Chemical Science

Amyloid fibrils are a common pathological hallmark in multiple neurodegenerative diseases, yet molecular tools to selectively recognise and manipulate them remain scarce. We report FibrilPaints, a family of modular peptides designed for selective amyloid binding and adaptable chemical functionality. The degenerative amyloid-targeting unit of FibrilPaints, W5P4H3R2, has a high content of {pi}-stacking and aromatic side chains. Systematic sequence variation, altering charge, termini, and residue order, revealed the importance of the composition of the amyloid-targeting unit for high-affinity binding across Tau and Huntingtin fibrils. Importantly, sequence changes outside this unit do not preclude fibril binding, which permits attachment of fluorophores or E3-recruiting motifs for targeted protein degradation. This work establishes FibrilPaint as a modular peptide system for the detection and modulation of amyloids. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/609586v4_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1e9cadborg.highwire.dtl.DTLVardef@50f9eorg.highwire.dtl.DTLVardef@446ee8org.highwire.dtl.DTLVardef@cd47a2_HPS_FORMAT_FIGEXP M_FIG Figure of content The modular design of FibrilPaints enables systematic evaluation of their functionality by testing the binding capacity of each variant (FibrilPaintX) to distinct amyloid fibrils. Successful binding results in visible painting of the fibrils, facilitating their detection and downstream research. C_FIG

The Gram-negative bacterium Burkholderia pseudomallei causes the severe disease melioidosis. {beta}-Lactams, including carbapenems, are the primary treatment, but are susceptible to chromosomal {beta}-lactamases, including the class D enzyme OXA-57. Here we show recombinant OXA-57 is active towards penicillins and first-generation cephalosporins, slowly hydrolyzes carbapenems including imipenem and meropenem, but is inactive towards oxyimino-cephalosporins (e.g., ceftazidime). Unlike many OXA enzymes, OXA-57 is sensitive to the mechanism-based inhibitor clavulanic acid, but less so to the diazabicyclooctane avibactam and not to the cyclic boronate vaborbactam. Crystal structures of covalent OXA-57:avibactam and OXA-57:meropenem complexes reveal limited hydrogen- bonding interactions with bound ligands. In molecular dynamics simulations, bound meropenem is mobile, while the water necessary for deacylation has only limited active site access. These observations are consistent with the low level of meropenem turnover, supporting proposals that OXA {beta}-lactamases generally possess limited carbapenemase activity, and highlight the potential importance of OXA-57 in B. pseudomallei {beta}-lactam resistance. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/630153v1_ufig1.gif" ALT="Figure 1000"> View larger version (24K): org.highwire.dtl.DTLVardef@d635d7org.highwire.dtl.DTLVardef@168d67borg.highwire.dtl.DTLVardef@1d95733org.highwire.dtl.DTLVardef@1ebeabb_HPS_FORMAT_FIGEXP M_FIG C_FIG

Proteolysis Targeting Chimeric Molecules (PROTACs) represent a promising avenue in drug discovery, as they can induce the targeted degradation of disease-relevant proteins within the cellular machinery. These compounds comprise a ligand tailored to bind the specific targeted protein connected to a recruiter molecule that engages with the E3 ligase. Despite their promise as therapeutic agents, their clinical advancement has encountered substantial challenges, primarily due to the limited availability of suitable E3 ligases. Additionally, cell permeability and proteolytic stability due to their peptide nature often hamper their application. In this study, we focus on the development of recruiters for the E3 ligase UBR1. This widely expressed protein has recently been demonstrated to be efficient in driving the degradation of oncogenic proteins. Our computational approach leverages a fragment-based peptidomimetics strategy, integrating pharmacophore filtering, docking, and fragment-linking optimization. Finally, we subject the wild-type peptide and the most promising combined fragments to advanced binding free energy calculations, unveiling insights into their dynamic water-mediated binding mechanisms and their potential as robust E3 ligase UBR1 recruiters, ultimately leading to the identification of promising compounds. This computational workflow is readily applicable to the development of related PROTACs and also to model protein-protein interactions with similar characteristics.

