Journal of Colloid and Interface Science

Nanoplastic interactions with cell membranes can influence particle uptake, translocation, and biological effects, making their molecular description important for assessing the environmental and biological consequences of plastic pollution. However, molecular simulations generally represent nanoplastics using monodisperse polymer chains, whereas nanoplastics formed by environmental degradation are polydisperse. Here, we construct 4 nm polyethylene terephthalate (PET), polyethylene (PE), and polystyrene (PS) nanoparticles with lognormal molecular-weight distributions reported for degraded polymers, and with melt-like chain packing and entanglement. Using Martini coarse-grained molecular dynamics, we simulate their interactions for 10 microseconds with three lipid bilayers of increasing complexity. PE and PS insert rapidly and remain largely intact, whereas PET remains surface-associated and progressively releases individual chains. Fluid, polyunsaturated lipid environments undergo greater deformation and promote substantially more chain release, up to 56% of the chains for PET and 43% for PS. Release begins with the shortest chains and progressively extends to longer chains, while semicrystalline PE remains largely intact. In contrast, a size-matched monodisperse PS particle releases no chains and minimally perturbs the membrane. These results identify the molecular-weight distribution as a key determinant of nanoplastic-membrane interactions, and indicate that uniform model particles underestimate the release of polymer chains into biological membranes.

Liquid-liquid phase separation (LLPS) of biomacromolecules has been shown to influence a large variety of biological processes via the formation of membraneless organelles. Aberrant LLPS, however, has been implicated in a number of oncological and neurodegenerative disorders. Proteins related to Alzheimer's, Parkinson's diseases and other major amyloidoses have all been shown to form these condensates. Interestingly, some amyloidogenic proteins were demonstrated to form heterotypic droplets, where both molecules coexisted within the same condensate and affected each other's aggregation. While such cross-interactions have been reported numerous times under non-LLPS conditions, the heterotypic droplet assemblies were only shown for a very limited number of amyloidogenic proteins. In this work, we examine heterotypic LLPS of prion proteins and the pro-inflammatory S100A9, whose cross-interaction under non-LLPS conditions we confirmed in a previous work. The results show that this interaction under condensation-promoting conditions enhances their aggregation, leading to the formation of a higher concentration of amyloid structures. These findings suggest that the pro-inflammatory S100A9 may have a critical role in promoting prion protein aggregation via the assembly of heterotypic condensates under high molecular crowding conditions.

Nanoplastic contamination is increasingly recognized as a biochemical stressor, yet the molecular determinants governing how polymer fragment size dictates protein-level interactions remain poorly understood. Here, we combine molecular docking and all-atom molecular dynamics simulations to characterize the interaction of polyethylene (PE) oligomers of increasing length (n = 3, 5, 7, and 14 repeat units) with human catalase, a tetrameric heme enzyme central to cellular antioxidant defense. Single-chain simulations reveal that short PE fragments (3-, 5-, and 7-mer) migrate from an initial domain-connector pose toward a heme-proximal, previously characterized inhibitor-binding site, whereas the 14-mer remains kinetically confined to a peripheral surface site, implicating short-chain PE as a potential catalase inhibitor. In multichain corona systems, backbone dynamics show a non-monotonic, chain-length-dependent destabilization, with the 3- and 5-mer inducing the greatest structural perturbation and the 14-mer best preserving native-like dynamics despite forming an extensive, percolating surface network across all four subunits. MM-PBSA free energy decomposition identifies van der Waals interactions as the dominant thermodynamic driver of binding, while electrostatic surface mapping indicates that cationic surface patches instead govern long-range spatial targeting of PE chains. These findings establish a framework linking nanoplastic fragment size to protein-level toxicity, with direct implications for assessing the biochemical risk of environmentally weathered polyethylene.

