics of each domain in isolation and in the native multidomain context using a construct that includes the N-terminal half of the mature protein (SpA-N). We also constructed a series of proteins with 1 to 5 repeats of B domain, linked exactly as the five domains of WT SpA are linked. We used nearest neighbor thermodynamic models to explicitly demonstrate that the domains in B domain repeat proteins fold independently. We also showed that the domains in SpA-N fold independently by comparing the folding free energies of domains in isolation and in their multidomain context. Previous dynamic NMR experiments detected highly flexible linkers between domains in 5B, suggesting that the domains of SpA are structurally independent, which is likely responsible for the lack of thermodynamic coupling. Our results also showed a steep increase in domain stability from the N-to C-terminus in SpA-N, from 0.97 {+/-} 0.05 to 5.57 {+/-} 0.28 kcal/mol. We hypothesize that this stability gradient is related to efficient secretion of protein A.

Quantitative analysis of action potential (AP) waveforms is central to studies of neuronal excitability, ion channel function, disease mechanisms, and pharmacological modulation. However, AP analysis is still often performed using partially manual workflows, laboratory-specific spreadsheets, or proprietary software environments that can limit reproducibility, transparency, and throughput. Here we present APpar, a freely available, open-source software tool for extracting AP parameters, developed for use with the OriginLab software package Origin/OriginPro. APpar detects APs from membrane voltage recordings using a user-defined derivative criterion and calculates a comprehensive set of excitability parameters, including resting membrane potential, AP threshold, dV/dt at threshold, overshoot, undershoot, AP amplitude, AP half-amplitude, rise time, decay time, AP duration, AP half-width, AP width at 0 mV, AP area above voltage threshold, dV/dtMAX, dV/dtMIN, interspike interval for the respective AP. Because AP threshold is a particularly sensitive and method-dependent measurement, APpar includes a TRUE-threshold validation algorithm. After the initial forward dV/dt threshold crossing is identified, the software finds AP overshoot, searches backward to the closest preceding local dV/dt maximum, then searches backward to the user-defined dV/dt crossing and recalculates AP parameters from this validated threshold point. We validated APpar using APs from dorsal root ganglion neurons current-clamp recordings, including copied identical APs, current-evoked repetitive firing, and long-duration spontaneous firing. The software produced stable measurements from identical copied APs and extracted dynamic changes in AP parameters across repetitive and spontaneous firing sequences. APpar provides a transparent, customizable, and Origin-compatible framework for reproducible AP analysis in neuronal electrophysiology. Significance statementAction potential waveform analysis is essential for interpreting neuronal excitability, but many AP measurements remain vulnerable to user-dependent threshold placement, manual cursor selection, and inconsistent parameter definitions. APpar, a freely available, open-source software tool, addresses this problem by automating AP detection and parameter extraction within the OriginLab environment widely available to electrophysiology laboratories. The software formalizes definitions of AP threshold, amplitude, duration, half-width, afterhyperpolarization, derivative-based parameters, and firing metrics, and introduces a TRUE-threshold validation algorithm that recalculates AP parameters from a derivative-validated threshold point. This workflow reduces operator-dependent variability while preserving user control over physiologically meaningful detection criteria. HighlightsAutomated action potential waveform analysis within OriginLab Origin environments AP threshold validation improves reproducibility of derivative-based threshold detection Extracts action potential kinetics, amplitudes, widths, and dV/dt measurements Open-source workflow supports reproducible neuronal electrophysiology data analysis Validated using repetitive and spontaneous firing in DRG neurons