Tuberculosis (TB) remains a major global health threat, with Mycobacterium tuberculosis (Mtb) infecting nearly a quarter of the global population. Drug-resistant TB and HIV-TB co- infections emphasize the need for novel therapeutic approaches targeting essential metabolic pathways. Here, we investigated Mtb cystathionine {beta}-synthase (MtbCBS), a PLP-dependent enzyme critical for sulfur metabolism and redox regulation, owing its potential as a therapeutic target. We present the first high-resolution cryo-EM structure of MtbCBS bound to aminooxyacetic acid (AOAA), and employed molecular dynamics (MD) simulations, quantum mechanics/molecular mechanics (QM/MM) calculations, and comparative inhibition studies to reveal the molecular basis and determinants governing irreversible PLP-enzyme inhibition. Our Cryo-EM structural analysis revealed two highly conserved active-site residues, T75 and Q147, critically stabilizing the inhibitor complex. Through molecular mimic studies, we demonstrated the precise structural factors and electronic features critical for inhibition efficiency. These findings provide the first mechanistic rationale for PLP enzyme inhibition and offer a generalizable framework for designing covalent inhibitors targeting PLP-dependent enzymes implicated in infectious diseases, cancer, and neurological disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/662948v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@195c7c7org.highwire.dtl.DTLVardef@6ee0c8org.highwire.dtl.DTLVardef@1679dfborg.highwire.dtl.DTLVardef@1b4e000_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract.C_FLOATNO Proposed mechanism of MtbCBS inhibition by AOAA. Proposed mechanism of action of AOAA illustrated through a graphical representation. The cartoon shows the domains of MtbCBS. Tetrameric structure of MtbCBS with active site highlighted (in red dashes). Enlarged view indicating the PLP-AOAA blocked intermediate interacting with residue Q147. Reaction scheme depicting the previous missing understanding of active site residue role in -elimination. Schematic representation of AOAA inhibition mechanism in the catalytic cycle of MtbCBS. Reactions were drawn using ChemDraw. The proposed scheme highlights that AOAA (highlighted Red) binding is stabilized by nearby residues Q147 and T75, leading to the formation of PLP-AOAA covalent adduct, and substrates (highlighted green) were incapable of reverting the suicidal inhibition. The directionality and reversibility were mentioned for each step. C_FIG

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.

Ligand binding to intrinsically disordered proteins resists description in terms of conventional binding pockets, yet it can be analysed as a dynamic process in which ligands move across transient surface interaction sites. Here we characterise a pathway-based representation in which ligand binding is described as a sequence of transitions between residue-defined microstates, enabling ligand-specific effects to be distinguished from intrinsic properties of the peptide conformational ensemble. Using all-atom molecular dynamics simulations of A{beta}42 and the C-terminal region of -synuclein in complex with chemically diverse small molecules, we construct transition matrices that encode ligand movement across the peptide surface and use Markov state models to identify dominant binding pathways and relative binding propensities. Pairwise enrichment-factor and AUC analyses reveal strong conservation of the highest-ranked pathways across chemically diverse ligands, with enrichment factors of 15-45 for the top-ranked states and AUC values typically [≥]0.75, well above random expectation. These dominant pathways are also preserved across changes in pH and temperature, whereas a urea control, included as a non-specific binder, shows reduced enrichment, indicating that ligands primarily modulate pathway weights rather than define the underlying network topology. Ensemble docking across chemically diverse libraries further supports the presence of recurrent ligand-accessible hotspots within the peptide conformational ensemble. Building on this framework, we apply a prospective screening pipeline to A{beta}42, combining MSM-derived hotspots with sequence-based Ligand-Transformer scoring and Gnina docking across 1.66 million compounds, to nominate 19 candidates for prospective experimental evaluation. Together, these results indicate that disordered protein sequences give rise to conformational ensembles that exhibit characteristic binding pathways for small molecules.

