ACS Central Science最新文献

Hydrogen-bonded organic frameworks (HOFs) offer atomic-precision platforms for probing water adsorption, yet monotonic building units often fail to meet the multifaceted demands of atmospheric water harvesting (AWH). In this study, a multivariate (MTV) strategy is employed to tune adsorption onset, work capacity, and cycling stability in HOFs. Introducing amino groups in controlled ratios creates a balance between hydrophilic sites and dynamic confinement within ordered frameworks. Specifically, the parent HOF, PFC-76, was constructed from the organic linker [1,1′:4′,1″-terphenyl]-3,3″,5,5″-tetracarboxylic acid (TPTCA), which assembles into 2D honeycomb networks via carboxylic acid dimer synthons. Functionalizing TPTCA with amino groups modulates the framework’s packing and dynamic behavior. Single-crystal X-ray crystallography revealed sliding dynamics in PFC-76-NH₂ during water adsorption, along with ordered water arrangements within the dynamic confinement spaces. Systematic variation of amino content (50%, 67%, and 80%) generated an atactic distribution of functional groups while maintaining crystallinity and porosity. This compositional tuning enhanced H₂O uptake, optimized the adsorption inflection point, and delivered an outstanding cycling stability. The strategy demonstrates how precise control over functional group incorporation and framework dynamics can yield programmable performance in soft porous crystals for practical applications.

Multivariate HOFs with functional tunable groups balance pore space and adsorption sites, enabling PFC-76-NH₂-67% to achieve high uptake, low energy cost, and excellent cycling in water harvesting.

Mutations in GBA1, the gene encoding the lysosomal hydrolase glucocerebrosidase (GCase), are the strongest common genetic risk factor for Parkinson’s Disease (PD). However, these mutations are incompletely penetrant, which suggests that there are likely genetic modifiers of GCase function. To identify such genes, we implemented a live cell GCase activity-based CRISPR-platform to enable genome-wide screening for novel regulators of lysosomal GCase activity. Among the screening hits, we find significant enrichment of genes linked to development and progression of PD through genome-wide association studies (GWAS). Moreover, we identify two lysosomal lipid transporter genes, including those encoding the lysosphospholipid transporter SPNS1 and the cholesterol transporter NPC1, and find an allele of SPNS1 that is associated with increased risk of PD. We show that disruption of SPNS1 does not affect GCase protein levels but impairs its lysosomal function. Collectively, these data suggest that dysfunction of many PD-associated genes converge to impact lysosomal GCase activity and thereby contribute to disease pathogenesis. A better understanding of the impacts of these and the other GCase modulators identified here should help unravel the important, yet complex, relationship between GBA1 and PD.

A fluorogenic substrate of GCase enables genome-wide screening for genes that influence its activity and reveals candidate risk factors for PD, showcasing the power of activity-based screening.

Pancreatic ductal adenocarcinoma (PDAC) remains refractory to current immune checkpoint blockade (ICB) therapies, necessitating innovative therapeutic strategies. Emerging evidence implicates aberrant sialoglycan upregulation as a key mediator of immune evasion in PDAC. Herein, we report Y-320, a highly potent oral sialylation inhibitor discovered through high-throughput screening. Y-320 suppresses α-2,3/2,6-sialylation in PDAC cells (IC₅₀ ≈ 200 nM) with >300-fold higher activity than the known pan-inhibitor P-3F_ax-Neu5Ac. Structural analyses reveal competitive occupation of multiple sialyltransferases’ substrate-binding pockets as Y-320’s action mechanism. In vivo, Y-320 significantly inhibits tumor growth and remodels the tumor immune microenvironment. Mechanistic studies establish that the therapeutic efficacy of Y-320 depends on the coordinated engagement between CD8⁺ T cell and macrophage. Importantly, Y-320 synergizes with anti-PD-1 therapy to overcome ICB resistance in PDAC, demonstrating superior tumor suppression compared to monotherapies. Our findings demonstrate that Y-320 shows promise for use as a therapeutic agent for cancer and validates sialylation inhibition as a novel glycoimmune checkpoint strategy for PDAC and other immunotherapy-resistant malignancies.

Y-320, an oral sialylation inhibitor identified through high-throughput screening, reduces tumor sialoglycans to block the sialic acid-Siglec immunosuppressive axis and enhance antitumor immunity.

Bioluminescence-assisted photoproximity labeling enables spatial proteome mapping in deep tissues.

The glycosylation of proteins endows them with distinct biophysical properties and allows them to play fundamental roles in cellular communication. Much of our understanding of glycoproteins has derived from the ability to enzymatically manipulate glycan structures. In particular, selective cleavage of glycans from proteins simplifies the analysis of glycoproteins and the determination of structure–activity relationships. However, limited enzymatic tools are available for the study of mucin-type O-glycans. To address this, we carried out the directed evolution of a glycoside hydrolase to increase its ability to cleave the sialyl T-antigen, a ubiquitous O-glycan structure in humans. We employed ultrahigh-throughput droplet-based microfluidics to rapidly screen vast libraries of variants in pL-sized droplets, thus minimizing the quantities of complex substrate required. Furthermore, by use of fluorescent protein-fusion and ratiometric gating during droplet sorting we could account for varying expression levels and identify highly active hits that could have been overlooked due to lower expression levels. Within just two rounds of screening, we uncovered variants with 840-fold enhancements in activity and new specificities compared to those of the WT enzyme. This campaign highlights the versatility of glycoside hydrolases and provides a broadly applicable strategy to engineer enzymatic tools for glycomics through microfluidic screening.

Combining a protein expression reporter with ultrahigh-throughput droplet-based microfluidics enabled us to drastically remodel the active site of a glycoside hydrolase and engineer new activities.

Allylboronic esters are highly versatile intermediates in organic synthesis. In this work, we report a general and scalable strategy for the regioselective deoxygenative borylation of allylic alcohols, enals, enones, and acrylates, upgrading these abundant functional groups in feedstock chemicals and natural products into value-added borylated synthetic handles. This method achieves efficient C–O bond activation under mild electroreductive conditions, and the effective control of regioselectivity was made possible by optimizing the borylating agent and supporting electrolyte. The utility of this approach was further demonstrated in a series of telescoped synthetic sequences, enabling alcohol and carbonyl transposition, formal cross-coupling of alcohols and aldehydes, allylic amination, and vinylogous homologation. This electrosynthetic protocol offers a broadly applicable, modular route to complex allylboron compounds from simple and readily available starting materials, including terpenoid natural products.

Regioselective electrochemical borylation of allylic alcohols, enones, enals, and acrylates is reported, which enables diverse synthetic strategies to upgrade abundant feedstocks and natural products.

Electron bifurcation reactions divide electrons from two-electron donors into high- and low-energy pools by transporting charge on spatially separated low- and high-potential electron hopping pathways. Bifurcation delivers electrons at potentials that drive downstream reactions in photosynthesis, respiration, and biocatalysis. Recent theoretical studies have described the requirements for effective ground-state electron bifurcation. The aim of this study is to design synthetic bifurcation constructs that can be driven by light. We describe a strategy to bifurcate holes (oxidizing equivalents) efficiently with light, and we present an illustrative energy landscape that could support this design. The design focuses on the electrochemical potentials and distances between cofactors. The analysis finds that hole bifurcation may be driven efficiently with light, guiding the further development of bioinspired networks that bifurcate charge and deliver the charges with prescribed electrochemical potentials.

Bioinspired light-driven hole bifurcating networks are designed based on de novo proteins, with the aim of separating holes into spatially separated pools at different electrochemical potentials.

The environmental scientist hitched a ride on a tourist cruise to measure pollutants in Antarctica.

Molecular interactions between receptors and ligands govern critical biological processes, from immune surveillance and T-cell activation to tissue development. However, current techniques for studying binding avidity often sacrifice throughput or precision. We introduce a high-throughput method for quantifying molecular and cellular binding kinetics using a centrifuge force microscope (CFM)─a compact imaging system integrated into a benchtop centrifuge. The CFM performs real-time force measurements on thousands of single cells in parallel, probing receptor–ligand interactions under controlled mechanical stress. To extend these capabilities, we developed a next-generation CFM with dual-channel fluorescence imaging that enables tracking of individual cell unbinding events. To demonstrate its utility, we profiled the binding mechanics of Bispecific T-cell Engager (BiTE) molecules, immunotherapeutic proteins that facilitate T-cell targeting of cancer cells. In cell–protein assays, we quantified the avidity of T and B cells interacting with BiTE-modified surfaces, revealing receptor-specific correlations between ligand concentration and bond strength. In cell–cell assays, we characterized BiTE-mediated adhesion between Jurkat and Nalm6 cells, demonstrating a time-dependent increase in avidity. By integrating force spectroscopy with fluorescence imaging, the CFM provides a high-throughput approach for investigating the mechanochemical principles underlying receptor-mediated interactions, with broad implications for biophysical chemistry, molecular recognition, and therapeutic development.

A high-throughput Centrifuge Force Microscope enables parallel, force-based unbinding studies of molecules or cells, using fluorescence to image single-cell immunological interactions.

Multivariate (MTV) porous materials exhibit unique structural complexities based on their diverse spatial arrangements of multiple building block combinations. These materials possess potential synergistic functionalities that exceed the sum of their individual components. However, the exponentially increasing design complexity of these materials poses significant challenges for accurate ground-state configuration prediction and design. To address this, we propose a Hamiltonian model for quantum computing that integrates compositional, structural, and balance constraints directly into the Hamiltonian, enabling efficient optimization of the MTV configurations. The model employs a graph-based representation to encode linker types as qubits. Our framework enables quantum encoding of a vast linker design space, allowing representation of exponentially many configurations with linearly scaling qubit resources, and facilitating efficient search for optimal structures based on predefined design variables. To validate our model, a variational quantum circuit was constructed and executed using the Sampling Variational Quantum Eigensolver (VQE) algorithm in the IBM Qiskit. Simulations on experimentally known MTV porous materials (e.g., Cu-THQ-HHTP, Py-MV-DBA-COF, MUF-7, and SIOC-COF2) successfully reproduced their ground-state configurations, demonstrating the validity of our model. Furthermore, VQE calculations were performed on a real IBM 127-qubit quantum hardware for validation purposes signaling a first step toward a practical quantum algorithm for the rational design of porous materials.

Quantum algorithms were developed to identify optimal multivariate porous material by exploring linker configurations encoded in qubits and were evaluated by the proposed Hamiltonian model.