Proceedings of the National Academy of Sciences

A recently discovered class of protein misfolding involving native entanglements could be a widespread mechanism by which loss-of-function diseases arise. Here, we test that hypothesis by examining if there is any statistical association between proteins predisposed to misfold in this way and a database of gene-disease relationships. We find that globular proteins containing non-covalent lasso entanglements (NCLEs) in their native structure, which are more prone to misfolding, are 61% more likely to be associated with disease, 68% more likely to harbor pathogenic missense mutations, and their misfolding-prone entangled regions are 64% more likely to harbor pathogenic missense mutations. Protein refolding simulations indicate that these disease associated, natively entangled proteins are 2.5-times more likely to misfold than comparable non-disease proteins that lack native NCLEs. These results indicate that native entanglement misfolding, especially in the presence of missense mutations, have the potential to contribute to a wide variety of diseases. More broadly, these findings open an entirely new space of therapeutic targets in which drugs are designed to avoid these misfolded states and increase the amount of folded, functional protein.

Human sentence comprehension proceeds word-by-word, with prior research proposing two central sources of cognitive demand during incremental processing: forward-looking disambiguation of the incoming information stream, and backward-looking retrieval of information associated with previous words from working memory. Recent work has shown that Transformer-based language models successfully generate predictions about sentence processing load in human psycho- and neurolinguistic data by operationalizing disambiguation cost as next-token surprisal, and memory retrieval cost as normalized attention entropy (NAE). Such models, however, remain difficult to interpret as it is not well understood what factors play causally into the decision to assign a cost value to a given word in such artificial neural networks. Here, we present interpretable and cognitively grounded models of disambiguation and memory retrieval and evaluate their neural alignment and spatio-temporal correlates using human magnetoencephalography responses to naturalistic narrative speech. Multivariate temporal response function modeling demonstrates firstly that these human-bias-informed models fare equally well in accounting for observed human language processing data as their Transformer counterparts. This same modeling framework then suggests that surprisal and NAE temporally dissociate in the cortical language network -- surprisal being predictive of bilateral superior temporal gyrus and supramarginal gyrus activation [~]300-500 ms, and NAE being predictive of activity in the same regions, but later [~]750-850 ms. By demonstrating that interpretable neurocomputational models can achieve meaningful brain alignment while maintaining explanatory transparency, this work offers a methodological blueprint for bridging the gap between algorithmic theory and neural implementation.

We study an unexpectedly fast decay of motility in dense suspensions of Escherichia coli bacteria supplied with excess glucose under anaerobic conditions. The decrease in swimming speed occurs on a timescale inversely proportional to the cell concentration, and is associated with the secretion of organic acids by the bacteria. We show that the decay is driven by the progressive accumulation of non-ionised organic acids in the medium, and develop a chemical kinetic model that successfully predicts the swimming speed variations over a range of conditions in the presence of these acids. We further measure the internal pH of E. coli cells exposed to organic acids, and find that the speed decay coincides with sharp declines in internal pH and metabolic rate. Our findings identify an additional layer of motility control that can arise in complex environments even when motility genes are expressed and energy sources are abundant. This mechanism is likely relevant for understanding bacterial motility in habitats such as the human gut, where high densities of bacteria and organic acids are common.

Animals such as bees, ants, wasps, termites, and naked mole-rats live in colonies in which a single queen is the only female reproductive, an arrangement known as eusociality. Eusocial animals are known for their remarkably long lifespans. It has been argued that longevity becomes selected when queens are shielded from "external mortality". While such protection may contribute, we find a deeper reason: the eusocial reproduction strategy itself inherently creates selection for long lifespans. Lifespans typically reflect two processes: the baseline risk of death and the rate at which this risk increases with age. Each is a parameter in the Gompertz mortality equation. We show that the mathematical properties of eusocial reproduction lead to slowly-growing, older populations where selection acts more strongly on the rate at which risk increases than on the baseline risk. In addition, we show that channeling reproduction through a single female also selects for longevity, which we term the "queen effect". Thus, the dynamics of eusocial reproduction select for longer lifespan. More broadly, these results show that reproductive structure and population growth dynamics can fundamentally shape selection on lifespan, with implications outside eusocial systems as well.