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel non-covalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (Mpro) by employing a scalable high throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this Mpro inhibitor with an inhibition constant (Ki) of 2.9 {micro}M [95% CI 2.2, 4.0]. Further, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of Mpro forming stable hydrogen bond and hydrophobic interactions. We then used multiple {micro}s-timescale molecular dynamics (MD) simulations, and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by Mpro, involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits Mpro and offers a springboard for further therapeutic design. O_TEXTBOXSignificance StatementThe ongoing novel coronavirus pandemic (COVID-19) has prompted a global race towards finding effective therapeutics that can target the various viral proteins. Despite many virtual screening campaigns in development, the discovery of validated inhibitors for SARS-CoV-2 protein targets has been limited. We discover a novel inhibitor against the SARS-CoV-2 main protease. Our integrated platform applies downstream biochemical assays, X-ray crystallography, and atomistic simulations to obtain a comprehensive characterization of its inhibitory mechanism. Inhibiting Mpro can lead to significant biomedical advances in targeting SARS-CoV-2 treatment, as it plays a crucial role in viral replication. C_TEXTBOX

{beta}-Lactamases catalyze {beta}-lactam antibiotic hydrolysis and are important contributors to bacterial antimicrobial resistance; {beta}-lactamase inhibitors are widely used to overcome {beta}-lactamase-mediated antibiotic resistance. Nucleophilic serine {beta}-lactamases (SBLs) react with their substrates and clinically available inhibitors via a covalent reaction to give complexes which can undergo further reaction. Using room temperature drop on fixed target serial crystallography, where ligands are rapidly mixed with microcrystals, and classical single-crystal crystallography at cryogenic temperatures, we investigate the reversible covalent reaction of the SBL CTX-M-15 with the diazobicyclooctane inhibitor avibactam. We observe avibactam covalently reacted (ring-opened) with the nucleophilic Ser70, at timepoints from 80 ms to minutes (room temperature) and hours (100 K). These crystallographic data reveal time-dependent movement of the avibactam carbamoyl complex, from 1.3 s onwards, that has implications for the 5-exo-trig recyclization mechanism that determines inhibitor reformation. Combined with molecular dynamics simulations and quantum mechanics calculations at the density functional theory level, the results show that in the first seconds of the reaction the avibactam N-sulfate nitrogen is poorly positioned for recyclization. This subsequently equilibrates after 10 s to a stable endpoint that is in a conformation potentially primed to initiate recyclization through attack of the N-sulfate nitrogen on the carbamoyl carbon. These results further demonstrate the capacity of room-temperature serial crystallography to capture time-resolved changes in ligand conformation at an enzyme active site, complementing discrete classical cryo-crystallography. These data inform on ligand dynamics and the stereoelectronics of diazobicyclooctane inhibition, aiding drug discovery efforts to develop inhibitors of nucleophilic enzymes.