Botanical dietary supplements (like wheat, barley, teff, oats, white lupin, pumpkin seed, and chickpeas) may contain trace amounts of toxicants in addition to important micronutrients. Developing and validating a reliable protocol for the simultaneous quantification of Cu, Fe, Zn, Mo, Se, Mn, Pb, Al, Ni, and Cr using a PerkinElmer (NexIONTM2000 model) quadrupole ICP MS (including a He collision and reaction cell when needed) with closed vessel microwave digestion using (HNO3 + H2O2) was the aim of this study.The method was subsequently utilized in a sample survey, and the outcomes were evaluated against WHO/JECFA standards. From five study regions, twenty-seven farm-collected botanical powder samples representing seven species were acquired. To create one composite per species, field subsamples were cleaned, air dried, ground, and blended (nine subsamples per botanical: three grabs from each of three farms). HNO3/H2O2 was used to digest aliquots (0.250-0.500gm) in closed microwave containers. Internal standards, multi-point external calibration, procedural blanks, verified reference materials, matrix spikes, and duplicates were all used in ICP MSs multi-element quantitation. Method LODs/LOQs, accuracy (CRM recoveries), and precision (RSD) were calculated.The technique produced low LODs that were suitable for dietary evaluation (typical LOD ranges: Cu, Fe, Zn, Mn, Ni, Cr (0.001-0.01) mg/kg; Mo, Se, Pb, Al (0.002-0.05) mg/kg. For the majority of analytes, within-run RSDs were less than 5%, while CRM recoveries ranged from 88.9 to 110%. The concentrations of essential elements varied greatly (average mg/kg: Fe (280.7{+/-}25.6); Zn (6.0{+/-}0.541); Cu (2.8{+/-}0.269); Mn (398.3{+/-}23.8); {micro}gm/kg: Se (0.061{+/-}0.006); Mo (1.0 {+/-}0.022). Although some composites approached or exceeded conservative intake thresholds for Pb and Al under high consumption scenarios, toxic elements were generally low (mean mg/kg: Pb (0.062{+/-}0.007); Al(185.2{+/-}18.5); Ni(1.6{+/-}0.163); Cr(1.8{+/-}0.171).For the simultaneous nutritional and contaminant profiling of supplements derived from cereals and those not, the validated ICP- MS workflow with microwave HNO3 and H2O2 digestion is suitable. Accurate labeling and consumer safety can be supported by routine screening and supply chain controls.

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.

Advances in Electrostatic Linear Ion Trap (ELIT) Charge Detection Mass Spectrometry (CDMS) over the past 10 years have revolutionized its use for analyzing very high-molecular-weight species such as protein complexes, viral vectors, vaccines, viruses, and amyloid fibrils. Nonetheless, ELIT-based CDMS has remained confined to a small number of specialized instrumentation groups, predominantly in academia, where large and complex home-built instruments are operated by highly skilled scientists in dedicated facilities. In this report, we discuss the primary challenges addressed in the design of a benchtop ELIT-based CDMS instrument. We highlight key design aspects of the hardware, acquisition modes, and control software, and we present important performance metrics (mass range, resolution and sensitivity) demonstrated using samples representative of the technology's key application areas.

The molten globule (MG) state is an intermediate in the unfolding pathway of proteins, typically triggered by denaturing agents such as urea, extreme pH, high pressure, or heat. The microscopic details of such states are far from understood. Here we study the MG states in protein Hen Egg-White Lysozyme (PDB ID: 1AKI) using microscopic constant pH molecular dynamics (CpHMD) simulations and experiments across a wide pH range. We observe that the titratable residues act as key drivers of conformational fluctuations, promoting the emergence of MG states at extreme pH. These states display partial unfolding, and small global structural changes (< 7% deviation). Hydration around the fluctuating acidic residues shows reduced water density and weakened hydrogen bonding at low pH. At high pH, hydration around acidic residues increases relative to pH = 7, whereas hydration around basic residues decreases. The translational and rotational dynamics of hydration water also exhibit pronounced pH dependence: the translational diffusion coefficient (Dtrans) increases linearly with decrease in pH in acidic medium and increases linearly with increasing pH in the basic regime. The rotational diffusion (Drot) shows similar dependencies on pH except a break at pH {approx} 4 corresponding to acidic residue pKa values. Our results may be useful to identify ligand binding of lysozyme in extreme pH conditions.

Buzz pollination is an important behavior in which bees use vibrations to extract pollen from poricidal anthers. However, the extent to which vibration frequency influences pollen release remains unclear. Here, we quantified pollen expulsion from Solanum sisymbriifolium anthers subjected to harmonic excitation over a broad frequency range encompassing the anthers first natural frequency. We excited anthers to expel pollen and measured anther kinematics and pollen release using high-speed videography. Particle tracking enabled continuous estimation of pollen release throughout each buzzing event, allowing both initial pollen flux and total pollen released to be quantified. Pollen release depended strongly on excitation frequency. Initial pollen flux, total pollen release, and anther kinematics peaked when excitation frequency approached the anthers natural frequency. Anther tip velocity amplitude exhibited the strongest correlation with total pollen release (r = 0.755) and initial pollen flux (r = 0.898). Experimental observations were compared with nonlinear and linear statistical models of pollen release. While both models captured trends in normalized pollen flux, they overpredicted total pollen release, suggesting that adhesive interactions play important roles during extended buzzing events. These findings demonstrate that anther structural dynamics influence pollen release and suggest that vibration amplification may improve the efficiency of buzz pollination.

Underwater adhesion research increasingly draws on bioinspired systems to uncover the molecular mechanisms that enable strong interfacial binding in aqueous environments. The biofilm adhesin Bap1 from Vibrio cholerae contains a short peptide motif, SYWFFGWHTK (CP), which exhibits exceptional adhesive performance, surpassing mussel foot protein mfp5 under comparable conditions. Despite its promise, the roles of ionic environments and aggregation behavior in governing CP adhesion remain unclear. In this study, we investigate how ion identity influences CP aggregation, film formation, and interfacial properties. Using dynamic light scattering, we identify the formation of micron-scale assemblies of aggregated molecular clusters (AAMCs), with size distributions modulated by salt type. Quartz crystal microbalance with dissipation and liquid atomic force microscopy reveal that CP film formation is both surface- and ion-dependent. On gold substrates, AAMCs preferentially adsorb and collapse into rigid, smooth nanofilms, consistent with hydrophobic-driven compaction. In contrast, silicate surfaces inhibit such collapse, yielding distinct morphologies and interfacial energetics. These findings demonstrate that surface chemistry and ionic conditions jointly regulate peptide aggregation and adhesion. This work provides mechanistic insight into hydrophobic-rich peptide systems and informs the rational design of next-generation wet adhesives, with broader implications for biomaterials and peptide-based formulations. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/733527v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1bd012aorg.highwire.dtl.DTLVardef@1977892org.highwire.dtl.DTLVardef@16cf79borg.highwire.dtl.DTLVardef@f405bf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Integrins are adhesion proteins that diffuse along the cell membrane, bind to ligands, and cluster with each other in the early stage of cell adhesion. Integrin clustering and its specific spatial distribution play important roles in subsequent biological processes; however, the mechanisms that give rise to their characteristic spatial distribution remain poorly understood. To address this issue, we developed a cell adhesion model that incorporates cell membrane deformation and integrin dynamics. A hybrid continuous/discrete model was applied to represent membrane deformation, whereas Brownian dynamics combined with a transition state model was used to describe integrin dynamics and binding kinetics. Comparison of numerical simulations of cell adhesion to a substrate with experimental observations at the early stage of adhesion successfully reproduced the characteristic spatial distribution of integrin clusters, in which high-density clusters formed at the periphery of the region adhering to the substrate. These results suggest that the cellular-scale distribution of integrin clusters can be reproduced using only minimal elements, such as adhesion-driven membrane deformation and integrin-ligand binding. In addition, we found that the strength of integrin-ligand binding regulates the degree of clustering by changing the size of the part of the membrane that is deformed, thereby mechanically supporting the mechanical involvement of the actin cytoskeleton in integrin clustering. Furthermore, the formation and spatial distribution of integrin clusters were shown to be determined not only by the static mechanical equilibrium of membrane deformation and physical adsorption, but also by membrane spreading/deformation and the dynamic behavior of integrins. This suggests that the size and spatial distribution of integrin clusters may be controllable by modulating the speed of membrane spreading.

Although rhizosphere microbiomes are known to enhance plants resistance to water stress, it is believed that only fungi actively contribute to the transport and uptake of water. We investigated the biomechanical impact of bacterial motility on water transport in soil by combining surface tension measurements and water infiltration experiments in soil microcosms. We observed that flagellar-based motility in Bacillus subtilis cells reduces the apparent surface tension of fluids by up to 15%. The effect reported depends on cell density and swimming speed, confirming its biomechanical origin, and was able to accelerate water infiltration and rewetting of soil. We conclude that Bacillus subtilis facilitates soil water transport through the deformation of air water interfaces in pores.