The recent movement history shapes motor performance, that is, previous movements can affect current movement characteristics such as trajectory shape. History effects are commonly attributed to carryover of motor-related activity. However, action execution entails sensory feedback; therefore, an alternative is that history effects stem from the sensory information produced by previous movements. To dissociate motor and sensory contributions, we assessed whether history effects emerge from imagined movements, which involve movement planning but not sensory feedback. Overt reaches around an obstacle led to systematic adjustment of the initial reach direction of following reaches - a hallmark of motor history. Imagined reaches around obstacles induced similar biases, albeit with smaller magnitude, presumably due to the need to inhibit overt execution during imagery. By contrast, execution but not imagery induced biases in late, feedback-related measures, suggesting that these history effects depended on sensory rather than motor aspects of the movement history. Thus, motor and sensory signals make distinct and complementary contributions to movement history: recent motor states shape feedforward planning, whereas recent sensory states shape feedback-related movement refinement. Significance StatementRecent movements bias upcoming ones, but these so-called history effects may have their origin either in planning motor commands or in the executed movements sensory consequences. By leveraging motor imagery to retain movement planning but remove movement-related sensory feedback, we show that feedforward, planning-related biases persist without sensory consequences, whereas feedback-dependent biases only emerge from prior sensory feedback. Thus, motor and sensory processes induce specific histories that affect distinct aspects of the current movement.

Symbioses are widespread (1) and underpin the function of diverse ecosystems (2-6), but their evolutionary stability is challenging to explain (7,8). Fitness trade-offs between contrasting intracellular and extracellular niches could act to stabilise endosymbioses because adaptation to either niche is predicted to reduce fitness in the alternate niche, thus reinforcing symbiosis (8,9). Here, we experimentally evolved four diverse Chlorella green algal endosymbionts of Paramecium bursaria to free-living conditions supplying either an amino acid, as provisioned by hosts (10,11), or nitrate, as available in freshwater (12), as the sole nitrogen source. Experimental algal populations adapted to free-living environments, generally increasing in population density and cellular chlorophyll content over time. In one of the four endosymbiont strains, adaptation to the nitrate free-living environment, but not the amino acid environments, drove the loss of fitness benefits to the host in reconstituted symbioses. This loss was not associated with reduced ability to grow on host-provisioned amino acids, nor lost ability to release the sugars provisioned to the host (10,13). Genome sequencing of evolved algal lines revealed genomic divergence between nitrate-adapted and amino acid-adapted lines, affecting genes involved with metabolic organisation and intracellular resource transport. Untargeted metabolomic profiling further showed extensive changes to membrane remodelling and turnover in N-evolved lines. Together, our data support a role for metabolic trade-offs driving divergence between contrasting intracellular and extracellular niches, with nitrogen as a key environmental axis driving divergence. Fitness trade-offs may, therefore, be a general, simple mechanism acting to reinforce symbiosis, contributing to evolutionary stability.

We have curated and annotated the topologic determinants for all human membrane proteins made at the endoplasmic reticulum (ER). This census of 4,863 proteins allowed us to systematically analyze the physical properties of their 20,546 TMDs and flanking soluble regions. Single-pass proteins house the majority of large exoplasmic and cytosolic domains, whereas multipass proteins overwhelmingly contain short loops and tails. All classes of transmembrane domains (TMDs) have positively charged cytosolic flanks, but negatively charged exoplasmic flanks feature primarily on TMDs inserted by Oxa1-family insertases. The TMD-pair, a topologic unit of two TMDs with a short exoplasmic loop, is the dominant building block of multipass proteins. TMD-pairs accommodate high-hydrophilicity and charge-containing TMDs crucial for multipass protein functions. We interpret these context-dependent TMD features in light of current mechanistic models for membrane protein biogenesis and function. Our findings have implications for the evolution of membrane proteomes and for engineering new membrane proteins.

Standard analysis of amyotrophic lateral sclerosis (ALS) clinical trials evaluates therapeutic efficacy by comparing linear slopes of total ALS Functional Rating Scale (ALSFRS) scores between treatment arms. This approach compresses multidomain ordinal data into a single scalar trajectory, discarding distributional structure. When subgroup-level trends differ in timing or direction, such aggregation can attenuate or eliminate them, a phenomenon known as Simpsons paradox. Here we apply Shannon entropy, computed from item-level score distributions within each ALSFRS functional domain following the framework established in [8], to the PRO-ACT database, stratified by treatment arm (Active: n = 4,581; Placebo: n = 2,931; 19 monthly time points). The entropy trajectories of drug-treated and placebo populations diverge visibly and systematically across all four functional domains (Bulbar, Fine Motor, Gross Motor, Respiratory). In the Fine Motor domain, the placebo population reaches peak entropy at month 8 and reverses, while the active population does not peak until month 13, a five-month delay in the populations transit toward functional loss. This divergence is model-independent: it is present in the raw Shannon entropy trajectories before any dynamical model is applied. A permutation test shuffling patient-level arm labels (n = 1,000 permutations) confirms that the total integrated absolute divergence across all four domains exceeds the null distribution at p < 0.001 (observed: 4.48; null: 2.03 {+/-} 0.33; 7.5 standard deviations above the null mean), with Fine Motor (p = 0.001) and Respiratory (p < 0.001) individually significant. The quantity that differs between arms, the shape and timing of the populations distributional evolution, does not exist as a measurable quantity in the total-score linear-slope framework used to evaluate these trials. Whether this signal reflects genuine treatment effects, compositional artifacts from pooling heterogeneous trials, or both cannot be determined from the anonymized public database alone. What can be determined is that the standard ALS clinical trial endpoint makes an implicit assumption, that the distributional information it discards is uninformative, and the present results demonstrate empirically that this assumption is false.

Cellular organelle content is fairly constant within a given cell type. This is accomplished in part by ensuring equitable organelle partitioning during division. Much of our understanding of organelle inheritance has come from investigating cells that divide in half producing two daughter cells. However, more elaborate division strategies that give rise to multiple daughters are not uncommon in nature. Here, we present the first characterization of organelle inheritance in a fungus that grows by multi-budding, producing several (2-20) daughter cells in a single cell cycle. We find that some organelles (mitochondria and ER) are evenly delivered to all growing buds, while others (vacuole and peroxisomes) are more variably inherited. We discuss the implications of even and uneven inheritance for this polyextremotolerant fungus capable of growing in dynamic, and diverse, environments.

During development, embryos store, transmit, and transform information to generate spatial patterns. Positional information (PI) quantifies how precisely cells form patterns at a given time, but cell motion has limited its application to static tissues. We introduce a framework for PI in dynamic tissues by decomposing mutual information between cells positions and properties over time into information flows contributing to PI preservation, loss and generation. These reveal information-theoretic signatures of ubiquitous developmental processes, including instruction, sorting and mixing, directly from data. Applying this framework to whole-embryo cell trajectories in Drosophila, mouse and zebrafish gastrulation, we provide local and global information-theoretic quantification of cell mixing and derive bounds on PI preservation imposed by tissue dynamics. Analyzing tissue flows as dynamical systems, we further show that morphogenesis structures mixing, preferentially preserving specific patterns. Finally, we derive inequality conditions for tracing generated PI to candidate information sources and distinguishing among alternative pattern-formation mechanisms, from programmed extracellular cues to self-organizing intercellular interactions.

Formaldehyde is a highly toxic metabolite that can cause extensive damage to DNA and proteins, and strategies to mitigate formaldehyde toxicity are poorly understood. Methylotrophic bacteria, such as Methylobacterium extorquens, thrive on one-carbon compounds as sole sources of carbon and energy. These organisms are excellent models for discovering formaldehyde stress response systems because formaldehyde is an obligate intermediate in their central carbon metabolism. Here, we characterize an evolved def allele (defevo) that increases formaldehyde resistance in M. extorquens. The def gene encodes peptide deformylase (PDF, EC:3.5.1.88), an enzyme that contributes to protein processing by removing the formyl group from N-formylmethionine (fMet) on nascent peptides. The defevoallele has a single missense mutation that decreases PDF activity both in vitro and in vivo. Transcriptomic analysis of the defevo strain indicates there are pleiotropic effects of this mutation and a differential response to formaldehyde stress. We investigate possible mechanisms for the defevo mutants increased resistance to formaldehyde, including mitigation of formaldehyde-induced protein stress and altered membrane physiology. We find that the defevo allele selectively alleviates exogenous, but not endogenous, formaldehyde stress and identify a tradeoff in heat shock resistance. This study reports the first observation of lowered PDF activity benefiting a cellular physiological phenotype. Our work indicates that altered protein metabolism can mitigate the toxic effects of formaldehyde and furthers our understanding of the strategies that can protect cells from formaldehyde-induced damage. ImportanceFormaldehyde is a toxic chemical that can damage essential molecules inside of cells, yet all organisms inevitably produce it during normal metabolism. Despite its ubiquity, our understanding of strategies for how cells navigate formaldehyde toxicity is incomplete. This study focuses on Methylobacterium extorquens, which naturally generates high levels of formaldehyde as part of its growth on simple carbon compounds. We show herein that a single genetic change, which slows down how newly made proteins are processed during translation, can unexpectedly improve the bacteriums ability to resist formaldehyde stress. Further, we show that this single change has numerous effects on the cell, many of which may contribute to formaldehyde resistance.

Bacterial ribosomal RNAs (rRNAs) are decorated with conserved nucleotide modifications, but the functionality of these modifications is often underexplored. MraW (RsmH) is a 16S rRNA methyltransferase that fine-tunes ribosomal function. We identified a loss-of-function allele in mraW that corrected a late-stage sporulation defect in Bacillus subtilis by bypassing a key sporulation checkpoint via altered translational regulation. Purified ribosomes isolated from {Delta}mraW cells displayed a [~]2-fold decrease in translation efficiency; in vivo, {Delta}mraW cells produced decreased levels of the sporulation checkpoint protein CmpA. This regulation was mediated by sequences from the 5 untranslated region and the coding sequence of cmpA, which form a step-loop structure that occlude early codons of the mRNA. Proteomic analysis revealed that MraW directly or indirectly regulates the production of multiple proteins, some of which form similar structural elements as the cmpA transcript. We propose that MraW modification of 16S rRNA enhances translation efficiency in general, and that specific transcripts, whose gene products are likely required in limiting quantities, have evolved structural features that act as a regulatory mechanism to govern protein levels. This type of regulation may be most apparent in bacteria which exhibit uncoupled transcription and translation. HIGHLIGHTSO_LIA conserved 16S rRNA modification enhances translation of structured mRNAs C_LIO_LIEarly mRNA stem-loops impose translational control dependent on ribosome modification C_LIO_LImRNA structure and rRNA modifications likely co-evolved to fine-tune protein dosage C_LI

The theory of island biogeography and its trophic extensions predict that both species richness and food-web complexity should increase with increasing ecosystem surface area. Accordingly, Species-Area Relationships (SARs) and Network-Area Relationships (NARs) are often observed to be positively-sloped, an observation that came to be considered as a law, and on which rest many area-based conservation plans for biodiversity. However, our mechanistic understanding of the driving mechanisms of SARs and NARs slopes remains limited, undermining our ability to predict how biodiversity will respond to habitat gain or loss. We show in 180 rural ponds sampled across five years that invasive alien predators reversed the SAR and NARs from positive in invader-free ponds, to negative in invaded ponds. Relationship reversal resulted from a higher prevalence of invasive alien predators driving magnified prey extinctions and simplified food webs in larger ponds. The ability of invasive alien predators to reverse SAR and NARs presumably reflected disproportionately high predation rates combined with a low sensitivity to prey extinction conferred by a wide trophic generalism. In a world where virtually all ecosystems face biological invasions, omnipresent invasive alien predators stress the pivotal role played by predation in shaping biocomplexity-area relationships, and highlight a growing need to preserve small ecosystems where invasive alien predators are less prevalent.

Abrupt regime shifts of complex ecosystems between alternative stable states are widespread in nature. Yet, our mechanistic understanding of disturbance-shift-ecosystem functioning relationships remains poor, and it is further unclear whether biotic disturbances can drive such shifts. Using a 5-year pond experiment, we demonstrate that invasion by the red swamp crayfish (Procambarus clarkii) drove a regime shift from a clear-water, macrophyte-dominated, to a turbid, phytoplankton-dominated state. The regime shift was associated with increased water temperature due to increased water turbidity enhanced light absorption, and with a seasonal switch of ecosystem metabolism from hetero-to autotrophy due to decreased respiration in summer, despite constant gross primary production. Reducing crayfish population densities by 44 % failed to move ecosystems back towards their initial state and functioning. Our results stress that biotic disturbances may have hardly-reversible consequences on the biophysical and biogeochemical processes that support ecosystem functioning.

Human Fc receptor-like 5 (FCRL5) is a low-affinity IgG Fc receptor expressed on various B cell subsets and a potential therapeutic target. We discovered that commonly used Fc-silencing mutations, designed to prevent interactions between the Fc{gamma} receptors on immune cells and the Fc domain of therapeutic IgG, do not prevent binding to FCRL5. As a result, unintended interactions between Fc-silent therapeutic IgG and human B cells may occur. We isolated a well-expressed variant of the Fc-binding portion of human FCRL5 by directed evolution and used structural modeling to guide the engineering of a human IgG1 Fc variant with approximately 100-fold higher affinity for FCRL5, enabling us to produce FCRL5:Fc complexes in solution. Native mass spectrometry, size exclusion chromatography, and the crystal structure of the FCRL5- IgG1 Fc complex solved at 3.4 [A] indicate that the two proteins bind in a 1:1 stoichiometry. Furthermore, the structure revealed that FCRL5 binds to IgG1 Fc in a manner completely distinct from that of previously characterized Fc-binding proteins, such as Fc{gamma} receptors, explaining why most Fc-silencing mutations do not disrupt FCRL5 binding. We demonstrate that selective cross-linking of FCRL5 with the B cell receptor (BCR) in cis, using Fc-engineered antibodies with either physiological or enhanced FCRL5 affinity, inhibits Ca2+ flux in FCRL5-expressing B cells. We compare this effect with the selective co-ligation of Fc{gamma}RIIb with the BCR. Our work demonstrates that FCRL5 interacts with human IgG Fc in a distinctive manner and that engagement of FCRL5 by Fc-silent therapeutic IgG could influence B cell function.

Visual surface perception is a fundamental aspect of vision, yet its neural implementation remains poorly understood. Troxlers perceptual filling-in paradigm provides a tractable illusion for studying surface perception, in which a peripheral figure becomes perceptually assimilated into the surrounding background after a period of sustained fixation. Although neural correlates of this phenomenon have been reported in early visual cortex, the underlying mechanisms, particularly the contribution of feedback signaling, remain unresolved. Here we use ultra-high-field (7T) layer-fMRI to investigate perceptual filling-in in the human visual cortex. While experimentally controlling perceptual filling-in, we measured GE-BOLD responses in ten participants. Analyses across cortical depth in the independently localized figure representation in primary visual cortex (V1) revealed neural correlates of filling-in in deep cortical layers, which are associated with feedback input. These findings provide evidence that perceptual filling-in and visual surface perception in general are supported by feedback signals to early visual cortex.

The discovery and collection of the enigmatic Golden Orb by the NOAA Ship Okeanos Explorer and ROV Deep Discover in deep Alaskan waters during 2023 has yielded substantial interest by the scientific and public communities alike. Initial field identifications of the specimen collected at 3,250 meters depth ranged from an egg mass to sponge to microbial biofilm. Here we characterize the biology and ecology of the Golden Orb, as well as other specimens of similar appearance identified since the collection of the original material. Through an integrative taxonomic approach including morphological analysis and genomic characterization of the Golden Orb, we identified the presence of cnidocytes of the spirocyst type (restricted to Hexacorallia), as well as metazoan DNA, from which we were able to derive complete mitochondrial genomes and Ultra Conserved Elements. These results indicate that the Golden Orb and a similar specimen from deep equatorial waters represent remnant cuticles belonging to the geographically widespread deep-sea anemone ally Relicanthus daphneae. We also document the presence of cuticle from a collected specimen of R. daphneae from the Southern Ocean and in situ photographic evidence of similar cuticles beneath living individuals. These findings underscore the extent to which the biodiversity and organismal biology of obscure deep sea fauna broadly remain unresolved and highlight the value of whole-specimen collections and rigorous taxonomic follow-up in telepresence-enabled ocean exploration.

AbstractMicrobial diversity is often assumed to be limited by the number of available resources, yet many communities persist well beyond that expectation. Understanding the mechanisms that enable such coexistence remains a central question in microbial ecology. Here, using a four-species bacterial consortium, we asked whether coexistence can emerge from interactions between species rather than from the external environment alone. Across 31 simple nutrient conditions, including 16 single-resource environments, all four species persisted and repeatedly reached stable coexistence. We then chose 27 additional conditions to further probe the boundaries of coexistence by varying resource concentrations, temporal dynamics, nutrient complexity and relief of auxotrophy-associated dependencies, and only observed the extinction of one species in one of these conditions. Although the community composition in each environment was largely shaped by species fitness on the supplied resources, experimental assays and consumer-resource modeling showed that the coexistence was not explained by resource supply, but rather by cross-feeding and niche partitioning of metabolic byproducts. These metabolic interactions were strong enough to sustain coexistence even for species unable to use the supplied resources directly. Furthermore, robust coexistence across environments appears to be an emergent property of microbial communities, ingrained in members metabolic byproduct profiles and niche differences. Our findings demonstrate how microbes can increase the chemical complexity of their environment sufficiently to maintain coexistence well beyond what is expected from external resource supply. SignificanceUnderstanding the drivers of microbial diversity is essential for managing natural ecosystems and designing synthetic microbiomes. This study challenges the conventional application of the competitive exclusion principle, demonstrating that a four-species consortium can coexist across 31 chemically and metabolically diverse one- and two-carbon source environments. By systematically testing and ruling out alternative stabilizing mechanisms, we show that co-existence is an emergent property of the consortium, sustained by metabolic cross-feeding and niche partitioning. Guided by computational models, we identify hallmarks of robust co-existence in simple environments, including high variance in resource affinities and growth on partner-derived metabolites. Our work demonstrates how microbes modify their environment to sustain high diversity and provides principles for designing synthetic microbiomes that persist across environments.

O_LIDrought is a major abiotic stressor that can restructure trophic interactions by limiting herbivore success and disrupting chemical signaling between plants and natural enemies. In tritrophic systems, plant volatiles guide natural enemy foraging and reproductive investment, often scaling with herbivore density; however, it is unclear whether drought alters this relationship and weakens top-down control. C_LIO_LIUsing a tomato-aphid-ladybeetle system, we tested how drought and herbivore density jointly affect plant VOC emissions, predator behavior, and aphid dynamics. We manipulated water availability (well-watered vs. drought) and aphid density (low vs. high), and measured plant physiology, volatile profiles, predator visitation and oviposition, and aphid responses. C_LIO_LIDrought reduced stomatal conductance, plant biomass, and both total and compositional output of VOCs. Emission of key predator-attracting compounds (e.g., methyl salicylate, {beta}-myrcene) peaked in well-watered, high-density plants but was suppressed under drought. C_LIO_LILadybeetle visitation increased with aphid density but declined under drought, reflecting conserved shifts in volatile cues. Oviposition was concentrated on well-watered, high-density plants and associated with specific compounds (e.g., methyl salicylate, carvacrol), while others (e.g., cymene-7-ol, para, 1-octanol) were negatively associated. C_LIO_LIAphid suppression by predators occurred only under well-watered, high-density conditions. Under drought, aphid growth was already constrained, and predators had little additional effect on their abundance. However, both drought and predator presence influenced aphid demography, increasing production of dispersive alates. C_LIO_LIThese findings underscore the sensitivity of chemically mediated trophic interactions to environmental stress. Increased drought disrupts plant signaling, reducing natural enemy effectiveness, weakening biocontrol, and shifting herbivore population structure. Understanding how stress alters cue reliability is key to predicting community dynamics and managing ecosystem functions under stress. C_LI

Parkinsons disease (PD) is characterized by the aggregation of -synuclein (aSyn) into amyloid fibrils that seed further aggregation and contribute to pathological spreading. Peptides that bind aggregated aSyn are promising therapeutic leads, but their validation is slow, difficult to standardize, and often relies on structural models limited to the ordered cross-{beta} core. Here, we built models of brain-derived full-length aSyn fibrils by extending the Lewy-fold cryo-EM structure with disordered N- and C-terminal segments and sampling the resulting ensembles with the CALVADOS coarse-grained force field. The resulting fibrils display a dynamic fuzzy coat in which the termini, especially the acidic C-terminal tails, form recurrent transient contacts with the core, including the aggregation-prone {beta}5 and {beta}9 motifs. We then used these full-length fibrils in a standardized in silico assay for peptide binding. Simulations of the validated peptide binders PSM3 and LL-37 reproduced their relative binding behavior and converged on a common mechanism in which electrostatic capture by the anionic fuzzy coat precedes stabilization on recurrent P2 and P3 hotspots within the structured core. Control simulations with monomeric aSyn or core-only fibrils showed that persistent association is lost in the absence of the full-length architecture, providing a mechanism for selectivity toward aggregated species. Finally, screening 123 peptides from aSynPEP-DB using a relative contact-based binding score yielded a ranked set of candidate binders and identified net positive charge as the dominant determinant of sustained association, with hydrophobicity acting as a secondary modulator. Together, these results establish full-length, brain-derived fibril ensembles as a practical framework for understanding ligand recognition at pathological amyloid surfaces and for prioritizing therapeutic peptide binders targeting aggregated aSyn. SignificanceParkinsons disease is driven by the assembly of -synuclein into amyloid fibrils, yet most structural models of these aggregates omit the disordered termini that form the fibrillar "fuzzy coat" in vivo. Here we use coarse-grained simulations to reconstruct full-length, brain-derived -synuclein fibrils and show that this fuzzy coat transiently contacts the Lewy-fold core, reshaping access to cross-{beta} surface motifs. Using these ensembles in a computational assay, we recapitulate the relative binding behavior of validated peptide inhibitors and reveal a two-step mechanism in which cationic and amphipathic peptides are first captured by the anionic fuzzy coat and then engage recurrent core hotspots. This framework explains selective recognition of aggregated -synuclein and provides a practical route to prioritize therapeutic peptide binders.