Streptomycetes are major producers of bioactive natural products, including the majority of the antibiotics. While much if the low-hanging fruit has been discovered, it is predited that less than 5% of the chemical space has been mined. Here, we describe the novel actinomycins L1 and L2, which are produced by Streptomyces sp. MBT27. The molecules were discovered via metabolic analysis combined with molecular networking of cultures grown with different combinations of carbon sources. Actinomycins L1 and L2 are diastereoisomers, and the structure of actinomycin L2 was resolved using NMR and single crystal X-ray crystallography. Actinomycin L is formed via a unique spirolinkage of anthranilamide to the 4-oxoproline moiety of actinomycin X2, prior to the condensation of the actinomycin halves. Feeding anthranilamide to cultures of Streptomyces antibioticus, which has the same biosynthetic gene cluster as Streptomyces sp. MBT27 but only produces actinomycin X2, resulted in the production of actinomycin L. This shows that actinomycin L results from joining two distinct metabolic pathways, namely those for actinomycin X2 and for anthranilamide. Actinomycins L1 and L2 showed significant antimicrobial activity against Gram- positive bacteria. Our work shows how new molecules can still be identified even in the oldest of natural product families. IMPORTANCEActinomycin was the first antibiotic discovered in an actinobacterium by Selman Waksman and colleagues, as early as 1940. This period essentially marks the start of the golden era of antibiotic discovery. Over time, emerging antimicrobial resistance (AMR) and the declining success rate of antibiotic discovery resulted in the current antibiotic crisis. We surprisingly discovered that under some growth conditions, Streptomyces sp. MBT27 can produce actinomycins that are significantly different from those that have been published so far. The impact of this work is not only that we have discovered a novel molecule with very interesting chemical modifications in one of the oldest antibiotics ever described, but also that this requires the combined action of primary and secondary metabolic pathways, namely the biosynthesis of anthranilamide and of actinomycin X2, respectively. The implication of the discovery is that even the most well-studied families of natural products may still have surprises in store for us.

Deep learning networks offer considerable opportunities for accurate structure prediction and design of biomolecules. While cyclic peptides have gained significant traction as a therapeutic modality, developing deep learning methods for designing such peptides has been slow, mostly due to the small number of available structures for molecules in this size range. Here, we report approaches to modify the AlphaFold network for accurate structure prediction and design of cyclic peptides. Our results show this approach can accurately predict the structures of native cyclic peptides from a single sequence, with 36 out of 49 cases predicted with high confidence (pLDDT > 0.85) matching the native structure with root mean squared deviation (RMSD) less than 1.5 [A]. Further extending our approach, we describe computational methods for designing sequences of peptide backbones generated by other backbone sampling methods and for de novo design of new macrocyclic peptides. We extensively sampled the structural diversity of cyclic peptides between 7-13 amino acids, and identified around 10,000 unique design candidates predicted to fold into the designed structures with high confidence. X-ray crystal structures for seven sequences with diverse sizes and structures designed by our approach match very closely with the design models (root mean squared deviation < 1.0 [A]), highlighting the atomic level accuracy in our approach. The computational methods and scaffolds developed here provide the basis for custom-designing peptides for targeted therapeutic applications.

The aggregation of natively disordered -Synuclein (Syn) into amyloid fibrils is a hallmark of Parkinsons and other neurodegenerative diseases. Understanding Syns pathological role remains a major challenge due to its complex, context-dependent energy landscape characterized by conformational plasticity and fibril polymorphism. Here, we present a systematic mutational analysis as a quantitative probe of the Syn energy landscape, focusing on electrostatic contributions to key aggregation pathways. We engineered Syn variants with one to eight lysine-to-glutamine substitutions and analyzed their aggregation under controlled conditions to delineate their effects on nucleation, elongation, seed amplification, fibril stability, and fibril polymorphism. We find that Syn aggregation from a homogenous solution can be modelled well using global properties, including protein concentration, charge, and ionic strength. Microscopic pathways and the resulting fibril polymorphs are instead modulated by sequence-specific effects. We identify mutations of residues found in fibril cores as perturbations that significantly modify the Syn free energy landscape, creating pathways and energy minima not accessible to the WT under the same experimental conditions. In contrast, mutations outside of the fibril core affect the magnitude of the relevant energy barriers whilst overall maintaining a WT-like free energy landscape. Our work outlines a scalable, quantitative framework that increases the informational output of the mutational studies of Syn using conventional assays. The approach can be extended by incorporating additional mutational and functional data to deepen our understanding of Syns energy landscape and its role in health and disease.

