Chemical Science

The LRLLR cell-penetrating motif can be transferred to confer membrane translocation activity, but only to compatible recipient peptides. Using umbrella sampling molecular dynamics simulations, we demonstrate that C-terminal LRLLR addition to the pro-apoptotic smacN peptide eliminates its translocation barrier entirely, transforming a +65 kJ/mol barrier into a -50 kJ/mol energy well. In contrast, N-terminal LRLLR addition to the neuroprotective NR2B9c peptide increases the translocation barrier from +85 to +100 kJ/mol, demonstrating that motif transfer can prove counterproductive for incompatible sequences. Cell-penetrating peptides offer promising strategies for intracellular delivery of therapeutic cargo, yet the sequence determinants governing their activity remain incompletely understood. The LRLLR motif, identified through systematic screening as essential for spontaneous membrane translocation, represents a minimal penetrating element whose transferability has not been previously evaluated. We appended this motif to two clinically relevant peptides: smacN, a tetrapeptide targeting inhibitor of apoptosis proteins in chemotherapy-resistant cancers, and NR2B9c, a nonapeptide that disrupts excitotoxic signaling in ischemic stroke. Potential of mean force profiles calculated across a POPC/POPG bilayer, combined with analysis of hydrogen bonding patterns, secondary structure propensity, and conformational dynamics, reveal the structural basis for these divergent outcomes. Successful transfer to smacN results from favorable complementarity: the hydrophobic, neutral smacN provides an ideal platform for the charged, amphipathic LRLLR motif, yielding a chimera capable of simultaneous interaction with both membrane leaflets. Transfer failure with NR2B9c stems from conformational rigidity induced by intramolecular hydrogen bonding, which prevents optimal membrane insertion, combined with unfavorable positioning of internal polar residues at the bilayer center. These findings establish that cell-penetrating motif transfer requires compatibility in charge distribution, hydrophobicity, and conformational flexibility between the motif and recipient sequence. The smacN-LRLLR chimera emerges as a promising candidate for experimental validation as a membrane-permeable therapeutic for survivin-positive tumors. More broadly, this work demonstrates the value of computational screening to identify compatible motif-cargo pairings prior to experimental investment.

1The formation of protein amyloid fibrils in the brain is a hallmark of various neurodegenerative diseases, including Alzheimer diseases and Parkinson diseases. Amyloid fibrils are highly ordered aggregates in which proteins folded in two-dimensional layers stack along one axis to form elongated linear assemblies. The specific conformations adopted by the proteins within each layer of the amyloid correlates with the pathology. Furthermore, their spreading and templating competency relies on strict in register packing of the folded proteins along the fibril growing axis. There is a need for tools to characterize not only the protein fold across the fibril cross section but also the spatial ordering of the proteins stacked along the amyloid fibril axis. We present an approach based on double electron electron resonance spectroscopy (DEER) using singly labelled tau protein assembled in amyloid fibrils that can deliver an apparent dimensionality of the supramolecular organization of tau fibrils. The parameters of the DEER background function can be used to assess the amyloid core location and packing order, and track time-resolved formation of aggregation intermediates. Showcasing the method on tau, we demonstrate that heparin-induced tau fibrils are mispacked while seeded aggregation can template amyloid fibrils with a higher packing order. This study benchmarks a new method that will provide critical structural insights into amyloid assemblies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/687719v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@8c42c9org.highwire.dtl.DTLVardef@74b0f8org.highwire.dtl.DTLVardef@10e8095org.highwire.dtl.DTLVardef@11bc727_HPS_FORMAT_FIGEXP M_FIG DEER-derived dimensionality parameter differentiates between spin-labelled tau protein in solution, in perfectly aligned fibril or in imperfectly aligned fibril (fibril structure edited from PDB 6qjh). C_FIG

