ACS Central Science

Immunotoxins (ITs) are potent targeted cancer therapeutics that couple tumor-selective receptor binding with efficient intracellular delivery and cytotoxic enzymatic activity of bacterial toxins. While ITs have shown impressive efficacy in hematologic malignancies, dose-limiting toxicity remains a major barrier to their broader clinical application, particularly in solid tumors. The exceptional potency of immunotoxin payloads contributes to off-tumor toxicity because even limited uptake by receptor-low cells can be sufficient to cause cell death. Here, we systematically investigated how receptor-binding domain (RBD) affinity and avidity interact with catalytic payload activity to determine IT selectivity. Using CD123-, HER3-, and HER2-targeted ITs, we found that increasing receptor-binding affinity or avidity altered potency but provided limited control over the selectivity between receptor-high and receptor-low cells. In contrast, attenuating catalytic activity produced profound gains in selectivity when payload potency was appropriately matched to receptor engagement. The optimal level of attenuation varied with receptor context and toxin scaffold, demonstrating that maximal selectivity emerges from balancing cellular delivery with catalytic activity rather than maximizing either property alone. In vivo, payload attenuation increased the maximum tolerated dose of a HER2-targeted IT by 400-fold and enabled robust antitumor activity well below its toxicity limit, whereas the WT counterpart showed no detectable efficacy at tolerated doses. Together, these findings uncover and establish payload activity as a tunable determinant of immunotoxin selectivity and provide a framework for matching receptor engagement with catalytic potency to develop safer and more broadly applicable targeted toxins.

Proteolysis-targeting chimeras (PROTACs) promote targeted protein degradation by inducing a transient ternary complex between a protein of interest and an E3 ubiquitin ligase. Despite the clinical promise of these event-driven therapeutics, defining the conformational landscape and interfacial organization of these complexes remains challenging. Here, we use an integrated native mass spectrometry (nMS) approach combining ion mobility, surface-induced dissociation (SID), and variable-temperature electrospray ionization (vT-ESI) to determine how small-molecule architecture shapes the structural and thermodynamic landscapes of bromodomain-containing protein 4 (BRD4) with the VCB E3 ligase complex. Using a set of PROTACs that differ in targeting ligand identity (JQ1 versus I-BET726) and PEG linker length, ion mobility measurements show that shorter linkers constrain the ternary complex into more extended topologies, whereas longer, more flexible linkers allow dynamic sampling of relaxed, native-like conformations. SID directly probes noncovalent interfaces and shows that JQ1 complexes favor prompt PROTAC ejection, whereas tighter-binding I-BET726 complexes are more likely to retain the PROTAC at the interface. Complementing these kinetically-controlled gas-phase measurements, vT-ESI reveals a monophasic melting transition for a JQ1-mediated complex and a distinct biphasic melting profile for an I-BET726-mediated complex. The gas-phase activation measurements revealed targeting-ligand-driven differences in PROTAC ejection and retention, whereas vT-ESI uncovered distinct temperature-dependent disassembly pathways for the matched-linker-length JQ10L and IBET10L complexes. Together, these complementary techniques show how PROTAC architecture influences ternary-complex conformation, interfacial connectivity, and disassembly.

Self-labeling protein (SLP) tags enable versatile labeling of proteins in live cells, yet only two SLPs are commonly used, limiting multiplexing. Here, we repurposed the oncoprotein K-Ras(G12C) and its covalent inhibitors to create a third, orthogonal SLP system. We used a deep-learning-based approach to radically redesign the sequence of K-Ras(G12C) while preserving its covalent-inhibitor binding pocket. Our top design, LUCI-tag, is a 19 kDa, monomeric, thermostable SLP that rapidly and covalently reacts with commercially available K-Ras(G12C) inhibitors bearing diverse payloads. Unlike existing SLPs, LUCI-tag exhibited payload-agnostic labeling kinetics, outperforming HaloTag7 and SNAP-tag for a negatively charged payload. X-ray crystal structures of drug-bound and drug-free LUCI-tag showed the design was structurally accurate and contained a preorganized inhibitor-binding pocket that could explain its rapid labeling kinetics. Proteomics and cell-signaling experiments confirmed LUCI-tag is biologically inert. LUCI-tag enabled rapid, wash-free, live-cell imaging and simultaneous three-color multiplexed experiments with HaloTag7 and SNAP-tag. This work establishes LUCI-tag as an immediately useful orthogonal SLP and demonstrates that covalent drug-target pairs can be repurposed into a broadly applicable platform for protein labeling.