Increasing numbers of multi-drug resistant pathogens call for new chemical scaffolds, addressing novel targets, that can serve as lead structures for the development of life-saving drugs. For antibiotics, natural product-inspired molecules represent a most promising resource. Natural products evolved to high chemical complexity and occupy a chemical space different than synthetic libraries. However, clinical translation of promising natural products is often impeded by their relative inaccessibility to medicinal chemistry optimization, e.g. iterative synthesis of large series of derivatives. Here, this limitation is addressed with a randomized library of bicyclic heptapeptides based on the natural product darobactin that hits the clinically not addressed target BamA. Variants of the ribosomally synthesized and post-translationally modified peptides were generated using heterologous mutasynthesis. A parallelized screening assay is adapted in nanoliter-scale beads to test the darobactin derivatives against our sensor strain. Loss of fluorescence sorting prioritized 563 events out of the analyzed [~]500k beads. Re-testing confirmed 48 hit events, of which 40 proved to produce distinct darobactin-type molecules. Most promising structures were isolated and the growth inhibitory effects against Gram-negative pathogens validated. One of our current frontrunner compounds (i.e., darobactin B) was reinforced by the randomized screen. While microbiological investigations of the new derivatives is ongoing, darobactin B was profiled in later tier assays and compared to another promising, rationally-designed analog (i.e., darobactin B9, "D22"). Early ADMET profiling and efficacy tests in a mouse pneumonia model were performed. Darobactin B reduced bacterial load of Pseudomonas aeruginosa and Klebsiella pneumoniae by intraperitoneal, as well as intratracheal administration. Our study showcases the potential of mutasynthetic libraries for high-throughput screening and identification of functional peptides for drug lead discovery.

"Mirror life", self-replicating organisms composed of non-natural-chirality biomacromolecules, presents a severe future threat with potentially global consequences. Consequently, there is strong agreement among experts that it should not be created. However, there is some disagreement over how effective existing medical countermeasures might prove against mirror bacteria in the event that they were created. Here, we leverage computational chemistry methods including docking and molecular dynamics to determine the likely binding efficacy of existing antibiotics against natural and mirror bacterial protein targets. We find that existing most antibiotics fail to bind to mirror bacterial protein targets, unlike their natural chirality targets. This suggests that current medical countermeasures would not successfully exert an antimicrobial activity against mirror bacteria if the latter were created. Our results motivate further policy advocacy to curtail research that directly leads to the creation of mirror life.

We demonstrate a path towards full Quantum Mechanics (QM) characterization of enzymatic activity. As a case-study, we investigate the detoxification of aflatoxin, a carcinogenic food contaminant, by laccase, a versatile oxidase capable of--but not efficient for--degrading aflatoxin. We use a combination of quantitative experimentation and QM modeling to show that low enzymatic steric affinity for aflatoxin is the main bottleneck, rather that the oxidative activity of laccase. To identify the structural elements responsible for low reaction rates, we perform a density functional theory (DFT) based modeling of both the substrate and the enzyme in a full QM simulation of more than 7,000 atoms. Thanks to our approach we point to amino acid residues that determine the affinity of laccase for aflatoxin. We show that these residues are substrate-dependent, making a full QM approach necessary for enzyme optimization. Altogether, we establish a roadmap for rational enzyme engineering applicable beyond our case study.

Antibiotic resistance is a critical public health problem. Each year ~2.8 million resistant infections lead to more than 35,000 deaths in the U.S. alone. Antimicrobial peptides (AMPs) show promise in treating resistant infections. However, applications of known AMPs have encountered issues in development, production, and shelf-life. To drive the development of AMP-based treatments it is necessary to create design approaches with higher precision and selectivity towards resistant targets. Previously we developed AMPGAN and obtained proof-of-concept evidence for the generative approach to design AMPs with experimental validation. Building on the success of AMPGAN, we present AMPGAN v2 a bidirectional conditional generative adversarial network (BiCGAN) based approach for rational AMP design. AMPGAN v2 uses generator-discriminator dynamics to learn data driven priors and controls generation using conditioning variables. The bidirectional component, implemented using a learned encoder to map data samples into the latent space of the generator, aids iterative manipulation of candidate peptides. These elements allow AMPGAN v2 to generate of candidates that are novel, diverse, and tailored for specific applications--making it an efficient AMP design tool.