Virtual screening for small-molecule binders is often limited by false positives from approximate scoring functions and rigid-receptor assumptions. These can be addressed downstream through accurate but expensive free energy calculations. At the same time, recent artificial-intelligence-based co-folding methods have been proposed that claim to achieve accuracy of free energy methods at much lower cost, but these have not yet delivered consistent improvements in early enrichment and can be confounded by memorization. Here we address this gap by introducing c(t)-based metadynamics (CTMD), a physics-based, high-throughput hit-triaging protocol tailored for early enrichment. CTMD uses the nonequilibrium reversible-work estimator c(t) introduced by Tiwary and Parrinello (Journal of Physical Chemistry B, 2015 119 736), computed from a small number of short, independent well-tempered metadynamics trajectories, to rank binding stability without requiring converged binding free energies. Across diverse targets and chemotypes, CTMD provides robust early enrichment while remaining fast, transferable with minimal parameter tuning, and resistant to memorization-driven artifacts--underscoring both an immediately deployable physics-based alternative for screening. For these systems we show how co-folding, particularly Boltz-2, achieves enrichment directly proportional to similairty with training set, and more worrying, even in the presence of signficant modifications to active site. Given its simplicity of implementation, CTMD should thus be an "embarassingly" open-source, early enrichment method available for use by the broad pharma and academic community that sits right between approximate but fast docking or AI based co-folding methods, and more expensive but accurate free energy calculations, expected to lead to saving significant financial and human capital in drug discovery campaigns.

The LC3/GABARAP protein family is a promising target for selective inhibition of autophagy and for targeted protein degradation. LC3/GABARAP proteins are challenging targets for small-molecule drug development due to their long, shallow binding grooves. In this work, we evaluate multiple approaches to stabilizing the extended structure of the native binding motif, producing N-methylated peptides and stapled peptides with low nanomolar affinity. A crystal structure and molecular dynamics simulations support a model where the N-methylation pre-organizes the motif into an extended, strand-like structure. N-methylation allowed minimization of the binding motif to a tetrapeptide that retained sub-micromolar affinity while minimizing charge and overall molecular weight. The truncated, N-methylated tetrapeptide showed moderate passive permeability. These results highlight more drug-like space for the development of LC3/GABARAP ligands with high affinity and selectivity.

Long-range protein electron transfer (ET) often depends on tryptophan and tyrosine residues acting as radical relay sites. For example, cytochrome c peroxidase (CcP) generates a W191*+ radical to increase ET from cytochrome c (Cc) to the active center. W191 substitution to Tyr reduces ET rates, but introduction of an adjacent general base at position 232 (as Glu or His) recovers activity. E232 fluorination shifts the ET pH dependence to lower values, verifying that a hydrogen bond elevates the Y191* formal potential for effective ET. Photoinitiated ET between Zn-porphyrin (ZnP) CcP (ZnCcP) and Cc also depends on activating Y191 with a basic residue, but through a different mechanism than for the peroxide-driven system. In ZnCcP, pH dependencies and solvent isotope effects indicate that proton-coupled electron transfer to the basic residue and ZnP*+, respectively, facilitate Y191* formation. Replacing Cc with the irreversible oxidant [Co(NH3)5Cl]2+ isolates distinct protein radicals for characterization by Electron Paramagnetic Resonance (EPR) spectroscopy. Radical distributions reveal that W191*+ lies [~]15 mV in potential below ZnP*+ and that the two radicals exchange on a slow time scale despite their close separation. Remarkably, ZnCcP Y,G191:E,H232 variants propagate radicals differently to peripheral sites depending on the nature of the 232 residue. QM/MM calculations support radical exchange between ZnP*+/Trp*+ and the importance of a hydrogen bond to Y191* for maintaining a high potential to oxidize peripheral donors. These resolved reactivity patterns of CcP/ZnCcP have general relevance for engineering proton management to separate and migrate charge in proteins and potentially other molecular systems.