Magnetic treatment in tomato seeds (Solanum lycopersicum L.) has been studied as a biotechnological technique to induce a reduction in germination times and enhance plant development. However, the modified cellular mechanisms involved in the reduction of germination times or the improvement of development parameters are not yet clearly established. To explore a possible altered cellular mechanism, the effect of homogeneous static magnetic fields on the structure of the cyclic nucleotide-gated channel 6 (CNGC6), the modification in the organization of POPC lipids in the plasma membrane, and changes in calcium ion mobility were evaluated. For this purpose, coarse-grained molecular dynamics simulations were performed using the Martini 3 model in GROMACS, applying five different magnetic flux densities (0.000, 0.001, 0.010, 0.100, 1.000, and 10.000) T over 1 000 ns. The results showed an anisotropic effect in the longitudinal direction of the protein, which generated heterogeneous behavior among the chains of the homotetramer; this altered the conformation of the CNGC6 channel and modified the pore bottleneck. In contrast, no significant changes were observed in the conformational order of the POPC phospholipid chains. As a preliminary, single-replicate exploratory study, these results suggest that homogeneous static magnetic fields may induce specific structural modifications in the CNGC6 ion channel of Solanum lycopersicum L. without compromising the integrity of the lipid bilayer or the dynamics of ion transport within the analyzed timescale; these preliminary findings provide a molecular-level structural basis for future experimental and computational investigations of magnetic field effects on plant cyclic nucleotide-gated channels.

For structural-biology and protein-production pipelines, the hardest part of a difficult protein is not the biology -- it is obtaining a well-behaved sample for functional studies. Programs routinely stall at construct design, expression, and purification: deciding where to truncate, which tags to use, how to express, and how to purify so the protein survives concentration and handling. These decisions are still made largely by literature precedent and experimental experience, and they require trial-and-error before arriving at a functional construct for hard targets. We present a prospective, single-pair wet-lab case study testing whether an integrated computational platform can improve these decisions. For human fibroblast growth factor 21 (FGF21) -- a clinically important and stability-challenged metabolic hormone -- we compared two expression constructs produced side by side under the same experimental workflow, using two different design strategies: one designed by a scientist from the literature (reproducing the published core-domain construct, PDB 6M6E), and one designed by the Orbion platform -- an AI, prediction-guided protein-design system (orbion.life) -- which additionally generated the expression and purification protocols (executed scientist-in-the-loop). The platforms construct used an unconventional, longer C-terminal boundary not found in public sequence databases. Since the two constructs differ in more than one feature, we treat them as workflow-level designs throughout. The scientist construct gave a higher initial yield ([~]2.4 xmore protein recovered at affinity capture). The platform-designed construct, however, showed a more favourable downstream developability profile: it concentrated higher (1.4 vs 0.7 mg/mL) while remaining more monodisperse by dynamic light scattering (DLS). The scientist construct, in contrast, aggregated on concentration, so its initial-yield advantage did not survive: in the final concentrated sample the Orbion construct provided the more usable material for downstream studies. Computed for the mammalian host used, the platform had prospectively scored its own design higher (composite 68.7 vs 59.0 for the scientist-designed construct), and its predictions of yield, solubility, and disorder matched the wet-lab outcome. This is a single, deliberately scoped case study, not a population-level benchmark; the two constructs differ in more than one feature, and biological activity was not assayed. Alongside the bottlenecks of this approach discussed here, used as a decision aid, prediction-guided construct and protocol design has the potential to remove costly iteration cycles of protein production campaigns.

Keratin proteins are fundamental structural components of hair fibers, contributing to their mechanical resilience, elasticity, and fracture resistance. However, systematic molecular-scale characterization of keratin unfolding mechanics across protein types remains limited, restricting the connection between protein-level deformation mechanisms and hierarchical hair fiber mechanics. Here, we establish a comparative molecular-dynamics-based framework for characterizing the unfolding behavior and nanomechanical response of a curated dataset of 51 keratin proteins. We conduct implicit atomistic molecular dynamics (MD) simulations, including equilibration and steered molecular dynamics (SMD) under four accelerated pulling velocities, to quantify unfolding forces, energy absorption, and structure-property relationships. These accelerated pulling conditions are interpreted as computational probes of relative molecular-scale trends, rather than direct reproductions of experimental hair-fiber strain-rate regimes. Across these accelerated SMD conditions, the simulations show rate-sensitive increases in unfolding force and energy absorption, consistent with constrained molecular relaxation during faster molecular pulling. Stronger correlations between nanomechanical properties and molecular descriptors emerge at higher pulling rates, and the nanomechanical responses of different keratin types (Type I and II) are also compared. The findings provide molecular-level insights into protein unfolding mechanisms that may contribute to the mechanical behavior of hierarchical keratin structures. This study establishes a quantitative framework for comparative keratin unfolding mechanics, providing molecular-level descriptors for future multiscale modeling of hair fiber behavior. These results support applications in biomaterial design, hair fiber durability analysis, and bioinspired material engineering. Future work will integrate these nanomechanical descriptors with fiber-level mechanics and machine learning-based keratin design.