Cytokines can elicit potent antitumor immunity, but their clinical use is often limited by systemic immune activation and dose-limiting toxicity. Protease-responsive masking offers a way to improve selectivity by linking cytokine activity to disease-associated protease cleavage, but current approaches have faced several challenges. Here we describe a de novo protein design strategy for generating protease-activatable cytokine prodrugs that overcomes these challenges. We use this strategy to design and characterize cytokine prodrugs and well-behaved AND-gated split systems that require both target-dependent colocalization and proteolytic unmasking to generate active cytokines. In challenging syngeneic tumor models, our IL-21 prodrugs reduced treatment-associated toxicity while maintaining antitumor efficacy.

We describe the concept for a new modality to create multi-specific therapeutics that utilizes modified nucleic acids as a scaffold to concatenate multiple warheads (hence called 'catamers'). Catamers are assembled via Watson-Crick interactions into multi-specific molecules from individual components such as ligand-binding modules, protease-cleavage sites, and toxins. Each warhead is covalently bound to an oligonucleotide, which in turn is connected to the catamer scaffold. Post-synthesis of the individual catamer components, they are annealed together such that Watson-Crick base pairs on the oligonucleotides dictate the organization of the warheads on the complete catamer. Notably, catamers are not aptamers, though they can contain aptamers as warheads, along with small molecules and peptides. By design, catamers are intended to address three key problems that have hamstrung the field of multi-specifics: (i) optimization rate; (ii) manufacturing cost; and (iii) unpredictable immunogenicity (Amash et al., 2024 PMID: 39189686). Catamers are purely synthetic and do not require cultured cells to produce. These advantages are based on the underlying design of the catamer and will require experimental validation in future studies. As a proof-of-concept catamer, we focus on a prostate-specific membrane antigen (PSMA)-targeted toxin conjugate. In molecular simulations, this catamer displays structural characteristics to support its intended pharmacology. Importantly, the design addresses one of the key shortcomings of antibody drug-conjugates (ADCs): off-target toxicity caused by release of the toxin after pinocytosis by healthy cells in contact with the blood.

N-linked Fc galactosylation drives variability in therapeutic mAb quality, affecting complement-dependent cytotoxicity and ADCC. Current control strategies suffer from narrow ranges, productivity loss, or unwanted glycoforms. Here, we combine metabolic and cellular glycoengineering by feeding 2-deoxy-2-fluorogalactose (2FG) to CHO cells engineered for hypergalactosylation via COSMC knockout and {beta}4-galactosyltransferase overexpression (C /GT+), achieving broad, tuneable control of Fc {beta}4-galactosylation. In DP12 C-/GT+ cells, a split-feed regimen spanned a wide galactosylation range (95-46%) but generated substantial aglycosylated and Man5 glycoforms. The same regimen in a second host, VRC01 C-/GT+, gave only a narrow range, indicating 2FG dosing does not transfer directly across cell lines. Based on a proposed mechanism where 2FG is metabolised via the Leloir pathway into inhibitory fluorinated nucleotide-sugar intermediates, we developed a cell-normalised, multi-bolus feeding strategy that substantially broadened control in VRC01 C-/GT+ cells while suppressing aglycosylation and Man5 formation. In a fed-batch Ambr(R) 250 process, this strategy achieved comparable galactosylation reduction with roughly ten-fold less 2FG, showing that the fraction of mAb secreted after feeding is a key determinant of control strategy efficiency. Across the resulting glycoform range, Bio-Layer Interferometry identified Fc {beta}4-galactosylation as the strongest correlate of Fc{gamma}RIIIA (CD16a) binding affinity (R2 = 0.92). Together, these findings establish combined metabolic and cellular glycoengineering as a platform for controlling mAb galactosylation across a broad range, with potential to fine-tune downstream pharmacological activity.