Huntingtons disease (HD) is caused by expansion of a polyglutamine tract in the huntingtin (Htt) protein, leading to aggregation of the exon 1 fragment (HttEx1) into amyloid fibrils. HttEx1 forms one of the lowest-complexity amyloid cores known, its fibril core consists of a single amino acid, glutamine. With emerging therapies improving patients prospects by silencing expression of HTT, tools to monitor HttEx1 aggregation become essential for timely intervention and next-generation therapeutics. Here, we show that the peptide FibrilPaint1 selectively binds HttEx1Q44 fibrils without interacting with monomeric protein, allowing to measure and trace HttEx1 amyloid fibrils. Using the FibrilRuler assay, we tracked fibril formation from early species to larger clustered assemblies. The non-fluorescent variant, FibrilPaint20, was used to recruit the E3 ubiquitin ligase CHIP to HttEx1 fibrils, enabling site-specific ubiquitin tagging. However, unlike Tau fibrils, ubiquitinated HttEx1 fibrils resisted proteasomal degradation. This reveals a fundamental difference in how amyloids with extremely low-complexity cores respond to cellular clearance machinery. Together, our findings establish the FibrilPaint peptide family as a toolset for the detection and molecular targeting of amyloids, providing new opportunities to study protein aggregation and act as building blocks for future diagnostic and therapeutic strategies in neurodegenerative diseases. HighlightsO_LIFibrilPaint1 selectively binds HttEx1Q44 amyloid fibrils and allows monitoring of fibril growth using the hydrodynamic radius (FibrilRuler). C_LIO_LIFibrilPaint20 recruits the E3 ligase CHIP to Htt fibrils, enabling ubiquitination. C_LIO_LIDespite successful ubiquitination, Htt fibrils resist proteasomal degradation in vitro, highlighting structural barriers. C_LIO_LIFibrilPaint provides a scaffold for functional targeting of amyloids with diagnostic and therapeutic potential. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/695423v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@18acc7corg.highwire.dtl.DTLVardef@1771f3borg.highwire.dtl.DTLVardef@1a35e51org.highwire.dtl.DTLVardef@85270a_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO The FibrilRuler Test: FibrilPaint enables measurement of Huntingtin fibril size during aggregation After a short lag-phase following removal of the protective MBP tag by Factor Xa, fibrillation proceeds rapidly. Subsequent fibril clustering further accelerates growth, leading to exponential increases in aggregate size. C_FIG

Pseudomonas aeruginosa is an adaptable organism, frequently found in chronic infections, and for which antimicrobial resistance is a growing concern. Therefore, there is an urgent need for alternative therapeutic strategies. Cationic antimicrobial peptides (AMPs) offer potent bactericidal activity but suffer from limited selectivity and potential host toxicity. To enhance species-specific targeting, we designed two prodrug variants of the AMP D-Bac8CLeu2,5 - EEEE-D-Bac8CLeu2,5 and ELEG-D-Bac8CLeu2,5 -- engineered for activation by the P. aeruginosa extracellular aminopeptidase PaAP. While both prodrug motifs effectively neutralized the positive charge of D-Bac8CLeu2,5 and prevented DNA-peptide complex formation, EEEE-D-Bac8CLeu2,5 showed negligible antimicrobial activity due to slow and incomplete activation. In contrast, ELEG-D-Bac8CLeu2,5 underwent rapid PaAP-mediated activation, restoring bactericidal activity in planktonic cultures and biofilms. PaAP contributed significantly to complete prodrug activation, particularly within biofilms, where the accumulation of partially activated intermediates correlated with biphasic killing kinetics. The prodrug showed reduced activity against other ESKAPEE pathogens, demonstrating selective activation by P. aeruginosa. Experiments selecting resistant bacteria revealed distinct mutations in lipopolysaccharide biosynthesis pathways for D-Bac8CLeu2,5 and the prodrug, with limited cross-resistance. These findings establish aminopeptidase-activated AMP prodrugs as a promising approach for species-selective antimicrobial therapy and highlight the feasibility of exploiting bacterial enzymes for controlled antimicrobial peptide activation. Table of contents graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/715093v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@4a5505org.highwire.dtl.DTLVardef@13e578org.highwire.dtl.DTLVardef@3e3080org.highwire.dtl.DTLVardef@e24266_HPS_FORMAT_FIGEXP M_FIG C_FIG

Fibrillar protein aggregates are a defining feature of neurodegenerative diseases and are attractive biomarkers and therapeutic targets. However, rational ligand design is limited by a poor mechanistic understanding of fibril binding. This work demonstrates that high-affinity binding to amyloid fibrils occurs via two topologically distinct binding modes, informing design changes that enhance ligand binding. Mathematical models were outlined that demonstrate these binding modes can be distinguished using diagnostic features from standard binding assays. Reanalysis of published binding data indicates that these binding modes are likely widespread amongst common ligand scaffolds. Guided by these binding modes, new ligands were designed with improved binding affinities and distinct fluorescence responses. Together, these findings support the presence of two prevalent binding modes and establish new design principles for enhancing interactions between ligands and amyloid fibrils.