Antimicrobial peptides (AMPs) are of growing interest as potential candidates for antibiotics to which antimicrobial resistance increases slowly. In this article, we perform the first in silico study of the synthetic {beta} sheet-forming AMP GL13K. Through atomistic simulations of single and multipeptide systems under different charge conditions, we are able to shine a light on the short timescales of early aggregation. We find that isolated peptide conformations are primarily dictated by sequence rather than charge, whereas changing charge has a significant impact on the conformational free energy landscape of multi-peptide systems. We demonstrate that the lack of charge-charge repulsion is a sufficient minimal model for experimentally observed aggregation. Overall, our work explores the molecular biophysical underpinnings of the first stages of aggregation of a unique AMP, laying necessary groundwork for its further development as an antibiotic candidate.

The de novo design of -helical coiled-coil peptides is advanced. Using established sequence-to-structure relationships, it is possible to generate various coiled-coil assemblies with predictable numbers and orientations of helices. Here we target new assemblies, namely A3B3 heterohexamer -helical barrels. These designs are based on pairs of sequences with 3-heptad repeats (abcdefg) programmed with a = Leu, d = Ile, e = Ala, and g = Ser, and b = c = Glu to make the acidic (A) chains and b = c = Lys in the basic (B) chains. These design rules ensure that the desired oligomeric state and stoichiometry are readily achieved. However, controlling the orientation of neighboring helices (parallel or anti-parallel) is less straightforward. Surprisingly, we find that assembly and helix orientation are sensitive to the starting position of the heptad repeats (the register) in the peptide sequences. Peptides starting at g (g-register) form a parallel 6-helix barrel in solution and in an X-ray crystal structure, whereas the b- and c-register peptides form an antiparallel complex. In lieu of experimental X-ray structures for b- and c-register peptides, AlphaFold-Multimer is used to predict atomistic models. However, considerably more sampling than the default value is required to match the models and the experimental data, as many confidently predicted and plausible models are generated with incorrect helix orientations. This work reveals the previously unknown influence of heptad register on the orientation of -helical coiled-coil peptides and provides insights for the modeling of oligopeptide coiled-coil complexes with AlphaFold.

Lasso peptides are a unique class of natural products with distinctively threaded structures, conferring exceptional stability against thermal and proteolytic degradation. Despite their promising biotechnological and pharmaceutical applications, reported attempts to prepare them by chemical synthesis result in forming the nonthreaded branched-cyclic isomer, rather than the desired lassoed structure. This is likely due to the entropic challenge of folding a short, threaded motif prior to chemically mediated cyclization. Accordingly, this study aims to better understand and enhance the relative stability of pre-lasso conformations--the essential precursor to lasso peptide formation--through sequence optimization, chemical modification, and disulfide incorporation. Using Rosetta fixed backbone design, optimal sequences for several class II lasso peptides are identified. Enhanced sampling with well-tempered metadynamics confirmed that designed sequences derived from the lasso structures of rubrivinodin and microcin J25 exhibit a notable improvement in pre-lasso stability relative to the competing nonthreaded conformations. Chemical modifications to the isopeptide bond-forming residues of microcin J25 further increase the probability of pre-lasso formation, highlighting the beneficial role of non-canonical amino acid residues. Counterintuitively, the introduction of a disulfide cross-link decreased pre-lasso stability. Although cross-linking inherently constrains the peptide structure, decreasing the entropic dominance of unfolded phase space, it hinders the requisite wrapping of the N-terminal end around the tail to adopt the pre-lasso conformation. However, combining chemical modifications with the disulfide cross-link results in further pre-lasso stabilization, indicating that the ring modifications counteract the constraints and provide a cooperative benefit with cross-linking. These findings lay the groundwork for further design efforts to enable synthetic access to the lasso peptide scaffold. SIGNIFICANCELasso peptides are a unique class of ribosomally synthesized and post-translationally modified natural products with diverse biological activities and potential for therapeutic applications. Although direct synthesis would facilitate therapeutic design, it has not yet been possible to fold these short sequences to their threaded architecture without the help of biosynthetic enzyme stabilization. Our work explores strategies to enhance the stability of the pre-lasso structure, the essential precursor to de novo lasso peptide formation. We find that sequence design, incorporating non-canonical amino acid residues, and design-guided cross-linking can augment stability to increase the likelihood of lasso motif accessibility. This work presents several strategies for the continued design of foldable lasso peptides.