COVID-19 highlighted the need for antivirals that can be rapidly deployed against both current and future coronavirus threats. CMX990 is a clinical stage coronavirus main protease (Mpro) inhibitor bearing a unique trifluoromethoxymethyl ketone warhead. Here, we broadly evaluate its pan-coronavirus target engagement, antiviral breadth, and pharmacologic differentiation. Across a reporter panel of 24 Mpro enzymes spanning alpha-, beta-, delta-, and gamma-coronaviruses, CMX990 retained robust potent activity, including against nirmatrelvir-resistant SARS-CoV-2 variants. In direct comparison, nirmatrelvir and ensitrelvir showed diminished potency against non-SARS-CoV-2 coronaviruses. Live-virus assays corroborated this breadth, with potent, selective activity against SARS-CoV-2, SARS-CoV-1, MERS-CoV, and additional human coronaviruses. Structural studies revealed a conserved covalent binding mode centered on the catalytic Cys of coronavirus Mpro. In serial-passage studies, resistance emerged only after approximately twice as many serial passages under CMX990 selection as under nirmatrelvir selection, without selecting for the canonical nirmatrelvir-resistance substitution E166V. Extracellular washout experiments revealed superior persistence of antiviral activity relative to nirmatrelvir, consistent with durable target engagement. In a murine SARS-CoV-2 infection model, once-daily CMX990 protected against weight loss and reduced lung viral titers to near baseline levels. Collectively, these findings identify CMX990 as a structurally and functionally validated pan-coronavirus protease inhibitor supporting its potential as a pandemic-ready antiviral candidate.

Electrochemical aptamer-based (EAB) sensors have emerged as a promising framework for reagentless, real-time molecular monitoring in complex biological matrices. Signal transduction in a prominent benchmark system--targeting aminoglycoside antibiotics--has been nearly universally attributed to target-specific, binding-induced conformational changes that modulate the distance between a redox reporter and the electrode surface. Here, using a suite of interfacial electrochemical and optical characterization methods, we systematically show that charge-screening, not structure switching, dominates the signaling mechanism in the case of the aminoglycoside EAB sensor. First, we demonstrate that the legacy aminoglycoside sensor sequence exhibits apparent affinities and relative electron kinetic modulations similar to unrelated control sequences, including generic stem-loop hairpins, unstructured poly-T sequences, and short duplexes. Multi-modal validation via bio-layer interferometry (BLI), circular dichroism (CD), and fluorescence spectroscopy confirms that this promiscuous target association occurs across disparate DNA sequences and without detectable conformational reconfiguration. Further investigation via charge-scaling polyamine assays and on-electrode fluorescence imaging demonstrate that the dominant signal transduction mechanism in these sensors is instead driven by macro-scale electrostatic backbone charge-screening.

Azo dyes are widespread in the environment, and humans ingest a range of these dyes present in food and drugs. The human gut microbiome significantly impacts the fate of ingested azo dyes primarily through the reduction of the azo bond (R-N=N-R'). Flavin-dependent azoreductases have been considered the key enzymatic drivers of this process. To challenge this paradigm, we constructed a sequence similarity network of known azoreductases and focused on AzoA of Klebsiella pneumoniae, a central representative within the gut microbiome cluster. Unexpectedly, K. pneumoniae AzoA displayed relatively low in vitro activity against a range of azo compounds. While the physiological implications remain unclear, these findings are consistent with the possibility that non-enzymatic mechanisms contribute substantially to azo compound reduction in the gut. Furthermore, structural characterization of AzoA, as a holoenzyme and in its substrate-bound state, revealed a previously unrecognized ligand-coupled mechanism involving remodeling of the active site and oligomeric state.

The ability to map protein interactomes and organelle proteomes is foundational for achieving a molecular understanding of living cells. Proximity labeling (PL) provides a powerful strategy for this, but existing enzymes and photocatalysts are limited by their spatial resolution, reliance on biotin, and/or in vivo compatibility. Here we report FlexID, an engineered promiscuous ligase that catalyzes the rapid attachment of diverse small-molecule probes to proximal endogenous proteins. Critically, FlexID operates through a zero-radius, direct-contact mechanism, offering superior spatial precision compared to existing PL tools. We engineered FlexID by combining the strengths of sequence- and structure-trained computational models to enhance its catalytic activity and structural stability. Biophysical analysis revealed that specific conformational changes in FlexID improve its ability to recognize diverse target proteins while simultaneously preventing the premature release of the reactive intermediate. We demonstrate FlexID's versatility through in vivo proximity labeling, comprehensive organelle proteome mapping, and a high-throughput, fluorescence-based screen for molecular glues. Our work shows that computational methods can be harnessed to create mechanistically distinct PL enzymes and establishes FlexID as a flexible, high-resolution tool for mapping protein interactions and proteomes in living cells.

NOS1AP is a genetically validated driver of tau pathology in Alzheimer's disease (AD), yet the NOS1AP-tau interaction itself has remained pharmacologically untargeted. We report CAPTOR-1, a first-in-class small molecule that disrupts this interaction by binding a pocket in the N-terminal region of NOS1AP (residues 1-126). A drug-resistant NOS1AP Y16A/F42A variant that retained tau binding but exhibited a 78-fold reduction in CAPTOR-1 affinity provides genetic evidence supporting an on-target mechanism. In human iPSC-derived neurons, CAPTOR-1 dose-dependently reduces endogenous NOS1AP-tau association, tau seeding activity, and pathogenic tau phosphorylation, phenocopying genetic NOS1AP knockdown; these effects extend to neurons from patients with sporadic AD. Orally dosed CAPTOR-1 crosses the blood-brain barrier and engages NOS1AP in brain dose-dependently. Chronic oral dosing rescues pathology, synaptic function, and memory in a tauopathy model (PS19) and an amyloidosis model (APP/PS1), sparing wild-type littermates in both. This work establishes pharmacological disruption of the NOS1AP-tau interaction as a viable, disease-modifying strategy for AD and positions CAPTOR-1 as a biomarker-ready chemical probe (pTau217, neurofilament light) for translational studies.

We aimed to repurpose the non-nucleoside reverse transcriptase (RT) inhibitor (NNRTI) rilpivirine (RPV) as a targeted protein degrader (TPD) of HIV-1 RT. Structure-guided modeling identified a TPD bifunctional linker exit trajectory from RPV that threads the NNRTI entrance channel. Ten RPV analogs (RPV') with varied warhead-linker attachments retained RT inhibition and antiviral activity, guiding selection of an amide-linked connector for degrader construction. We synthesized Proteolysis Targeting Chimeras (PROTACs) designed to recruit CUL4CRBN and CUL2VHL, alongside adamantyl acetic acid-based Hydrophobic Tags (HyTs). TPDs were evaluated for RT inhibition, virus inhibition, biophysical target engagement, and proteasome-dependent degradation. Some PROTACs showed minimal antiviral activity or limited solubility for our assays, whereas the HyT with a tetraethylene glycol (PEG4) linker (PEG4-Ad) exhibited low nanomolar potency to suppress HIV-1 replication and acceptable solubility. PEG4-Ad reduced RT levels in a proteasome-dependent manner without cytotoxicity but did not exhibit superior potency against RPV resistance mutations. MD simulations suggested that PEG4 linkers maximize episodic exposure of the hydrophobic tag, consistent with PEG4-Ad efficacy. These data highlight the promise - and constraints - of antiviral degraders, indicating that linker-controlled hydrophobic tag exposure and subcellular target accessibility may be critical design parameters for prospective therapeutics.

Methotrexate (MTX) is a narrow-therapeutic-index drug widely used in cancer and autoimmune disease treatment, for which delayed clearance can cause severe toxicity and requires close therapeutic drug monitoring. Here, we integrate high-stringency Capture-SELEX, biophysical characterization, molecular modeling, mutational validation, and electrochemical transduction to develop two structurally distinct MTX-binding DNA aptamer families. Full-length 3315 and 930 bound MTX with apparent KD values of 89 and 408 nM, respectively. Systematic truncation generated compact functional variants: 3315-55 retained 63 nM affinity and broad buffer tolerance, whereas 930-65 reached an apparent KD of 44 nM in 10 mM Mg2, revealing markedly different ion dependencies. Biolayer interferometry confirmed rapid and reversible MTX recognition, while 3315 variants retained binding in serum-containing buffer. Computational analysis and site-directed mutagenesis identified distinct recognition architectures: a compact G-rich scaffold coupled to a central binding interface in 3315 and a localized Mg2+-stabilized binding pocket in 930. Methylene blue-labeled 3315-55 and 930-65 were integrated into electrochemical aptamer-based sensors, producing concentration-dependent responses to 100-1000 uM MTX in PBS, discriminating MTX from folic acid, and responding to MTX directly in undiluted human blood. Together, these results establish a structure-guided workflow linking aptamer discovery, mechanistic validation, and electrochemical translation, providing new molecular recognition elements and a foundation for future reagent-less MTX therapeutic drug monitoring.