Lipid nanoparticles (LNPs) are a leading drug delivery platform for mRNA or other nucleic acid-based therapeutics. LNP platforms are typically composed of ionizable aminolipids, phospholipids, sterols, and lipids tagged with polyethylene glycol. The ionizable aminolipids are typically cationic at low pH, allowing them to encapsulate negatively charged mRNA. The pH at which the ionizable head groups change charge states, the apparent pKa, is crucial to understand the characteristics and formulation of LNP. However, this is difficult to measure as the apparent pKa differs from the pKa of the aminolipids in bulk solution due to the complex chemical and charge environment. In this study, we use molecular dynamics (MD) simulations with alchemical free energy perturbation to calculate the pKa shift as a function of lipid composition, treating LNP-like and vesicle-like environments. Our results show that the pH-dependent structure of the systems affects the trends in pKa shifts in complex ways, driven by factors including surface electrostatics and lipid internalization. Our all-atom simulation protocol allows us to efficiently estimate the apparent pKa of LNP-like models formed with novel ionizable aminolipids and estimate how it will change with composition.

Biofilm mechanics depend strongly on growth history, hydration, nutrient availability, and interfacial attachment, yet conventional rheology requires harvesting and transfer that can perturb the as-grown structure. Here, we introduce bioRheoFlow, a 3D-printed rheometer-mounted platform for cultivation and mechanical characterization without sample transfer. The platform combines evaporation compensation with static or axial nutrient flow, and benchmark measurements validate its rheometric performance. Applied to Pseudomonas putida and Pantoea sp., bioRheoFlow reveals that biofilms cultivated in situ under axial flow exhibit substantially higher elastic moduli than conventionally grown and scraped samples. Despite similar linear-viscoelastic stress ranges, the species show distinct nonlinear responses: P. putida exhibits a lower crossover stress and more abrupt failure, whereas Pantoea sp. sustains larger stresses and deformations. Creep suggests contributions from bulk deformation and biofilm-substrate interactions. bioRheoFlow provides a controlled framework for probing growth-conditioned mechanics in living biofilms.

Finite-bandgap charge-based FET biosensors are known to be insensitive to electronic tunneling noise in the semiconductor and interference from weakly-charged proteins in physiological samples. However, their signal is still corrupted by pH fluctuations and condensing counterions in the bulk electrolyte. Here, we demonstrate that electrolyte noise is screened by the Stern layer beyond the linear Debye-Huckel limit, when the interfacial potential drop is larger than the thermal voltage. Using a fully nonlinear Gouy-Chapman-Stern (GCS) theory, a universal calibration curve is derived and shown to collapse the low-noise FET signals for miRNA, extracellular vesicles (EV), and protein, captured either directly or through silica and magnetic nanoparticle charge reporters, over eleven decades of analyte concentration. The theory involves the dissociation constant KD and a gain parameter {chi}, which represents the competing effects of the reporter charge and buffer Debye screening that must be large to produce the low-noise GCS condition. The limit of detection (LOD) is shown to be KD/{chi}, which can be optimized by varying the probe density, charge reporter, and buffer solution. An optimized hybridization buffer then yields {chi} ~ 22 (LOD ~1 pM) for miRNA detection, and multivalent capture reduces KD by four orders of magnitude for EV detection (relative to protein detection) with {chi} ~ 34 (LOD ~10 fM).

Lipid packing defects expose hydrophobic regions of membranes and influence protein-membrane recognition, membrane remodeling, and lipid sensing. Quantitative analysis of these defects remains challenging for heterogeneous membranes with strong curvature, mixed bilayer and monolayer organization, and substantial neutral-lipid content. Here, we present Lipid Defect Analyzer (LipiDeA), an open-source Python framework for quantitative analysis of lipid packing defects in complex membrane systems. LipiDeA reconstructs membrane surfaces using triangulated meshes that adapt to local membrane geometry and identifies packing defects from lipid coverage of the reconstructed surface. The framework further classifies bilayer and monolayer regions, resolves defect properties according to local membrane curvature, and distinguishes defects associated with phospholipid tails and neutral lipids. Validation using planar and buckled DPPC bilayers reproduced previously reported packing defect constants and showed that defects preferentially occur in positively curved membrane regions. Application to lipid-droplet-like membranes revealed composition- and topology-dependent defect formation, with the largest defects occurring during the transition from bilayer-dominated to monolayer-containing membranes and distinct defect properties for DAG- and TAG-containing systems. These results highlight the importance of local membrane geometry and composition in determining lipid packing defects.

Antifreeze proteins and peptides adhere to ice crystals and inhibit their growth, resulting in freezing point depression. AFP6 is an abundant antifreeze peptide in the blood serum of winter flounder (Pseudopleuronectes americanus). This 37-residue peptide forms an amphiphilic -helix with a hydrophobic ice-binding surface. In this study, prediction of the peptide structure suggested the formation of an antiparallel dimer burying the hydrophobic surfaces of both subunits. The oligomerisation of AFP6 was therefore examined in aqueous solutions using size-exclusion chromatography and chemical crosslinking along with ice-binding evaluation. Crosslinking of non-amidated AFP6, followed by denaturing electrophoresis, revealed bands consistent with monomers and dimers, whereas results for the amidated form and a recombinant mutant suggested additional larger forms. Bands consistent with the presence of monomers and dimers were also predominant following non-amidated AFP6 crosslinking under a variety of solution conditions, with smaller proportions of peptide assembled up to tetrameric sizes; however, the larger oligomers appeared to be absent from AFP6 treated with sodium bicarbonate. Isolated oligomers of non-amidated AFP6 produced ice crystal morphologies and thermal hysteresis comparable to those for the unfractionated peptide suggesting similar interaction with ice. Oligomerisation of AFP6 may allow greater solubility of this amphiphilic -helical peptide in aqueous solutions.

Cell membranes are decorated by dense, polymeric macromolecules such as proteins with bulky intrinsically disordered regions, glycosylated proteins, and glycopolymers. Experiments have illustrated that the curvature of cellular membranes, which plays a role in diverse biological processes, can be regulated by the local density of these membrane-tethered polymers and their response to environmental changes. However, the mechanisms underlying the feedback between solution conditions, membrane curvature, and the local density and molecular weight of membrane-tethered polymers remain largely unexplored. In this work, using a combination of theory and experiment, we show that the ionic strength of the surrounding solution and the degree of ionization both play important roles in regulating the conformation of the membrane-tethered polymers, which in turn influences their membrane curvature generation capabilities. Specifically, we show that for negatively charged, disordered proteins and glycans, the thickness of the polymer brush decreases with ionic strength but increases with grafting density and degree of ionization, resulting in enhanced sensitivity to membrane curvature and an amplified ability to drive membrane curvature at lower ionic concentrations. Our findings reveal a mechanism by which membrane-tethered polymers generate membrane curvature to minimize free energy, with the extent of curvature generation modulated by the polymer grafting density and layer thickness, as well as by the ionic strength of the surrounding solution. The implications of these findings are broad, suggesting that perturbations to biopolymer charge, such as sialylation of glycans and phosphorylation of disordered proteins, could actively modulate membrane curvature induction in diverse cellular processes from endocytosis to cell motility.

The prevailing view holds that simpler animate beings predating the dawn of cellular life once existed, yet they have long since vanished from the present-day Earth. Our hypothesis posits that these animate beings persist to this day. To this end, we devised a long-term experiment spanning over a decade, keeping Staphylococcus aureus (S. aureus) within a sealed aqueous system of pure water. The findings illustrated that, upon the complete cell death (CCD) of the S. aureus, as cellular remnants progressively succumbed to dissolution, the aqueous solution underwent self-purification, bringing forth a class of lipid bilayer membrane microspheres containing RNA and proteins. These structures maintained long-term sustainable stability within the thermodynamic storm of water molecules and underwent dynamic size fluctuations over time - collectively exhibited phenomena indicative of being "alive". This study reveals that the cell, upon complete cell death, undergoes reversion to a living entity simpler than the cell itself - the Meta Body (MB). The discovery of MB opens an entire re-conceptualization of what death ultimately brings.

Paper-based colorimetric sensors offer a low-cost and accessible platform for point-of-care (POC) analysis, but enzyme activity loss during coating and drying can weaken analytical signals and require high enzyme loadings or complex immobilization procedures. Although surfactants are widely used to improve wettability in paper-based assays, their potential contribution to colorimetric performance beyond these effects remains unclear. Here, we investigated surfactant-assisted colorimetric signal enhancement in a glucose assay implemented on a 96-puddle paper plate (96-PPP) and identified Tween 20 as the most effective surfactant. Its effect on detection performance became more pronounced as glucose oxidase (GOx) loading decreased; at 0.1 mg/mL GOx, Tween 20 lowered the limit of detection (LoD) from 0.113 to 0.034 mg/mL (approximately 3.3-fold) over a working range of 0-5 mg/mL, despite no statistically significant change in the measured contact angle at this loading. Tween 20 had no appreciable effect on the reaction in solution but preserved 95% of the apparent reaction rate constant after drying, compared with 11% without it, and atomic force microscopy (AFM) revealed a more dispersed dried enzyme morphology on mica. Tween 20-containing sensors also showed slower signal decay during repeated wetting-drying cycles and thermal stress, retained 77% (vs 26%) of the response at 400 mM NaCl, and exhibited within-PPP and between-batch coefficients of variation (CVs) below 10% (vs 12.3-19.5%), while maintaining glucose selectivity over potentially interfering molecules. These results indicate that Tween 20 enhances paper-based glucose sensing beyond wettability, in part by retaining enzyme cascade activity during drying, although the contributions of the individual enzymes and the underlying mechanism remain to be established.

Microplastic pollution from homopolymers such as polypropylene (PP), polystyrene (PS), and polyethylene (PE) poses growing health and environmental concerns, highlighting the need for robust polymer-degrading biocatalysts. We previously identified a naturally occurring cysteine-dependent hydrolase (CsdH) from Rhodococcus opacus, featuring a unique Cys160-Lys127-Asp39 catalytic triad and providing a novel mechanism for polyethylene terephthalate (PET) degradation. In this study, we have determined crystal structures of CsdH in complex with PP, PS, PE, and styrene and demonstrated the potential of the enzyme to directly degrade these homopolymers into their respective low molecular weight degradation products using LC-MS. Structural analysis reveals that the enzyme retains a conserved principal access tunnel while undergoing subtle substrate-dependent changes to accommodate different substrates. The enzyme exhibited broad plastic degradation activity with the highest weight loss observed for PE, followed by PP and PS. SEM analysis reveals surface roughness, cracks and grooves, confirming polymer degradation. Further, these results corroborate through FTIR and TGA analysis. These findings establish a strong foundation for enzyme engineering and aim at developing efficient microplastic degradation.

The unprecedented rise in greenhouse gases such as carbon dioxide (CO2), and their detrimental effects on the atmosphere have intensified the current climate emergency. This challenge has inspired the development of novel carbon capture and utilisation (CCU) technologies, specifically microbial electrosynthesis (MES), for the bioelectrochemical fixation of CO2 into commodity chemical compounds (CCCs) using microbial biocatalysts. In this study, we systematically enriched and maintained robust mixed microbial communities of electroactive bacteria (EAB) from wastewater treatment sludge to serve as biocatalysts for MES. The MES performance of these biocatalysts under different operational conditions in bioelectrochemical systems (BES) reactors were investigated. BES reactors with enriched biocatalysts incubated and maintained under controlled conditions produced higher CCCs yields than those developed at ambient temperatures, while strict anaerobic operations further improved the MES efficiency compared to aerobic conditions. At an applied potential of -1000 mV vs Ag/AgCl, CO2 conversion reached up to 88.11%, significantly outperforming the lower potential (-600 mV) operation. These findings underscore the importance of systematic development of robust and stable biocatalysts, as well as maintaining strict anaerobic conditions, for achieving efficient MES performance, thereby demonstrating the potential of our approach for scalable industrial CCU applications.