N-acetyl-DL-leucine is an analogue of the alpha amino acid leucine with a chiral stereocenter. The active L-enantiomer of the racemate is currently under development for rare neurological disorders. Here we present evidence that a selective recognition of N-acetyl-L-leucine versus L-leucine by different uptake transporters significantly contributes to the therapeutic effects of N-acetyl-L-leucine. A previous study of the pharmacokinetics of racemic N-acetyl-DL-leucine and N-acetyl-L-leucine revealed D-L enantiomer competition and saturation kinetics, best explained by carrier-mediated uptake. The strategy we used was to first analyze the physicochemical properties associated with good oral bioavailable drugs and how these are alerted by N-acetylation by comparing N-acetyl-L-leucine with L-leucine. Using in silico computational chemistry we found that N-acetylation has a profound impact on certain physicochemical properties that can rationalize why N-acetyl-L-leucine is drug-like compared to L-leucine. Our calculations show that at physiological pH, L-leucine is a zwitterion, whereas N-acetyl-L-leucine is present as mainly an anion. Specifically, N-acetylation removes a charge from the nitrogen at physiological pH and N-acetyl-L-leucine is an anion that is then a substrate for the organic anion transporters. We examined N-acetyl-L-leucine uptake in human embryonic kidney cells overexpression candidate organic anion transporters (OAT) and pharmacological inhibitors. We found that N-acetyl-L-leucine is a translocated substrate for OAT1 and OAT3 with low affinity (Km ~10 mM). In contrast, L-leucine is known to be transported by the L-type Amino Acid Transporter (LAT) with high affinity (Km ~0.2 mM) and low capacity. The clinical consequence is that L-leucine uptake becomes saturated at 50-fold lower concentration than N-acetyl-L-leucine. These results demonstrate a mechanism of action that explains why N-acetyl-L-leucine is effective as a drug and L-leucine itself is not.

Protein stabilization is a "Holy Grail" of biocatalysis, and stability design is an area of intense research interest. While it is increasingly feasible to effectively increase enzyme thermostability, optimization without compromising activity or selectivity remains a significant challenge. Here, we use full-atom protein sequence design with sidechain conditioning (FAMPNN) to engineer thermostable variants of the borneol dehydrogenase from Salvia rosmarinus (SrBDH1), an enzyme from a family where unselective enzymes dominate, and selectivity is determined by dynamical considerations. By combining FAMPNN design with residue conservation analysis and avoiding active site residues, we were able to computationally design SrBDH1 variants with up to 10 {degrees}C enhanced thermostability and strongly increased half-life time at elevated temperature, while retaining selectivity towards (+)-borneol. This design framework, integrating de novo and physics-based protein design tools, demonstrates that stability can be enhanced without disrupting functionally relevant dynamics, providing a route to engineer robust and selective biocatalysts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/719482v1_ufig1.gif" ALT="Figure 1"> View larger version (97K): org.highwire.dtl.DTLVardef@1a35073org.highwire.dtl.DTLVardef@f6c56dorg.highwire.dtl.DTLVardef@11b965forg.highwire.dtl.DTLVardef@2d6eef_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG