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CD45 is a cell surface phosphatase that shapes the T cell receptor signaling threshold but does not have a known ligand. A family of adenovirus proteins, including E3/49K, exploits CD45 to evade immunity by binding to the extracellular domain of CD45, resulting in the suppression of T cell signaling. We determined the cryo-EM structure of this complex and found that the E3/49K protein is composed of three immunoglobulin domains assembled as beads on a string that compel CD45 into a closely abutted dimer by cross-linking the CD45 D3 domain, leading to steric inhibition of its intracellular phosphatase activity. Inspired by the E3/49K mechanism, we engineered CD45 surrogate ligands that can fine-tune T cell activation by dimerizing CD45 into different orientations and proximities. The adenovirus E3/49K protein has taught us that, despite a lack of a known ligand, CD45 activity can be modulated by extracellular dimerizing ligands that perturb its phosphatase activity and alter T cell responses.

Accurately describing protein-ligand binding and unbinding kinetics remains challenging. Computational calculations are difficult and costly, while experimental measurements often lack molecular detail and can be unobtainable. Here, we extend our multiscale milestoning method, Simulation-Enabled Estimation of Kinetics Rates (SEEKR), with metadynamics molecular dynamics simulations to yield accurate small molecule drug residence times. Using the pharmaceutically relevant threonine-tyrosine kinase (TTK) and eight long-residence-time (tens of seconds to hours) inhibitors, we demonstrate accurate prediction of absolute and rank-ordered ligand residence times and free energies of binding.

The μ-opioid receptor (μOR), a prototypical G protein-coupled receptor (GPCR), is the target of opioid analgesics such as morphine and fentanyl. Due to the severe side effects of current opioid drugs, there is considerable interest in developing novel modulators of μOR function. Most GPCR ligands today are small molecules, however biologics, including antibodies and nanobodies, represent alternative therapeutics with clear advantages such as affinity and target selectivity. Here, we describe the nanobody NbE, which selectively binds to the μOR and acts as an antagonist. We functionally characterize NbE as an extracellular and genetically encoded μOR ligand and uncover the molecular basis for μOR antagonism by determining the cryo-EM structure of the NbE-μOR complex. NbE displays a unique ligand binding mode and achieves μOR selectivity by interactions with the orthosteric pocket and extracellular receptor loops. Based on a β-hairpin loop formed by NbE that deeply protrudes into the μOR, we design linear and cyclic peptide analogs that recapitulate NbEs antagonism. The work illustrates the potential of nanobodies to uniquely engage with GPCRs and describes lower molecular weight μOR ligands that can serve as a basis for therapeutic developments.

Positron Emission Tomography (PET) ligands have advanced Alzheimers disease (AD) diagnosis and treatment. Using autoradiography and cryo-EM, we identify AD brain tissue with elevated tau burden, purify filaments, and determine the structure of second-generation high avidity PET ligand MK-6240 at 2.31 Å resolution, which bound at a 1:1 ratio within the cleft of tau paired-helical filament (PHF), engaging with glutamine 351, lysine 353, and isoleucine 360. This information elucidates the basis of MK-6240 PET in quantifying PHF deposits in AD and may facilitate the structure-based design of superior ligands against tau amyloids.

In pharmaceutical discovery, the "magic methyl" effect describes a substantial improvement in the pharmacological properties of a drug candidate with the incorporation of methyl groups. Therefore, to expedite the synthesis of methylated drug analogs, late-stage, undirected methylations of C(sp3)-H bonds in complex molecules would be valuable. However, current methods for site-selective methylations are limited to activated C(sp3)-H bonds. Here we describe a site-selective, undirected methylation of unactivated C(sp3)-H bonds, enabled by photochemically activated peroxides and a nickel(II) complex whose turnover is enhanced by an ancillary ligand. The methodology displays compatibility with a wide range of functional groups and a high selectivity for tertiary C-H bonds, making it suitable for the late-stage methylation of complex organic compounds that contain multiple alkyl C-H bonds, such as terpene natural products, peptides, and active pharmaceutical ingredients. Overall, this method provides a synthetic tool to explore the "magic methyl" effect in drug discovery.

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.

BACKGROUND: Wnt proteins are crucial for embryonic development, stem cell growth, and tissue regeneration. Wnt signaling pathway is activated when Wnt proteins bind to cell membrane receptors. METHODS AND RESULTS: We employed a luciferase reporter assay in HEK293STF cells to measure Wnt protein-induced signaling. We observed that Wnt3a uniquely promotes the Wnt/β-catenin pathway through positive cooperativity. Additionally, MFH-ND, a molecular mimic of Wnt ligands, markedly increased Wnt3a-induced signaling in a dose-responsive manner. This suggests that various Wnt ligands can synergistically enhance Wnt pathway activation. CONCLUSIONS: The study suggests the likelihood of various Wnt ligands coexisting in a single signalosome on the cell membrane, providing new insights into the complexities of Wnt signaling mechanisms.

Message passing neural networks (MPNNs) on molecular graphs generate continuous and differentiable encodings of small molecules with state-of-the-art performance on protein-ligand complex scoring tasks. Here, we describe the proximity graph network (PGN) package, an open-source toolkit that constructs ligand-receptor graphs based on atom proximity and allows users to rapidly apply and evaluate MPNN architectures for a broad range of tasks. We demonstrate the utility of PGN by introducing benchmarks for affinity and docking score prediction tasks. Graph networks generalize better than fingerprint-based models and perform strongly for the docking score prediction task. Overall, MPNNs with proximity graph data structures augment the prediction of ligand-receptor complex properties when ligand-receptor data are available.

Many ion channels are known to behave as an allosteric protein, coupling environmental stimuli captured by specialized sensing domains to the opening of a central pore. The classic Monod-Wyman-Changeux (MWC) model, originally proposed to describe binding of gas molecules to hemoglobin, has been widely used as a framework for analyzing ion channel gating. Here, we address the issue of how accurately the MWC model predicts activation of the capsaicin receptor TRPV1 by vanilloids. Taking advantage of a concatemeric design that makes it possible to lock TRPV1 in states with zero to four bound vanilloid molecules, we showed quantitatively that the overall gating behavior is satisfactorily predicted by the MWC model. There is, however, a small yet detectable subunit position effect: ligand binding to two kitty-corner subunits is 0.3-0.4 kcal/mol more effective in inducing opening than binding to two neighbor subunits. This difference-less than 10% of the overall energetic contribution from ligand binding-might be due to the restriction on subunit arrangement imposed by the planar membrane; if this is the case, then the position effect is not expected in hemoglobin, in which each subunit is related equivalently to all the other subunits.

Synthetic Notch (synNotch) receptors are genetically encoded, modular synthetic receptors that enable mammalian cells to detect environmental signals and respond by activating user-prescribed transcriptional programs. Although some materials have been modified to present synNotch ligands with coarse spatial control, applications in tissue engineering generally require extracellular matrix (ECM)-derived scaffolds and/or finer spatial positioning of multiple ligands. Thus, we develop here a suite of materials that activate synNotch receptors for generalizable engineering of material-to-cell signaling. We genetically and chemically fuse functional synNotch ligands to ECM proteins and ECM-derived materials. We also generate tissues with microscale precision over four distinct reporter phenotypes by culturing cells with two orthogonal synNotch programs on surfaces microcontact-printed with two synNotch ligands. Finally, we showcase applications in tissue engineering by co-transdifferentiating fibroblasts into skeletal muscle or endothelial cell precursors in user-defined micropatterns. These technologies provide avenues for spatially controlling cellular phenotypes in mammalian tissues.

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, whereas its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here, we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify CFTR modulators. We docked ∼155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered mid-nanomolar potentiators, as well as inhibitors, that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

Cellular signaling, crucial for biological processes like immune response and homeostasis, relies on specificity and fidelity in signal transduction to accurately respond to stimuli amidst biological noise. Kinetic proofreading (KPR) is a key mechanism enhancing signaling specificity through time-delayed steps, although its effectiveness is debated due to intrinsic noise potentially reducing signal fidelity. In this study, we reformulate the theory of kinetic proofreading (KPR) by convolving multiple intermediate states into a single state and then define an overall processing time required to traverse these states. This simplification allows us to succinctly describe kinetic proofreading in terms of a single waiting time parameter, facilitating a more direct evaluation and comparison of KPR performance across different biological contexts such as DNA replication and T cell receptor (TCR) signaling. We find that loss of fidelity for longer proofreading steps relies on the specific strategy of information extraction and show that in the first-passage time (FPT) discrimination strategy, longer proofreading steps can exponentially improve the accuracy of KPR at the cost of speed. Thus, KPR can still be an effective discrimination mechanism in the high noise regime. However, in a product concentration-based discrimination strategy, longer proofreading steps do not necessarily lead to an increase in performance. However, by introducing activation thresholds on product concentrations, can we decompose the product-based strategy into a series of FPT-based strategies to better resolve the subtleties of KPR-mediated product discrimination. Our findings underscore the importance of understanding KPR in the context of how information is extracted and processed in the cell.

We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).

Imaging scaffolds composed of designed protein cages fused to designed ankyrin repeat proteins (DARPins) have enabled the structure determination of small proteins by cryogenic electron microscopy (cryo-EM). One particularly well characterized scaffold type is a symmetric tetrahedral assembly composed of 24 subunits, 12 A and 12 B, which has three cargo-binding DARPins positioned on each vertex. Here, the X-ray crystal structure of a representative tetrahedral scaffold in the apo state is reported at 3.8 Å resolution. The X-ray crystal structure complements recent cryo-EM findings on a closely related scaffold, while also suggesting potential utility for crystallographic investigations. As observed in this crystal structure, one of the three DARPins, which serve as modular adaptors for binding diverse `cargo proteins, present on each of the vertices is oriented towards a large solvent channel. The crystal lattice is unusually porous, suggesting that it may be possible to soak crystals of the scaffold with small (≤30 kDa) protein cargo ligands and subsequently determine cage-cargo structures via X-ray crystallography. The results suggest the possibility that cryo-EM scaffolds may be repurposed for structure determination by X-ray crystallography, thus extending the utility of electron-microscopy scaffold designs for alternative structural biology applications.

We report our initial real-world experience with 177Lu-PSMA-617 radioligand therapy. Methods: We performed a retrospective review of patients treated with 177Lu-PSMA-617. Pretreatment PSMA PET, laboratory findings, overall survival, a fall in prostate-specific antigen by 50% (PSA50), and toxicities were evaluated. Results: Ninety-nine patients were included. Sixty patients achieved a PSA50. Seven of 18 (39%) patients who did not meet the TheraP PSMA imaging criteria achieved a PSA50. Nineteen of 31 (61%) patients who did not meet the VISION laboratory criteria achieved a PSA50. Sixty-three patients had a delay or stoppage in therapy, which was due to a good response in 19 patients and progressive disease in 14 patients. Of 10 patients with a good response who restarted treatment, 9 subsequently achieved a PSA50 on retreatment. The most common toxicities were anemia (33%) and thrombocytopenia (21%). Conclusion: At our center, patients who did not meet the TheraP PSMA imaging criteria or the VISION laboratory criteria benefited from 177Lu-PSMA-617 radioligand therapy.

Schwann cells (SCs) undergo phenotypic transformation and then orchestrate nerve repair following PNS injury. The ligands and receptors that activate and sustain SC transformation remain incompletely understood. Proteins released by injured axons represent important candidates for activating the SC Repair Program. The low-density lipoprotein receptor-related protein-1 (LRP1) is acutely up-regulated in SCs in response to injury, activating c-Jun, and promoting SC survival. To identify novel LRP1 ligands released in PNS injury, we applied a discovery-based approach in which extracellular proteins in the injured nerve were captured using Fc-fusion proteins containing the ligand-binding motifs of LRP1 (CCR2 and CCR4). An intracellular neuron-specific protein, Protein Kinase C and Casein Kinase Substrate in Neurons (PACSIN1) was identified and validated as an LRP1 ligand. Recombinant PACSIN1 activated c-Jun and ERK1/2 in cultured SCs. Silencing Lrp1 or inhibiting the LRP1 cell-signaling co-receptor, the NMDA-R, blocked the effects of PACSIN1 on c-Jun and ERK1/2 phosphorylation. Intraneural injection of PACSIN1 into crush-injured sciatic nerves activated c-Jun in wild-type mice, but not in mice in which Lrp1 is conditionally deleted in SCs. Transcriptome profiling of SCs revealed that PACSIN1 mediates gene expression events consistent with transformation to the repair phenotype. PACSIN1 promoted SC migration and viability following the TNFα challenge. When Src family kinases were pharmacologically inhibited or the receptor tyrosine kinase, TrkC, was genetically silenced or pharmacologically inhibited, PACSIN1 failed to induce cell signaling and prevent SC death. Collectively, these studies demonstrate that PACSIN1 is a novel axon-derived LRP1 ligand that activates SC repair signaling by transactivating TrkC.

The blood-brain barrier (BBB) poses a significant obstacle in developing therapeutics for neurodegenerative diseases and central nervous system (CNS) disorders. P-glycoprotein (P-gp), a multidrug resistance protein, is a critical gatekeeper in the BBB and plays a role in cancer chemoresistance. This paper uses cryo-EM P-gp structures as starting points with an induced fit docking (IFD) model to evaluate 19 pairs of compounds with known P-gp efflux data. The study reveals significant differences in binding energy and sheds light on structural modifications impact on efflux properties. In the cases examined, fluorine incorporation influences the efflux by altering the molecular conformation rather than proximal heteroatom basicity. Although there are limitations in addressing covalent interactions or when binding extends into the more flexible vestibule region of the protein, the results provide valuable insights and potential strategies to overcome P-gp efflux, contributing to the advancement of drug development for both CNS disorders and cancer therapies.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from

Individual cell sensing of external cues has evolved through the temporal patterns in signaling. Since nuclear factor κB (NF-κB) signaling dynamics have been examined using a single subunit, RelA, it remains unclear whether more information might be transmitted via other subunits. Using NF-κB double-knockin reporter mice, we monitored both canonical NF-κB subunits, RelA and c-Rel, simultaneously in single macrophages by quantitative live-cell imaging. We show that signaling features of RelA and c-Rel convey more information about the stimuli than those of either subunit alone. Machine learning is used to predict the ligand identity accurately based on RelA and c-Rel signaling features without considering the co-activated factors. Ligand discrimination is achieved through selective non-redundancy of RelA and c-Rel signaling dynamics, as well as their temporal coordination. These results suggest a potential role of c-Rel in fine-tuning immune responses and highlight the need for approaches that will elucidate the mechanisms regulating NF-κB subunit specificity.

Programmed death-ligand 1 (PD-L1) is a promising target for cancer immunotherapy due to its ability to inhibit T cell activation; however, its expression on various noncancer cells may cause on-target off-tumor toxicity when designing PD-L1-targeting Chimeric Antigen Receptor (CAR) T cell therapies. Combining rational design and directed evolution of the human fibronectin-derived monobody scaffold, PDbody was engineered to bind to PD-L1 with a preference for a slightly lower pH, which is typical in the tumor microenvironment. PDbody was further utilized as a CAR to target the PD-L1-expressing triple negative MDA-MB-231 breast cancer cell line. To mitigate on-target off-tumor toxicity associated with targeting PD-L1, a Cluster of Differentiation 19 (CD19)-recognizing SynNotch IF THEN gate was integrated into the system. This CD19-SynNotch PDbody-CAR system was then expressed in primary human T cells to target CD19-expressing MDA-MB-231 cancer cells. These CD19-SynNotch PDbody-CAR T cells demonstrated both specificity and efficacy in vitro, accurately eradicating cancer targets in cytotoxicity assays. Moreover, in an in vivo bilateral murine tumor model, they exhibited the capability to effectively restrain tumor growth. Overall, CD19-SynNotch PDbody-CAR T cells represent a distinct development over previously published designs due to their increased efficacy, proliferative capability, and mitigation of off-tumor toxicity for solid tumor treatment.

Obtaining accurate binding free energies from in silico screens has been a long-standing goal for the computational chemistry community. However, accuracy and computational cost are at odds with one another, limiting the utility of methods that perform this type of calculation. Many methods achieve massive scale by explicitly or implicitly assuming that the target protein adopts a single structure, or undergoes limited fluctuations around that structure, to minimize computational cost. Others simulate each protein-ligand complex of interest, accepting lower throughput in exchange for better predictions of binding affinities. Here, we present the PopShift framework for accounting for the ensemble of structures a protein adopts and their relative probabilities. Protein degrees of freedom are enumerated once, and then arbitrarily many molecules can be screened against this ensemble. Specifically, we use Markov state models (MSMs) as a compressed representation of a proteins thermodynamic ensemble. We start with a ligand-free MSM and then calculate how addition of a ligand shifts the populations of each protein conformational state based on the strength of the interaction between that protein conformation and the ligand. In this work we use docking to estimate the affinity between a given protein structure and ligand, but any estimator of binding affinities could be used in the PopShift framework. We test PopShift on the classic benchmark pocket T4 Lysozyme L99A. We find that PopShift is more accurate than common strategies, such as docking to a single structure and traditional ensemble docking─producing results that compare favorably with alchemical binding free energy calculations in terms of RMSE but not correlation─and may have a more favorable computational cost profile in some applications. In addition to predicting binding free energies and ligand poses, PopShift also provides insight into how the probability of different protein structures is shifted upon addition of various concentrations of ligand, providing a platform for predicting affinities and allosteric effects of ligand binding. Therefore, we expect PopShift will be valuable for hit finding and for providing insight into phenomena like allostery.

Molecular docking is a widely used technique for leveraging protein structure for ligand discovery, but it remains difficult to utilize due to limitations that have not been adequately addressed. Despite some progress toward automation, docking still requires expert guidance, hindering its adoption by a broader range of investigators. To make docking more accessible, we developed a new utility called DockOpt, which automates the creation, evaluation, and optimization of docking models prior to their deployment in large-scale prospective screens. DockOpt outperforms our previous automated pipeline across all 43 targets in the DUDE-Z benchmark data set, and the generated models for 84% of targets demonstrate sufficient enrichment to warrant their use in prospective screens, with normalized LogAUC values of at least 15%. DockOpt is available as part of the Python package Pydock3 included in the UCSF DOCK 3.8 distribution, which is available for free to academic researchers at https://dock.compbio.ucsf.edu and free for everyone upon registration at https://tldr.docking.org.

Auranofin, an FDA-approved drug for rheumatoid arthritis, has emerged as a promising antiparasitic medication in recent years. The gold(I) ion in auranofin is postulated to be responsible for its antiparasitic activity. Notably, aurothiomalate and aurothioglucose also contain gold(I), and, like auranofin, they were previously used to treat rheumatoid arthritis. Whether they have antiparasitic activity remains to be elucidated. Herein, we demonstrated that auranofin and similar derivatives, but not aurothiomalate and aurothioglucose, inhibited the growth of Toxoplasma gondii in vitro. We found that auranofin affected the T. gondii biological cycle (lytic cycle) by inhibiting T. gondiis invasion and triggering its egress from the host cell. However, auranofin could not prevent parasite replication once T. gondii resided within the host. Auranofin treatment induced apoptosis in T. gondii parasites, as demonstrated by its reduced size and elevated phosphatidylserine externalization (PS). Notably, the gold from auranofin enters the cytoplasm of T. gondii, as demonstrated by scanning transmission electron microscopy-energy dispersive X-ray spectroscopy (STEM-EDS) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS).IMPORTANCEToxoplasmosis, caused by Toxoplasma gondii, is a devastating disease affecting the brain and the eyes, frequently affecting immunocompromised individuals. Approximately 60 million people in the United States are already infected with T. gondii, representing a population at-risk of developing toxoplasmosis. Recent advances in treating cancer, autoimmune diseases, and organ transplants have contributed to this at-risk populations exponential growth. Paradoxically, treatments for toxoplasmosis have remained the same for more than 60 years, relying on medications well-known for their bone marrow toxicity and allergic reactions. Discovering new therapies is a priority, and repurposing FDA-approved drugs is an alternative approach to speed up drug discovery. Herein, we report the effect of auranofin, an FDA-approved drug, on the biological cycle of T. gondii and how both the phosphine ligand and the gold molecule determine the anti-parasitic activity of auranofin and other gold compounds. Our studies would contribute to the pipeline of candidate anti-T. gondii agents.

BACKGROUND: The combination of monalizumab (anti-NKG2A/CD94) and durvalumab (anti-programmed death ligand-1) may promote antitumor immunity by targeting innate and adaptive immunity. This phase 1/2 study of monalizumab and durvalumab evaluated safety, antitumor activity, and pharmacodynamics in patients with advanced solid tumors. MAIN BODY: Immunotherapy-naïve patients aged ≥18 years with advanced disease, Eastern Cooperative Oncology Group performance status of 0-1, and 1-3 prior lines of systemic therapy in the recurrent/metastatic setting were enrolled. In part 1 (dose escalation), patients received durvalumab 1500 mg every 4 weeks (Q4W) with increasing doses of monalizumab Q2W/Q4W (n=15). Dose expansion in part 1 included patients with cervical cancer (n=15; durvalumab 1500 mg Q4W and monalizumab 750 mg Q2W) or metastatic microsatellite stable (MSS)-colorectal cancer (CRC) (n=15; durvalumab 1500 mg Q4W and monalizumab 750 mg Q4W). In part 2 (dose expansion), patients with MSS-CRC (n=40), non-small cell lung cancer (NSCLC; n=20), MSS-endometrial cancer (n=40), or ovarian cancer (n=40) received durvalumab 1500 mg Q4W and monalizumab 750 mg Q2W. The primary endpoint was safety. Secondary endpoints included antitumor activity per Response Evaluation Criteria In Solid Tumors version 1.1 (RECIST v1.1). Exploratory analyses included assessment of T-cell and natural killer (NK) cell activation and proliferation in peripheral blood and the tumor microenvironment (TME). The study enrolled 185 patients (part 1, 45; part 2, 140). No dose-limiting toxicities were observed and the maximum tolerated dose was not reached. In part 2, the most common treatment-related adverse events were fatigue (12.1%), asthenia (9.3%), diarrhea (9.3%), pruritus (7.9%), and pyrexia (7.1%). In the expansion cohorts, response rates were 0% (cervical), 7.7% (MSS-CRC), 10% (NSCLC), 5.4% (ovarian), and 0% (MSS-endometrial). Sustained NK cell activation, CD8+ T-cell proliferation, increased serum levels of CXCL10 (C-X-C motif chemokine ligand 10) and CXCL11, and increased tumor infiltration of CD8+ and granzyme B+ cells were observed. CONCLUSIONS: Although efficacy was modest, monalizumab plus durvalumab was well tolerated and encouraging immune activation was observed in the peripheral blood and TME. TRIAL REGISTRATION NUMBER: NCT02671435.

Carbon monoxide poisoning is one of the most common forms of poisoning in the world. Although the primary mode of treatment, oxygen therapy, is highly effective in many cases, there are instances in which it is inadequate or inappropriate. Whereas oxygen therapy relies on high levels of a low-affinity ligand (O2) to displace a high-affinity ligand (CO) from metalloproteins, an antidote strategy relies on introducing a molecule with a higher affinity for CO than native proteins (Kantidote,CO > Kprotein,CO). Based on the fundamental chemistry of CO, such an antidote is most likely required to be an inorganic compound featuring an electron-rich transition metal. A review is provided of the protein-, supramolecular complex-, and small molecule-based CO poisoning antidote platforms that are currently under investigation.

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the proteins symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligands docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

Chemical methods for the extraction and refinement of technologically critical rare earth elements (REEs) are energy-intensive, hazardous, and environmentally destructive. Current biobased extraction systems rely on extremophilic organisms and generate many of the same detrimental effects as chemical methodologies. The mesophilic methylotrophic bacterium Methylobacterium extorquens AM1 was previously shown to grow using electronic waste by naturally acquiring REEs to power methanol metabolism. Here we show that growth using electronic waste as a sole REE source is scalable up to 10 L with consistent metal yields without the use of harsh acids or high temperatures. The addition of organic acids increases REE leaching in a nonspecific manner. REE-specific bioleaching can be engineered through the overproduction of REE-binding ligands (called lanthanophores) and pyrroloquinoline quinone. REE bioaccumulation increases with the leachate concentration and is highly specific. REEs are stored intracellularly in polyphosphate granules, and genetic engineering to eliminate exopolyphosphatase activity increases metal accumulation, confirming the link between phosphate metabolism and biological REE use. Finally, we report the innate ability of M. extorquens to grow using other complex REE sources, including pulverized smartphones, demonstrating the flexibility and potential for use as a recovery platform for these critical metals.

BACKGROUND: Immune checkpoint inhibitors (ICIs), antibodies targeting PD-1 (programmed cell death protein 1)/PD-L1 (programmed death-ligand 1) or CTLA4 (cytotoxic T-lymphocyte-associated protein 4), have revolutionized cancer management but are associated with devastating immune-related adverse events including myocarditis. The main risk factor for ICI myocarditis is the use of combination PD-1 and CTLA4 inhibition. ICI myocarditis is often fulminant and is pathologically characterized by myocardial infiltration of T lymphocytes and macrophages. Although much has been learned about the role of T-cells in ICI myocarditis, little is understood about the identity, transcriptional diversity, and functions of infiltrating macrophages. METHODS: We used an established murine ICI myocarditis model (Ctla4+/-Pdcd1-/- mice) to explore the cardiac immune landscape using single-cell RNA-sequencing, immunostaining, flow cytometry, in situ RNA hybridization, molecular imaging, and antibody neutralization studies. RESULTS: We observed marked increases in CCR2 (C-C chemokine receptor type 2)+ monocyte-derived macrophages and CD8+ T-cells in this model. The macrophage compartment was heterogeneous and displayed marked enrichment in an inflammatory CCR2+ subpopulation highly expressing Cxcl9 (chemokine [C-X-C motif] ligand 9), Cxcl10 (chemokine [C-X-C motif] ligand 10), Gbp2b (interferon-induced guanylate-binding protein 2b), and Fcgr4 (Fc receptor, IgG, low affinity IV) that originated from CCR2+ monocytes. It is important that a similar macrophage population expressing CXCL9, CXCL10, and CD16α (human homologue of mouse FcgR4) was expanded in patients with ICI myocarditis. In silico prediction of cell-cell communication suggested interactions between T-cells and Cxcl9+Cxcl10+ macrophages via IFN-γ (interferon gamma) and CXCR3 (CXC chemokine receptor 3) signaling pathways. Depleting CD8+ T-cells or macrophages and blockade of IFN-γ signaling blunted the expansion of Cxcl9+Cxcl10+ macrophages in the heart and attenuated myocarditis, suggesting that this interaction was necessary for disease pathogenesis. CONCLUSIONS: These data demonstrate that ICI myocarditis is associated with the expansion of a specific population of IFN-γ-induced inflammatory macrophages and suggest the possibility that IFN-γ blockade may be considered as a treatment option for this devastating condition.

Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel NaV1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to NaV1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.

Plants sense abscisic acid (ABA) using chemical-induced dimerization (CID) modules, including the receptor PYR1 and HAB1, a phosphatase inhibited by ligand-activated PYR1. This system is unique because of the relative ease with which ligand recognition can be reprogrammed. To expand the PYR1 system, we designed an orthogonal * module, which harbors a dimer interface salt bridge; X-ray crystallographic, biochemical and in vivo analyses confirm its orthogonality. We used this module to create PYR1*MANDI/HAB1* and PYR1*AZIN/HAB1*, which possess nanomolar sensitivities to their activating ligands mandipropamid and azinphos-ethyl. Experiments in Arabidopsis thaliana and Saccharomyces cerevisiae demonstrate the sensitive detection of banned organophosphate contaminants using living biosensors and the construction of multi-input/output genetic circuits. Our new modules enable ligand-programmable multi-channel CID systems for plant and eukaryotic synthetic biology that can empower new plant-based and microbe-based sensing modalities.

Targeted alpha therapy (TAT) pairs the specificity of antigen targeting with the lethality of alpha particles to eradicate cancerous cells. Actinium-225 [225Ac; t1/2 = 9.920(3) days] is an alpha-emitting radioisotope driving the next generation of TAT radiopharmaceuticals. Despite promising clinical results, a fundamental understanding of Ac coordination chemistry lags behind the rest of the Periodic Table due to its limited availability, lack of stable isotopes, and inadequate systems poised to probe the chemical behavior of this radionuclide. In this work, we demonstrate a platform that combines an 8-coordinate synthetic ligand and a mammalian protein to characterize the solution and solid-state behavior of the longest-lived Ac isotope, 227Ac [t1/2 = 21.772(3) years]. We expect these results to direct renewed efforts for 225Ac-TAT development, aid in understanding Ac coordination behavior relative to other +3 lanthanides and actinides, and more broadly inform this element's position on the Periodic Table.

Chitin is an abundant biopolymer and pathogen-associated molecular pattern that stimulates a host innate immune response. Mammals express chitin-binding and chitin-degrading proteins to remove chitin from the body. One of these proteins, Acidic Mammalian Chitinase (AMCase), is an enzyme known for its ability to function under acidic conditions in the stomach but is also active in tissues with more neutral pHs, such as the lung. Here, we used a combination of biochemical, structural, and computational modeling approaches to examine how the mouse homolog (mAMCase) can act in both acidic and neutral environments. We measured kinetic properties of mAMCase activity across a broad pH range, quantifying its unusual dual activity optima at pH 2 and 7. We also solved high-resolution crystal structures of mAMCase in complex with oligomeric GlcNAcn, the building block of chitin, where we identified extensive conformational ligand heterogeneity. Leveraging these data, we conducted molecular dynamics simulations that suggest how a key catalytic residue could be protonated via distinct mechanisms in each of the two environmental pH ranges. These results integrate structural, biochemical, and computational approaches to deliver a more complete understanding of the catalytic mechanism governing mAMCase activity at different pH. Engineering proteins with tunable pH optima may provide new opportunities to develop improved enzyme variants, including AMCase, for therapeutic purposes in chitin degradation.

Programmed cell death protein-1 (PD-1)/programmed death ligand-1 (PD-L1) immune checkpoint blockade as a breakthrough in cancer immunotherapy has shown unprecedented positive outcomes in the clinic. However, the overall effectiveness of PD-L1 antibody is less than expected. An increasing number of studies have demonstrated that PD-L1 is widely distributed and expressed not only on the cell membrane but also on the inside of the cells as well as on the extracellular vesicles secreted by tumour cells. Both endogenous and exogenous PD-L1 play significant roles in influencing the therapeutic effect of anti-tumour immunity. Herein, we mainly focused on the distribution and function of PD-L1 and further summarized the potential targeted therapeutic strategies. More importantly, in addition to taking the overall expression abundance of PD-L1 as a predictive indicator for selecting corresponding PD-1/PD-L1 monoclonal antibodies (mAbs), we also proposed that personalized combination therapies based on the different distribution of PD-L1 are worth attention to achieve more efficient and effective therapeutic outcomes in cancer patients. LINKED ARTICLES: This article is part of a themed issue on Cancer Microenvironment and Pharmacological Interventions. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.2/issuetoc.

FGF9 is a potent mitogen and survival factor, but FGF9 protein levels are generally low and restricted to a few adult organs. Aberrant expression of FGF9 usually results in cancer. However, the mechanism of FGF9 action has not been fully established. Previous studies showed that FGF1 and FGF2 directly bind to integrin αvβ3, and this interaction is critical for signaling functions (FGF-integrin crosstalk). FGF1 and FGF2 mutants defective in integrin binding were defective in signaling, whereas the mutants still bound to FGFR suppressed angiogenesis and tumor growth, indicating that they act as antagonists. We hypothesize that FGF9 requires direct integrin binding for signaling. Here, we show that docking simulation of the interaction between FGF9 and αvβ3 predicted that FGF9 binds to the classical ligand-binding site of αvβ3. We show that FGF9 bound to integrin αvβ3 and generated FGF9 mutants in the predicted integrin-binding interface. An FGF9 mutant (R108E) was defective in integrin binding, activating FRS2α and ERK1/2, inducing DNA synthesis, cancer cell migration, and invasion in vitro. R108E suppressed DNA synthesis and activation of FRS2α and ERK1/2 induced by WT FGF9 (dominant-negative effect). These findings indicate that FGF9 requires direct integrin binding for signaling and that R108E has potential as an antagonist to FGF9 signaling.

ABSTRACT This research article provides a comprehensive analysis of the preparation, structural characterization, 3D modeling, and biological screening of two novel formulated metal complexes, NiPDBZNPH and CuPDBZNPH. These complexes were obtained by combining 2,2′‐pyridine‐2,6‐diylbis(1H‐benzimidazole) (PDBZ) and 2‐hydroxy‐naphthaldehyde Schiff‐base (NPH) ligands with Ni(II) and Cu(II) ions, resulting in the compounds [Ni (NPH)(PDBZ)(Cl)] and [Cu (NPH)(PDBZ)(Cl)], respectively. Spectroscopic and analytical techniques confirmed that both complexes exhibit octahedral geometry around the central metal ion. Computational studies using density functional theory (DFT) corroborated the molecular structures and investigated the quantum chemical properties of the ligands and complexes. A series of in vitro assays were conducted to assess their anti‐inflammatory, antifungal, antibacterial, and antioxidant properties, revealing enhanced bioactivity compared to the uncoordinated ligands. The potential of NiPDBZNPH and CuPDBZNPH as therapeutic candidates was also explored through interactions with calf thymus DNA (CT‐DNA). Molecular docking simulations targeting specific protein receptors were performed to evaluate binding affinities and ligand–protein interactions, with results highlighting significant interactions within enzyme active sites. These findings emphasize the pivotal role of metal–ligand coordination in enhancing pharmacological properties and contribute valuable insights toward the design of novel therapeutic compounds for use in medicinal chemistry and pharmaceutical research. [ABSTRACT FROM AUTHOR]

Herein, we have demonstrated a palladium‐catalyzed γ‐alkenylation of unactivated alkenes with vinylcyclopropanes. A bidentate 8‐aminoquinoline directing group was utilized for the regioselective γ‐C(alkenyl)−H functionalization of unactivated alkenes with vinylcyclopropanes. This protocol exhibits wide substrate scope and good selectivity. Additionally, substrate diversification was performed to demonstrate the synthetic utility of the protocol. Mechanistic investigations were carried out to provide an insight to the reaction mechanism. A plausible mechanism was also proposed for the present methodology. [ABSTRACT FROM AUTHOR]

Aggregated forms of different proteins are common hallmarks for several neurodegenerative diseases, including Alzheimer's disease, and ligands that selectively detect specific protein aggregates are vital. Herein, we investigate the molecular requirements of thiophene‐vinyl‐benzothiazole based ligands to detect a specific type of Aβ deposits found in individuals with dominantly inherited Alzheimer's disease caused by the Arctic APP E693G mutation. The staining of these Aβ deposits was alternated when switching the terminal heterocyclic moiety attached to the thiophene‐vinyl‐benzothiazole scaffold. The most prevalent staining was observed for ligands having a terminal 3‐methyl‐1H‐indazole moiety or a terminal 1,2‐dimethoxybenzene moiety, verifying that specific molecular interactions between these ligands and the aggregates were necessary. The synthesis of additional thiophene‐vinyl‐benzothiazole ligands aided in pinpointing additional crucial chemical determinants, such as positioning of nitrogen atoms and methyl substituents, for achieving optimal staining of Aβ aggregates. When combining the optimized thiophene‐vinyl‐benzothiazole based ligands with a conventional ligand, CN‐PiB, distinct staining patterns were observed for sporadic Alzheimer's disease versus dominantly inherited Alzheimer's disease caused by the Arctic APP E693G mutation. Our findings provide chemical insights for developing novel ligands that allow for a more precise assignment of Aβ deposits, and might also aid in creating novel agents for clinical imaging of distinct Aβ aggregates in AD. [ABSTRACT FROM AUTHOR]

In this research work, the catalytic performances of two manganese-based catalysts, manganese (III) acetylacetonate (Mn(acac)3) and manganese tallate (Mn-TO), were studied during the process of Ashalcha heavy oil oxidation under in situ combustion conditions. DSC analysis shows distinct thermal behavior of both ligated catalysts during low- and high-temperature oxidation phases (LTO and HTO); for example, the shifting in peak temperature (Tp) in the HTO at a heating rate of 10 °C/min was reduced by approximately 5.3% for Mn-TO and 2.24% for Mn(acac)3 when compared with uncatalyzed heavy oil. Combined isothermal kinetic analyses using the Friedman and Kissinger–Akahira–Sunose analytic methods have provided insights about activation energies and frequency factors over the whole conversion range, where the catalytic performance of Mn-TO showed low activation energies in both LTO and HTO (Eα of Mn-TO was approximately 13.33% (LTO) and 7.68% (HTO) less than with the heavy oil alone). In addition, calculations of the effective rate constant confirmed the increased oxidation rate trend of both catalysts, with Mn-TO exhibiting the highest values. The findings highlight the potential of these manganese-based catalysts, the Mn-TO catalyst in particular, in optimizing heavy oil oxidation processes. The overall results further contribute to developing more efficient ligand catalyst complexes for sustainable heavy oil recovery while continuously improving their efficient application during in situ combustion in the petroleum industry. [ABSTRACT FROM AUTHOR]

AbstractMethane activation and functionalization under catalytic conditions remains a challenge that must be addressed to make this abundant alkane, the primary component of natural gas, into a more useful resource. One possible method of methane activation is concerted metalation-deprotonation (CMD), which thus far has been largely limited to precious metals and more reactive substrates. In this DFT study, CMD activation of methane is assessed employing more earth-abundant 3d transition metal complexes to assess the effects of metal, ligands, etc. upon the kinetics and thermodynamics of methane C–H activation via CMD mechanisms. Key findings from this study reveal the strong influence spin states as well as ligand modification have on the activation energy barriers. Moreover, an unexpected observation pertaining to ligand modification was seen where the acetate ligand exhibited higher computed free energy barriers compared to the trifluoroacetate ligand. Although acetate is more basic than trifluoroacetate, the ligand directing effects ultimately had a greater influence on the thermodynamic control of the CMD mechanism being studied here. [ABSTRACT FROM AUTHOR]

Stem cell factors (SCFs) are pivotal factors existing in both soluble and membrane-bound forms, expressed by endothelial cells (ECs) and fibroblasts throughout the body. These factors enhance cell growth, viability, and migration in multipotent cell lineages. The preferential expression of SCF by arteriolar ECs indicates that arterioles create a unique microenvironment tailored to hematopoietic stem cells (HSCs). Insufficiency of SCF within bone marrow (BM)-derived adipose tissue results in decreased their overall cellularity, affecting HSCs and their immediate progenitors critical for generating diverse blood cells and maintaining the hematopoietic microenvironment. SCF deficiency disrupts BM function, impacting the production and differentiation of HSCs. Additionally, deleting SCF from adipocytes reduces lipogenesis, highlighting the crucial role of SCF/c-kit signaling in controlling lipid accumulation. This review elucidates the sources, roles, mechanisms, and molecular strategies of SCF in bone renewal, offering a comprehensive overview of recent advancements, challenges, and future directions for leveraging SCF as a key agent in regenerative medicine. [ABSTRACT FROM AUTHOR]

