ACS Central Science最新文献

Multivalent inhibitors that mimic the polysaccharide array on cells represent a new paradigm in the development of antiviral agents and antibiotics. Covalent ligand anchoring limits the affinity and, in turn, potency of these inhibitors with dissociation constants (K_d) commonly found in the micromolar or upper nanomolar range. Addressing this deficiency we here report on easily accessible gold core–shell nanoparticles (rSAM-NPs) featuring adaptable reversible self-assembled monolayer (rSAM)-based shells. The rSAMs are anchored by noncovalent amidinium-carboxylate interactions on gold nanoparticles at slightly alkaline pH resulting in laterally mobile pH-responsive assemblies that are functional at physiological pH. Introducing sialic acid ligands in the shell, we show that the rSAM-NPs strongly interact with the influenza virus surface protein hemagglutinin (limit of detection LoD < 2 nM) and deactivated bird flu virus H5N1 (LoD < 1 HAU) in allantoic liquid. Finally, we show that the rSAM-NPs effectively inhibit the interaction of the virus with red blood cells at concentrations in the low picomolar range. This represents a significant increase in potency with respect to multivalent inhibitors of similar size based on covalently anchored monosaccharides.

Gold core nanoparticles with adaptable, sialic acid presenting, self-assembled monolayer shells effectively inhibit the interaction between deactivated bird flu virus (H5N1) and red blood cells at low picomolar concentrations.

Disease-modifying antirheumatic drugs (DMARDs) have greatly improved the treatment of rheumatoid arthritis (RA), but strategies to prevent disease onset and recurring flares remain limited. While abatacept (CTLA-4 IgG) can delay RA onset and corticosteroids are used for flare control, the benefit is temporary. We report that combining standard-of-care treatments with a locally administered immunomodulatory agent, termed Agg-CLNP, enhances both disease prevention and flare mitigation. Agg-CLNP consists of polymer nanoparticles conjugated with an immunodominant aggrecan peptide and encapsulate calcitriol. These nanoparticles are optimized for uptake by dendritic cells (DC) in lymph nodes proximal to arthritic joints. In vitro, Agg-CLNP suppressed costimulatory molecules and HLA class II (HLA-2) expression and upregulated CTLA-4 in human monocyte-derived DC from healthy and RA donors. In SKG mice, a T cell-driven RA model, Agg-CLNP combined with CTLA-4 IgG synergistically delayed disease onset and reduced severity. In a dexamethasone (Dex) withdrawal flare model, post-Dex Agg-CLNP treatment reduced flare severity and preserved a regulatory phenotype in DC, while suppressing local pathogenic T_H17 cells. Next generation RNA sequencing of lymph node DC revealed Ctla4 upregulation and changes in other immunomodulatory genes linked to flare prevention. These findings highlight Agg-CLNP as a potential therapeutic strategy to address critical unmet needs in RA management.

Agg-CLNP is a disease modifying agent which modulates immune activation and effectively suppresses disease onset and controls flares, providing a potential solution to unmet needs in rheumatoid arthritis.

Safety concerns continue to arise as lead and other potentially toxic metals are found in the aerosols of modern disposable e-cigarettes.

Surface-enhanced Raman scattering (SERS) is a powerful analytical technique offering ultrasensitive, nondestructive molecular fingerprinting. However, challenges such as spectral overlap, noise, and signal variability, especially in complex mixtures, limit its reliability and reproducibility. With increasing volumes of complex SERS data, there is a pressing need for advanced tools to manage and interpret this information. Cheminformatics amalgamates chemical knowledge with computational methods to deliver solutions for spectral preprocessing, database management, molecular modeling, pattern recognition, and multimodal data integration. This Outlook presents a vision for uniting SERS and cheminformatics to enhance the reliability of (bio)chemical analysis and discovery. We propose a conceptual framework built upon four interconnected pillars: (1) centralized SERS databases, (2) molecular modeling for mechanistic insights, (3) machine learning (ML) for spectral analysis, and (4) automation and artificial intelligence for expanding the SERS chemical space. Together, these four pillars form a dynamic, feedback-driven system that enhances interpretability, accelerates data-driven discovery, and facilitates real-time SERS analysis. The symbiotic relationship between SERS and cheminformatics positions this integration at the forefront of data-driven chemical research with transformative applications in materials science, catalysis, biomedical diagnostics, and environmental monitoring.

Integrating SERS with cheminformatics enables automated, real-time chemical sensing and data-driven discovery, advancing surface and molecular analysis across scientific fields.

Chirality plays a fundamental role in biology, where stereochemical information governs how molecules fold, interact, and function. While the effects of stereochemistry are well-established for small molecules and natural biomacromolecules, less is known about how it shapes the properties of synthetic, biomimetic polymers. In this study, we explore how backbone and glycan stereochemistry influences conformation, physical interactions, and biological behavior in water-soluble glycopolymers. Using ring opening metathesis polymerization (ROMP), we synthesized precision glycopolymers (PGPs) from two diastereomeric norbornenyl moieties (endo and exo) and monosaccharides (glucose, galactose, and mannose). Despite having nearly identical molecular and macromolecular compositions, the resulting PGPs displayed major differences in their physical and biological properties. Glycopolymers with β-linkages showed distinct circular dichroism (CD) signals, and exo-derived backbones displayed more hydrophobic local environments, as confirmed by all-atom molecular dynamics simulations and dye interaction studies. These structural differences had clear functional consequences. exo-PGPs bound plant lectins more rapidly and with higher avidity, whereas endo-PGPs showed greater selectivity toward human galectin-3, stronger inhibition of cholera toxin, and enhanced uptake into 4T1 triple-negative breast cancer cells. Together, these findings provide the first demonstration of biological activity in endo-derived glycopolymers and establish backbone stereochemistry as a key design element that encodes macromolecular behavior in biologically relevant contexts.

Subtle changes in polymer stereochemistry drive major differences in macromolecular conformation and biological function, revealing stereochemistry as a key element in glycomaterial design.

An iron-anthracene dyad was recently used to populate a microsecond-lived nonluminescent (dark) triplet state, but with a surprisingly low triplet population yield. In-depth spectroscopic experiments highlight that direct energy transfer does not take place, but rather an intramolecular electron-transfer occurs, generating the corresponding reduced iron center and oxidized anthracene moiety, and the final triplet dark state is populated following charge recombination. This electron-transfer cascade reaction mechanism provided the unique opportunity to control the energy level of the charge-separated state relative to the energy of the triplet state by changing the solvent polarity. As such, the triplet formation yield increased from 5% in acetonitrile to 75% in dichloromethane. This outlines an unreported mechanistic pathway for first-row transition metal complexes to populate long-lived excited states and provides design guidelines that differ between d⁵ and prototypical d⁶ photosensitizers. The d⁵ electronic configuration enables population of the final triplet energy acceptor via a cascade of electron transfer that does not formally require intersystem crossing or spin-flip transitions, thus also minimizing energy loss channels. Although the energy of the final triplet state is important, our findings highlight that the redox potentials of the excited photosensitizer and final energy acceptor moiety are pivotal to efficiently populate dark triplet states.

The mechanism describing the population of an anthracene-localized triplet dark state within an iron-anthracene dyad was shown to occur via a cascade of electron transfer, not energy transfer.

Scientists are identifying the chemicals we emit when we emote─and learning how they affect the behavior of people around us.

The structural prominence of indole-based sulfur-containing compounds in pharmacologically relevant substances stems from their versatile biofunctional capabilities. Despite their significance, the stereogenic elements embedded in these structures have frequently been overlooked in drug discovery endeavors primarily due to the absence of efficient synthetic methodologies. Here, we introduce a groundbreaking strategy for the enantioselective synthesis of indole-based sulfinamides via a copper-catalyzed asymmetric nucleophilic cyclization and sulfinamidation reaction. Utilizing ortho-alkynylanilines and sulfinylamines, this method achieves a broad spectrum of sulfinamides with complete atom economy, establishing a new paradigm in synthetic efficiency. Our approach not only facilitates the formation of S-chirogenic sulfinamides but also concurrently constructs products featuring both stereogenic sulfur and atropisomeric chirality. Comprehensive mechanistic investigations, complemented by density functional theory (DFT) calculations, provide deep insights into the reaction mechanism, particularly in elucidating the S-stereogenic and atropisomeric control during the cyclization and sulfinamidation processes.

A copper-catalyzed cyclizative sulfinamidation strategy enables facile synthesis of indole-based sulfinamides with simultaneous control of stereogenic sulfur and atropisomeric chirality.

The selective recognition of hydrophilic carbohydrates in water remains a longstanding challenge in supramolecular chemistry due to solvent competition and the lack of a strong driving force comparable to the hydrophobic effect. Herein, we report the design, synthesis, and characterization of a water-soluble tetralactam macrocycle, MPNT²⁺·2Cl^–, as a highly effective synthetic lectin for glucuronate. MPNT²⁺·2Cl^– features two dimethylnaphthalene panels, pyridinium spacers, and morpholine side chains, forming a rigid, preorganized cavity with convergent hydrogen bond donors, polarized C–H donors, and complementary electrostatic interactions. The receptor achieves a binding affinity of 103,000 M^–1 for glucuronate in water, over 19-fold higher than previous synthetic systems, along with excellent selectivity over structurally similar carbohydrates. Single-crystal X-ray analysis, DFT calculation, and IGMH analysis reveal a dense network of [N–H···O], [C–H···O], and [C–H···π] interactions, highlighting the role of stereoelectronic complementarity in complex formation. Moreover, MPNT²⁺·2Cl^– acts as a chiroptical sensor, producing binding-induced circular dichroism signals that enable sensitive detection of glucuronic acid at physiologically relevant concentrations. This work presents a generalizable strategy for designing synthetic lectins that recognize carbohydrates in aqueous solutions and opens up new possibilities for developing molecular sensors and diagnostic tools for biologically important anionic sugars.

A synthetic macrocyclic lectin recognizes glucuronate in water, enabling strong, selective binding and chiroptical sensing of a biologically important sugar.

Mechanophores are molecules that undergo chemical changes in response to mechanical force, offering unique opportunities in chemistry, materials science, and drug delivery. However, many potential mechanophores remain unexplored. For example, ferrocenes are attractive targets as mechanophores due to their combination of high thermal stability and mechanochemical lability. However, the mechanochemical potential of ferrocene derivatives remains dramatically underexplored despite the synthesis of thousands of structurally diverse complexes. Herein, we report the computational, machine learning guided discovery of synthesizable ferrocene mechanophores. We identify over one hundred potential target ferrocene mechanophores with wide-ranging mechanochemical activity and use data-driven computational screening to identify a select number of promising complexes. We highlight design principles to alter their mechanochemical activation, including regio-controlled transition state stabilization through bulky groups and a change in mechanism through noncovalent ligand–ligand interactions. The computational screening is validated experimentally both at the polymer strand level through sonication experiments and at the network level, where a computationally discovered ferrocene mechanophore cross-linker leads to greater than 4-fold enhancement in material tearing energy. This work establishes a generalizable framework for the high-throughput discovery and rational design of mechanophores and offers insights into structure–activity relationships in mechanically responsive materials.

Machine learning-guided discovery and validation of ferrocene-based mechanophores enables tunable reactivity and enhanced polymer mechanical properties.