Fluorescent proteins (FPs) are the workhorse of modern-day cellular imaging and biosensing. However, rationally predicting and engineering the photophysical properties of FPs remain challenging, as these are governed by complex three-dimensional microenvironments and post-translational modifications. Here, we present a novel surface-mutation-guided engineering strategy combined with iterative rounds of rational mutagenesis to improve key photophysical properties of red fluorescent proteins (RFPs). This approach generated two bright, monomeric RFP variants from the mFruits lineage, mCranberry and mCranberry2, with quantum yields of 85% and 80%, respectively. Strategic incorporation of charged amino acid residues on the protein surface enhanced fluorescence quantum yield without compromising photostability. Comprehensive photophysical characterization and live-cell microscopy demonstrate enhanced performance of these variants and establish their utility as robust probes for fluorescence imaging. However, the exact mechanism of such improvements is subject to further investigation. Collectively, this work introduces a strategy for optimizing fluorescence properties and provides a framework that may be broadly applicable to other pigment-protein systems such as genetically encoded metal-ion indicators and photosynthetic light-harvesting complexes.

Massive library-based platforms enable rapid early hit discovery, yet subsequent hit resynthesis and validation remain major bottlenecks in drug discovery. This delay is amplified when optimizing hits, or elaborating structures towards more advanced modalities, such as chemical inducers of proximity (CIPs). Here, we report PROXINAUT, an end-to-end workflow integrating self-encoded library-based hit discovery with an automated parallel solid-phase synthesis platform to streamline hit discovery, validation, optimization, and degrader development. As a demonstration, screening a 176k-member benzimidazole library against BRD4 yielded six hit candidates, which were obtained via parallel automated synthesis and validated as submicromolar binders. The automation workflow empowered a rapid structure activity relationship exploration around the whole scaffold and resulted in a variant with six fold improved binding affinity. Next, we aimed to automatize the development of bifunctional degraders. Solid phase synthesis typically leaves a C-terminal amide as a synthetic artifact that can compromise druglike properties. We developed a strategy to repurpose this resin-attachment site, converting it into functional degrons featuring either FBXO31-targeting C-terminal amides or cereblon-binding cyclic imides. Operating without human intervention, our automated platform executes up to 16 synthetic steps across multiple parallel structures, enabling true de novo synthesis of full bifunctional scaffolds, where ligand, linker and E3 recruiter variations can all be explored within the same workflow. This resulted in cell-active BRD4 degraders with subnanomolar to nanomolar potency. Overall, we show how library selections can merge with multi-step parallel automation to convert hits directly into validated leads and advanced degrader modalities.

Fixed-backbone sequence discovery, or inverse folding, is a critical recurring task in the development of new polypeptide therapeutics. Once promising backbones are established for a target pocket, computational inverse folding methods greatly help accelerate generation of candidate sequences. Such methods are mature for the traditional case of limiting to the fixed twenty-letter canonical vocabulary; however, they cannot access the broader space of non-canonical amino acids (NCAAs). This design constraint is exacerbated for peptide binders, a fast-growing modality that readily incorporates NCAAs, though in practice non-canonical design frequently depends on laborious medicinal-chemistry campaigns. An extension of inverse folding to NCAAs is thus critical to accelerating design of novel therapeutic peptides. AtomWeaver uses a joint all-site, atom-level generative scheme that does not restrict side-chain categorical assignment by either predetermined or co-resolving residue identity. Conditioned only on a fixed peptide backbone and its target protein, its multi-component flow guides side-chain atoms as unlabeled points in R3 from a nested shell prior to a variable-count final atom cloud. Identity is then read by matching each predicted cloud against a reference library of canonical and non-canonical templates. Since identity is decided only at decode time, the addressable vocabulary is a property of the library rather than of the trained weights: a new NCAA costs one reference structure and no retraining, and the model can select residues it was never prompted for and never saw in training. On a deep mutational scan of two peptide-target systems, AtomWeaver's canonical readout shows high observed mean agreement with experimental values among the compared inverse-folding methods. In the mixed canonical-noncanonical setting that canonical-only baselines cannot support at all, it likewise retains ranking signal across both systems. AtomWeaver also displayed self-consistent designs on de novo binder backbones, with the highest interface confidence among compared methods. Notably, it reached these metrics while achieving broad empirical coverage of our 300-residue vocabulary, including four non-canonical types never visible in training. AtomWeaver thus serves canonical and non-canonical peptide design alike, while transforming residue vocabulary to an expandable inference-time choice.

A broad-spectrum antiviral is required to enable rapid intervention against current, newly emerging and mutating viruses. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), Sindbis virus (SINV) and chikungunya virus (CHIKV) all engage negatively charged moieties on host cells, such as heparan sulfate (HS) and sialic acid, to facilitate attachment for entry and infection. We designed HS-mimetic nanoparticles in the form of polymer vesicles (polymersomes) by blending membrane-forming and sulfonated copolymers. These biocompatible polymersomes successfully inhibited host cell infection of HS-dependent SARS-CoV-2 and HS-independent IAV in vitro with sub-nanomolar potency. Multivalent interaction of several virus ligands with a single polymersome as quantified by fluorescence correlation spectroscopy likely contributes to their potency. The sulfonated polymersomes also functioned in vivo as demonstrated by a reduction in the spread of SINV, an alphavirus model for CHIKV, in zebrafish embryos, which led to a significantly increased survival. Hence, our polymersomes could form the basis for an urgently required multifunctional broad-spectrum antiviral nanomedicine.

Antibody-oligonucleotide conjugates (AOCs) offer a promising solution to delivery challenges of therapeutic oligonucleotides. However, the relationship between their complex chemical architectures and biological activity remains poorly understood, limiting the development of important structure-function relationships. For siRNA-containing AOCs, increasing the siRNA-to-antibody ratio beyond one (drug-to-antibody ratio, DAR>1) reduces potency, attributed to altered pharmacokinetics arising from increased negative charge density. Here, we investigated whether simple chemical modifications could improve AOC efficacy and mitigate limitations associated with higher DAR. Introduction of a single C16 lipid modification to the siRNA significantly enhanced target gene silencing compared to the unmodified AOC. Extending this modification to a DAR2 architecture, in which two siRNAs are conjugated per antibody, restored the loss of activity associated with increasing DAR from 1 to 2. Notably, at an equivalent siRNA dose (1 mg/kg), the DAR2-C16 AOC requires half the amount of antibody while achieving knockdown comparable to the DAR1-C16 AOC. We also developed a charge-balancing ionizable linker (CBIL) designed to partially compensate for the negative charge of siRNA. Incorporation of the CBIL enhanced target gene silencing in heart and skeletal muscle without a corresponding increase in hepatic activity, resulting in a shift toward greater extrahepatic activity relative to liver. Together, these findings demonstrate that chemical modification of both the siRNA payload and antibody-siRNA linker can be used to tune AOC potency and tissue activity, while enabling higher payload loading without compromising efficacy. These results establish chemical design as an important strategy for expanding the architecture and therapeutic potential of AOCs.

The folate receptor (FR) is overexpressed in a range of human tumours including ovarian cancer cells. We propose that the overexpression of the FR on the surface of ovarian tumour cells could be exploited for the selective delivery of a DNA damage response inhibitor (DDRi) in the form of an intact folate drug conjugate (FDC). This approach would improve the therapeutic index of the parent DDRi facilitating combination studies of the DDRi-based FDC with DNA damaging chemotherapy. FR-mediated cellular uptake of the proposed folate drug conjugates is requisite for FDC selective delivery into tumours. In this study, we synthesised a series of olaparib-based folate conjugates that maintained the biochemical PARP1 inhibition associated with olaparib and showed binding affinity for the folate receptor. Significantly, we identified compounds 10b and 11 that selectively enter FR overexpressing tumour cells via folate receptor-mediated endocytosis in their intact form and engage with their target as demonstrated by the potent inhibition of PARylation (KB cells, PARylation IC50 = 5.7 and 3.9 nM; respectively).

Cyclic peptides can engage targets beyond the reach of small molecules, but their discovery typically relies on libraries reused across targets, diversification around a known interaction motif, or computational methods limited to a handful of non-canonical building blocks. Here, we present nCycle-Forge, a simulated annealing framework that designs cyclic peptide binders by iteratively substituting building blocks and scoring each proposal by cofolding with the target. We designed, synthesized, and screened 1,472 cyclic peptides against the active-site pocket of Thrombin and the shallow p53-binding surface of MDM2 from the target sequence alone and without fixing binding mo-tifs. The library yielded chemically diverse hits against both targets in a single round without experimental optimization, with hit rates comparable to or up to 24-fold higher than in larger experimental libraries. Purified designs reached sub- to low-micromolar potency, with the best Thrombin inhibitor at Ki 0.14 M and the best MDM2 binder at EC50 2.4 M. Surface plasmon resonance confirmed direct binding, competition with or-thosteric inhibitors at both sites, and weaker binding under conditions expected to linearize the designs. nCycle-Forge requires no building block-specific parameterization, conformer generation, or retraining, and provides a target-focused route to functional cyclic peptides beyond the canonical amino acid alphabet.