Liquid-liquid phase separation (LLPS) driven by intrinsically disordered protein regions underlies the formation of membraneless organelles. The role of these structures in cell biology is an active area of research, yet their physical understanding remains less developed than that of protein assemblies with well-defined, rigid tertiary structures. The amino acid composition of disordered regions, particularly the abundance of charged residues, is known to modulate phase behavior. These factors govern accessible conformations, the assembly of compact sticker clusters, and the porosity of the resulting polymer networks. In contrast, the spatial distribution of side-chain volumes remains a comparatively understudied sequence determinant. Here, we employ a model that captures the patterning of side-chain volumes and interaction strengths without specifying chemical identity to show how sequence blockiness modulates the phase-nucleation propensity, connectivity, and compactness of polypeptide-like polymer assemblies. Using a library of polymers with identical composition but permuted residue arrangements, we show that clustering of bulky residues generates cooperative sticker domains and identify the threshold blockiness required to stabilize polymer networks. Coarse-grained simulations and mean-field theory reveal that this effect arises from an interplay among steric repulsion, solvent entropy, and higher-valency interactions, whereby blocky patterns promote the formation of multi-node percolated networks. Segregation of stickers and spacers is therefore one of the sequence parameters governing LLPS which may be useful for interpreting the evolution of disordered protein sequences, high-throughput proteome screening, and engineering of stimuli-responsive biomaterials. These rules may be exploited to predetermine condensate stability, viscoelasticity, and molecular exchange rates without altering chemical functionality.

Amyloid {beta}-protein (A{beta}), which is known for its role in Alzheimer's disease (AD), is also involved in several physiological functions. Of the two predominant isoforms, A{beta}40 and A{beta}42, the latter is more aggregation-prone and more active in health and disease. In the brain, A{beta} interacts with free lipids, which may affect its assembly pathways. Here, thioflavin T (ThT) fluorescence spectroscopy is combined with molecular dynamics (MD) to investigate A{beta}40 and A{beta}42 co-assembly with free dimyristoylphosphatidylcholine (DMPC) and DMPC/cholesterol (CHOL) lipids. ThT measurements at several protein-to-lipid (PL) ratios show isoform- and lipid composition-dependent kinetics of A{beta} fibril formation with clear isoform-dependent lipid effects at a PL ratio of 1:5. Early co-assembly stages of six A{beta}40/A{beta}42 with DMPC and DMPC/CHOL lipids at this PL ratio are then examined by MD. MD results indicate that lipids alter the secondary structure more and interact more avidly with A{beta}40 than with A{beta}42. In turn, A{beta}40 increases the planar order of lipid bicelles more than A{beta}42. Unlike A{beta}40, A{beta}42 decreases the nematic order of CHOL. In DMPC/CHOL lipids, A{beta}42 but not A{beta}40 exhibits two A{beta}-lipid interaction modes associated with mutually exclusive A{beta}42-lipid and A{beta}42-A{beta}42 interactions. Our MD findings provide a plausible explanation for an experimentally observed increase in the lag time for A{beta}40 fibril formation in DMPC lipids and even more so in DMPC/CHOL lipids that contrasts with much smaller effects of lipids on A{beta}42 fibril formation and offer additional atomistic-level insights into A{beta} co-assembly with lipids amenable to experimental testing.

Pyrogenic black carbon, such as biochar and wildfire char, possesses a reversible electron storage capacity (ESC), allowing it to serve as an electron donor or acceptor for microorganisms. However, not all the ESC is bioavailable, and the proportion available varies by culture. We hypothesized microbes capable of producing soluble redox mediators could access the ESC in biochar interior and thus utilize a higher percentage of the ESC than organisms without a mediator. To test this hypothesis, we grew wild-type Shewanella oneidensis (MR-1) and {Delta}bfe MR-1, a mutant incapable of exporting flavins, on air-oxidized wood biochar. Cell counts and redox titration show that both strains of MR-1 grew to similar cell densities and accessed comparable amounts of biochar ESC (~19%). The addition of exogenous flavin mononucleotide (FMN) yielded no measurable increase in final cell density, due to the strong adsorption of FMN to biochar. SEM images show attachment of MR-1 and {Delta}bfe to biochar surfaces and the presence of nanowires. This study demonstrates MR-1 can utilize biochar ESC for growth, through direct physical contact without the involvement of flavins. Understanding how microbes metabolize biochar provides insight into the impacts and biogeochemical roles of pyrogenic carbon.