Antimicrobial peptides (AMPs) that also form functional amyloids exhibit remarkable environmental sensitivity, yet the physicochemical rules governing their structural switching remain unresolved. Here, we investigate how surfactant charge and assembly dynamics regulate the antimicrobial-amyloidogenic transition of Uperin 3.5, a 17-residue amphibian AMP with pronounced conformational plasticity. Using an integrated approach combining all-atom molecular dynamics simulations with circular dichroism and thioflavin T fluorescence assays, we systematically probe the effects of surfactant identity, concentration relative to the critical micelle concentration (CMC), peptide stoichiometry and ionic strength. We show that -helical stabilisation and antimicrobial-like behaviour scale directly with surfactant charge: anionic Sodium dodecyl sulphate (SDS) induces the highest helicity in monomeric Uperin 3.5 ({approx}80-90%), followed by zwitterionic dodecyl-phosphocholine (DPC) ({approx}35-45%), while cationic Cetyltrimethylammonium bromide (CTAB) fails to stabilise secondary structure. This charge-ordered trend is mirrored in oligomer remodelling, with SDS driving the most rapid dissociation of {beta}-sheet tetramers, DPC inducing slower partial disassembly and CTAB exhibiting minimal effect. Above the CMC, micellar environments stabilise amphipathic -helical states and efficiently dissolve amyloid assemblies. In striking contrast, under below-CMC conditions, limited SDS availability combined with peptide crowding promotes cooperative aggregation, where surfactant monomers act as dynamic scaffolds that nucleate N-terminal {beta}-sheet interactions--an effect strongly accelerated by physiological salt. Large-scale simulations reveal mixed /{beta} aggregates whose formation is governed by electrostatic screening and surfactant-mediated co-assembly. Together, these findings establish surfactant charge and assembly state as quantitative, environment-dependent regulators of functional amyloidogenesis in antimicrobial peptides. More broadly, they suggest that controlled modulation of membrane-mimetic environments can be exploited to bias peptides toward antimicrobial or amyloidogenic states, offering conceptual avenues for therapeutic strategies targeting peptide misfolding and neurodegenerative disorders.

Cyclic peptides have emerged as a pivotal modality for next-generation therapeutics, due to their superior biocompatibility, high selectivity, and structural stability. While AI-driven peptide design has advanced rapidly, conventional optimization algorithms are often constrained by initialization biases, which impede the efficient exploration of the vast chemical space. Here, we propose a novel methodology that integrates the protein language model ESM-2 with cyclic permutation averaging of embeddings to resolve this bottleneck. This approach establishes a comprehensive "peptide space", a high-dimensional vector representation that encapsulates the physicochemical and structural attributes of cyclic peptides. Our analysis reveals that random sequence selection results in a heterogeneous distribution within this space, potentially underrepresenting specific functional regions. Conversely, navigating this defined peptide space enables the selection of libraries that uniformly span diverse molecular properties. In a proof-of-concept study designing binders for {beta}2-microglobulin ({beta}2m), we demonstrate that initial sequences uniformly sampled from our peptide space yield superior candidates more efficiently than those derived from random selection. Furthermore, this framework facilitates the quantitative assessment of mutational perturbations on global peptide properties, supporting rational decision-making for both broad exploration and local optimization. This "peptide space" concept provides a foundational framework for defining appropriate search boundaries and enhancing computational efficiency in AI-mediated drug discovery. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/710724v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1dd903eorg.highwire.dtl.DTLVardef@128f941org.highwire.dtl.DTLVardef@1041e13org.highwire.dtl.DTLVardef@1527b25_HPS_FORMAT_FIGEXP M_FIG C_FIG

The NAD+-dependent deacetylase sirtuin 1 (Sirt1) is known to regulate the tumor suppressor p53 via deacetylation, but the structural basis of the protein-protein interaction between full-length p53 and Sirt1 has so far remained elusive. We apply an integrated approach, combining structural mass spectrometry (MS) with data-driven molecular docking, to study the interaction between human p53 and Sirt1. Sirt1 was found to bind exclusively to acetylated p53 forming complexes with a 1:1 stoichiometry, irrespectively of p53s oligomeric state. The lysine residue at position 582 (K582) in p53 was identified as predominant acetylation site showing a selective Sirt1-dependent deacetylation at this position. Cross-linking mass spectrometry (XL-MS) provided valuable distance constraints between p53 and Sirt1. Specifically, cross-links created between p53-K382 / Sirt1-K427 and p53-K120 / Sirt1-K622 give hints on a highly flexible interface. Molecular docking was conducted based on the distance constraints imposed by the cross-links, positioning Sirt1 at the DNA-binding and tetramerization domains of p53. This gives a rationale for a steric exclusion of additional Sirt1 molecules binding to p53. We present the first structural model of the full-length p53:Sirt1 (1:1) complex, establishing a mechanistic framework that links p53 activity to its Sirt1-controlled acetylation status.

Summary paragraphThe central dogma of molecular biology describes how genetic information stored in nucleic acids guides the formation of structured proteins from a single molecular alphabet of twenty amino acids (C20)1,2. The extent to which C20 is uniquely capable of forming structural polymers remains a fundamental open question. Here we demonstrate that peptides built from other, "xeno" amino acid alphabets can adopt protein-like secondary structural motifs. Having designed two different xeno alphabets, with them we constructed both combinatorial random sequence libraries and specific, designed 25-mer sequences. We report sequence-dependent structural motifs that result according to circular dichroism, infrared spectroscopy and nuclear magnetic resonance interpreted by molecular dynamics simulations, supported by extensive quantum mechanical calculations. This evidence, including a solution-phase NMR-resolved helical motif, demonstrates that the potential for amino acids to form structure bearing sequences is not unique to lifes alphabet, and thereby reveals a previously unexplored sequence-structure space. Results inform the search for extraterrestrial life, lay foundations for incorporating novel synthetic functional groups and heteroatoms into structure-bearing alphabets, and provide the first truly independent data with which to test and improve all that has been learned about protein folding from the study of lifes 20 side chains.

Assembly-line enzymes carry out multi-step synthesis of diverse metabolites by using a handful of catalytic motifs in which minor structural differences control substrate specificity and reaction order. Here we examine differences in substrate binding to FabB and FabF, the two {beta}-ketoacyl-ACP synthases (KSs) responsible for fatty acid elongation in Escherichia coli, by exploring a peculiar mutational effect. In FabB, a blocking mutation in the acyl binding pocket yields a shifted, but broad product profile, while in FabF, the same mutation disrupts the binding of acyl chains longer than eight carbons (C8). X-ray crystal structures of the FabB mutant provide an explanation: a second, previously unobserved binding pocket allows medium-to-long acyl chains ([≥] C8) to bind with an alternate conformation. Molecular simulations suggest that this pocket is more stable in FabB than in FabF, where mutations reduce the catalytic competency of longer chains instead of shifting them to the alternate pocket. Our findings indicate that homologous KSs differ not only in their primary binding sites but also in the availability of alternative binding modes that can buffer against mutational effects and enable functional diversification.

Emerging fungal pathogens represent a concerning threat to both global health and food security. In this study, we aimed to address our rising vulnerability to fungal pathogens through the development of the Fung-AI pipeline: an AI/ML-driven approach for antifungal discovery. A generative adversarial network (GAN) was trained to generate novel candidate antifungal peptide sequences. Next, in silico antifungal and hemolytic classifiers were built to further prioritize AI-generated peptides for experimental validation. From a pool of [~]10,000 candidates, thirteen peptides were selected for testing over two-stages of experimentation. Five peptides were found to display mild antifungal activity against the wheat pathogen, Fusarium graminearum, with minimal inhibitory concentrations (MICs) ranging from 250 {micro}g/mL to 500 {micro}g/mL. Four of the five peptides also showed activity against the human pathogen, Candida albicans (MIC: 500 {micro}g/mL). Two of our AI-generated antifungal peptides additionally demonstrated low cytotoxicity in HepG2 human liver carcinoma cells (LC50 > 704.2 {micro}g/mL) indicating that they may be useful as scaffolds for future optimization for therapeutic applications. None of our peptides were found to considerably inhibit the emerging pathogen C. auris, suggesting the need for pathogen-specific down-selection of candidate peptides. Overall, we present a proof-of-principle, generative-AI-based approach for the rapid design of de novo antifungal peptides.