Phase separating biopolymers are often described by the sticker-spacer model, which accounts for non-attractive linkers that connect discrete attractive moieties. "Associative polymer" theories describe these systems as two coexisting fluids of stickers and spacers, respectively. In such theories the stickers and spacers are decoupled in the sense that sticker binding does not affect spacer conformations or vice versa. Informed by coarse-grained simulations, we develop a phenomenological mean-field theory to determine the microscopic coupling between the sticker and spacer degrees of freedom. Accounting for linkers connecting adjacent spacers introduces free energy contributions due to conformational entropy of the spacer and the binding combinatorics of the stickers. These contributions have opposite dependencies on spacer length because longer spacers allow a greater volume to search for binding partners but incur a greater entropy cost upon bond formation. The length dependent terms from these contributions cancel leaving a length-independent elastic term arising from the fact that a small amount of spacer stretching lowers the free energy by increasing the number of possible binding partners. The cancellation of spacer length from the theory justifies the decoupling approximation and supports mean-field treatments of heterogeneous spacers.

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

Carbon is a versatile electrode material that is used in applications ranging from electrical energy storage and electrosynthesis to CO2 conversion, H2 production, and biosensing. The development of pyrolytic carbon electrodes derived from lithographically patterned photoresist structures has expanded the possibilities for creating diverse 2D and 3D electrode designs. In this paper, we present disc-shaped SU-8-derived pyrolytic carbon scaffold electrodes with an open hexagonal honeycomb lattice. The scaffolds were fabricated, using embedded 3D printing within a shear-thinning support bath composed of fused silica nanoparticles (7% w/v) in mineral oil. The rheological properties of the support bath were optimized to enable the printing of low-viscosity materials like SU-8, which would otherwise lack structural integrity in standard extrusion-based 3D printing. The SU-8 scaffolds were then pyrolyzed and characterized using SEM, Raman spectroscopy, Energy Dispersive X-ray, X-ray Photoelectron Spectrometry, and Transmission Electron Microscopy, which revealed graphene-like 'microflowers' on its surface. Electrochemical analysis demonstrated excellent electrochemical properties. The functionality of the scaffold electrodes was validated by differentiation of human neural stem cells into dopaminergic neurons on the scaffold surface, followed by real-time detection of dopamine exocytosis upon cell depolarization.

Plant-derived flavonoids show measurable anti-dengue activity in cell culture, but their translational value is limited by a narrow therapeutic window: the concentrations that inhibit the virus approach or exceed those that are cytotoxic. Whether nanoparticle formulation can resolve this constraint, rather than simply add potency, remains untested for a chemically defined fraction. Here we show that biogenic silver nanoparticle (AgNP) formation using a flavonoid-enriched fraction of Carica papaya inverts an unusable selectivity profile into a viable one. The unformulated fraction was cytotoxic below the concentrations required for antiviral activity: its 50% cytotoxic concentration (CC50 = 134.9 ug/mL) lay below its 50% effective concentration against dengue virus serotype 2 (DENV-2; EC50 = 254.4 ug/mL), giving a Selectivity Index (SI) of 0.53. Using the same flavonoids as sole reducing and capping agents produced AgNPs (Z-average 128.4 nm; PDI 0.232; zeta potential -28.4 mV) that moved both parameters simultaneously. CC50 rose approximately 8.6-fold to 1,165.74 ug/mL while EC50 fell approximately 8.8-fold to 29.05 ug/mL, raising the SI to 40.12, an approximately 75-fold shift. Time-of-addition analysis localised the effect to the extracellular phase: inhibition was significant under pre-treatment and co-treatment but not after viral adsorption, identifying the AgNPs as entry inhibitors rather than replication inhibitors. Consistent with a serotype-independent physical mechanism, AgNP treatment at 30 ug/mL reduced viral RNA across all four serotypes, using inocula standardised against WHO-traceable NAAT reference reagents. These findings identify capping chemistry, rather than silver content alone, as a determinant of the therapeutic window in phytosynthesised nanoantivirals.