Polyketide biosynthesis relies on the conformational adaptability of type II polyketide synthases and accessory enzymes, which direct chain folding and regiospecific cyclization. The aromatase/cyclase TcmN from Streptomyces glaucescensis catalyzes the first two ring closures of tetracenomycin C. Still, the molecular basis by which conformational dynamics regulate substrate binding and product release remains unresolved. Understanding how conformational transitions control ligand recognition and prevent aggregation is crucial for deciphering the molecular bases of polyketide biosynthesis and for guiding engineering strategies to synthesize novel natural products. Here, we investigated how ligand interactions modulate the conformational equilibrium of TcmN and the mechanistic consequences for catalysis. Using NMR spectroscopy (STD, CSP, relaxation dispersion), calorimetry, molecular docking, and microsecond-scale molecular dynamics simulations, we mapped the conformational ensembles of apo TcmN and its complexes with naringenin (a substrate/product analogue) and intermediate 12 (INT12). Apo TcmN samples both open and closed conformations. Naringenin preferentially stabilizes the closed state, a conformation thought to protect hydrophobic residues from solvent exposure. In contrast, INT12 shifts the equilibrium toward the open state, characterized by an expanded cavity that permits substrate entry, product release, and accommodation of extended intermediates. Hydrogen-bond analysis highlighted conserved catalytic residues (R82, E34, Q110, T133) as key anchors for productive poses. These results establish that TcmN functions through a ligand-gated breathing mechanism, in which successive intermediates selectively tune the cavity volume and shape, balancing catalytic efficiency with protection against aggregation. Conformational adaptability emerges as a central determinant of aromatase/cyclase function, providing molecular insights relevant for polyketide biosynthetic engineering. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/708631v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@5646aorg.highwire.dtl.DTLVardef@39016org.highwire.dtl.DTLVardef@1e8c285org.highwire.dtl.DTLVardef@3aba20_HPS_FORMAT_FIGEXP M_FIG C_FIG

A{beta}40 and A{beta}42 peptides differ by just two C-terminal residues, yet they display strikingly different aggregation and toxicity profiles. Whether this distinction is already encoded at the monomer level is still under debate. Here, we combine extensive all-atom simulations in explicit solvent, well-tempered metadynamics, and a tailored consensus cluster analysis to compare the monomeric ensembles of the two isoforms under identical conditions. Both peptides populate broad, coil-like conformational distributions; however, A{beta}42 shows systematically higher {beta}-structure propensity, especially in the C-terminal region, and samples more extended conformations with higher hydrophobic exposure compared to A{beta}40. These results support a mechanistic link between sequence-encoded monomer conformational preferences and the differential amyloidogenicity of the two isoforms, highlighting monomer-level determinants of A{beta}42s distinct aggregation behavior.

Therapeutic peptides combine high target specificity with potent biological activity.1 However, treatment success is often limited by rapid clearance and the need for frequent injections.2, 3 This challenge is particularly acute for therapeutic peptides used in obesity, where clinical benefit must be balanced against dose-dependent adverse effects. In nature, these constraints are overcome by storing hormones as reversible fibrils,4 but pharmacokinetic control is essential for widespread adoption of bio-inspired self-assembled depots for therapeutic peptides. Here, we show that tuneable pharmacokinetics can be achieved and modelled by mapping the fundamental chemical parameters of reversibly self-assembly in vitro. We demonstrate this approach for the amylin analogue pramlintide. Amylin analogues are under development for the next generation of diabetes and obesity treatments, with improved mechanism of action e.g. preserving lean body mass.5-8 Pramlintide is an approved drug with a well-established safety profile, however, it has a comparable half-life to native amylin.8-12 In a pilot study, we achieve in vitro-in vivo correlation, increasing the half-life of pramlintide 20-82-fold in rats, while controlling burst release. These findings demonstrate that the optimisation of pharmacokinetics can be decoupled from peptide engineering, establishing a generalisable framework for generating long-acting peptide formulations by emulating native storage mechanisms.

Antimicrobial peptides (AMPs) are emerging as promising alternatives to conventional antibiotics, and growing evidence indicates a fundamental link between antimicrobial activity and amyloid-like self-assembly. Many AMPs are known to form amyloid-like fibrils, while several amyloidogenic peptides exhibit intrinsic antimicrobial properties, suggesting shared underlying physicochemical determinants such as amphipathicity, {beta}-sheet propensity, and charge distribution. However, the rational design of peptides that simultaneously encode these dual functionalities remains a significant challenge. Here, we present amyAMP, a generative deep-learning framework based on a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), designed to learn and generate peptides with integrated antimicrobial and amyloidogenic properties. Trained on curated datasets of antimicrobial and amyloid-forming peptides, amyAMP captures the latent sequence-property relationships governing dual functionality. Statistical and latent-space analyses demonstrate that the generated peptides closely overlap with biologically relevant peptide space while remaining distinct from random sequences, indicating successful learning of key biochemical features. To validate functional behavior, we performed extensive coarse-grained molecular dynamics simulations to probe membrane interaction, peptide self-assembly, and membrane disruption. The simulations reveal rapid membrane adsorption, stable amphipathic insertion, and strong peptide-peptide aggregation. Notably, cooperative clustering of peptides on membrane surfaces induces membrane thinning and curvature perturbations, highlighting a mechanistic coupling between aggregation and antimicrobial activity. Collectively, these results establish that amyAMP effectively captures the shared physicochemical principles underlying antimicrobial action and amyloid-like self-assembly. This work provides a generalizable framework for the AI-guided design of multifunctional peptides to advance the development of next-generation therapeutics targeting antimicrobial resistance.

Pathological seeding of protein misfolding is a hallmark of proteinopathies. However therapeutic strategies to clear these aggregates are lacking, impairing both study of their biological importance in disease etiology and progression as well as development of therapeutics. This is due in part to the need to selectively clear oligomerized proteins whilst leaving functional monomers intact, as well as the challenge of developing molecules that act on the full complement of misfolds the protein can adopt throughout the course of disease. In this work, we describe a dopant system consisting of an engineered alpha-synuclein protein construct that rapidly co-aggregates into existing WT alpha-synuclein oligomers, enabling rapid degradation of the entire assembly in the presence of a small molecule trigger. This work provides proof-of-principle for an approach that transforms pathological seeding from a disease-driver into a therapeutic vulnerability, and is potentially applicable to any proteinopathy without requiring a small molecule binder of the pathologic species.

The chemical basis underlying the striking blue hue of live H. americanus, known as American lobster, are studied in evolutionary biology and in polyene physical chemistry. Carapace colouration is generated by the antioxidant astaxanthin bound within the carotenoprotein crustacyanin complexes. Here, we present the ex vivo structure of the most abundant -crustacyanin and {beta}-crustacyanin forms, determined respectively by cryo-electron microscopy and X-ray crystallography to a resolution of 2.75 [A]. Our structural analysis reveals -crustacyanin as an elongated arrangement of {beta}-crustacyanin heterodimers tethered by an heptatricopeptide repeat (HPR) protein. In vitro complex formation between the {beta}-crustacyanin unit with a synthetic heptatricopeptide reproduces the observed blue colour of -crustacyanin, identifying the HPR protein, in concert with crustacyanins, as contributor in tuning carapace colour. Overall, these results explain how nature adjusts the colour across the entire visible spectrum by exploiting the bathochromic shift of astaxanthin from its unbound red form ({lambda}max = 472 nm) firstly to the {beta}-crustacyanin violet bound form ({lambda}max = 591 nm), and then to the -crustacyanin bound blue form ({lambda}max = 631 nm).