We have explored NHSi‐supported copper(I) complexes as active and highly efficient catalysts for A3 (aldehyde‐alkyne‐amine) and KA2 (ketone‐alkyne‐amine) three‐component coupling reactions to synthesize propargyl amines in excellent yields with high TOF under solvent‐and additive‐free conditions. [ABSTRACT FROM AUTHOR]

Nanoparticle-based thin films are increasingly being used in various applications. One of the key factors that determines the properties and performances of these films is the type of ligands attached to the nanoparticle surfaces. While long-chain surfactants, such as oleic acid, are commonly employed to stabilize nanoparticles and ensure high monodispersity, these ligands often hinder charge transport due to their insulating nature. Although thermal annealing can remove the long-chain ligands, the removal process often introduces defects such as cracks and voids. In contrast, the use of short-chain organic or inorganic ligands can minimize interparticle distance, improving film conductivity, though challenges such as incomplete ligand exchange and residual barriers remain. Polymeric ligands, especially block copolymers, can also be employed to create films with tailored porosity. This review discusses the effects of various ligand types on the morphology and performance of nanoparticle-based films, highlighting the trade-offs between conductivity, structural integrity, and functionality. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive examination of non-canonical DNA structures, particularly focusing on G-quadruplexes (G4s) and i-motifs. G-quadruplexes, four-stranded structures formed by guanine-rich sequences, are stabilized by Hoogsteen hydrogen bonds and monovalent cations like potassium. These structures exhibit diverse topologies and are implicated in critical genomic regions such as telomeres and promoter regions of oncogenes, playing significant roles in gene expression regulation, genome stability, and cellular aging. I-motifs, formed by cytosine-rich sequences under acidic conditions and stabilized by hemiprotonated cytosine–cytosine (C:C+) base pairs, also contribute to gene regulation despite being less prevalent than G4s. This review highlights the factors influencing the stability and dynamics of these structures, including sequence composition, ionic conditions, and environmental pH. Molecular dynamics simulations and high-resolution structural techniques have been pivotal in advancing our understanding of their folding and unfolding mechanisms. Additionally, the article discusses the therapeutic potential of small molecules designed to selectively bind and stabilize G4s and i-motifs, with promising implications for cancer treatment. Furthermore, the structural properties of these DNA forms are explored for applications in nanotechnology and molecular devices. Despite significant progress, challenges remain in observing these structures in vivo and fully elucidating their biological functions. The review underscores the importance of continued research to uncover new insights into the genomic roles of G4s and i-motifs and their potential applications in medicine and technology. This ongoing research promises exciting developments in both basic science and applied fields, emphasizing the relevance and future prospects of these intriguing DNA structures. [ABSTRACT FROM AUTHOR]

Objective: To investigate the associations between apparent diffusion coefficient (ADC) values extracted from three different region of interest (ROI) position approaches and programmed cell death ligand-1 (PD-L1) expression, and evaluate the performance of the nomogram established based on ADC values and clinicopathological parameters in predicting PD-L1 expression in cervical cancer (CC) patients. Methods: Through retrospective recruitment, a training cohort of 683 CC patients was created, and a validation cohort of 332 CC patients was prospectively recruited. ROIs were delineated using three different methods to measure the mean ADC (ADCmean), single-section ADC (ADCss), and the minimum ADC of tumors (ADCmin). Logistic regression was employed to identify independent factors related to PD-L1 expression. A nomogram was drawn based on ADC values combined with clinicopathological features, its discrimination and calibration performances were estimated using the area under the curve (AUC) of receiver operating characteristic and calibration curve. The clinical benefits were evaluated by decision curve analysis. Results: The ADCmin independently correlated with PD-L1 expression. The nomogram constructed with ADCmin and other independent clinicopathological-related factors: FIGO staging, pathological grade, parametrial invasion, and lymph node status demonstrated excellent diagnostic performance (AUC = 0.912 and 0.903, respectively), good calibration capacities, and greater net benefits compared to the clinicopathological model in both the training and validation cohorts. Conclusion: ADCmin independently correlated PD-L1 expression, and the nomogram established with ADCmin and clinicopathological independent prognostic factors had a strong predictive performance for PD-L1 expression, thereby serving as a promising tool for selecting cases eligible for immunotherapy. Clinical relevance statement: The minimum ADC can serve as a reliable imaging biomarker related to PD-L1 expression; the established nomogram combines the minimum ADC and clinicopathological factors that can assist clinical immunotherapy decisions. Key Points: Diffusion-weighted imaging quantitative parameters can characterize the internal characteristics of tumor tissue. The minimum ADC significantly correlated with programmed cell death ligand-1 expression. The proposed nomogram can assist clinicians with immunotherapy decision-making for patients with CC. [ABSTRACT FROM AUTHOR]

γ‐Hydroxybutyric acid (GHB) analogs are small molecules that bind competitively to a specific cavity in the oligomeric CaMKIIα hub domain. Binding affects conformation and stability of the hub domain, which may explain the neuroprotective action of some of these compounds. Here, we describe molecular details of interaction of the larger‐type GHB analog 2‐(6‐(4‐chlorophenyl)imidazo[1,2‐b]pyridazine‐2‐yl)acetic acid (PIPA). Like smaller‐type analogs, PIPA binding to the CaMKIIα hub domain promoted thermal stability. PIPA additionally modulated CaMKIIα activity under sub‐maximal CaM concentrations and ultimately led to reduced substrate phosphorylation. A high‐resolution X‐ray crystal structure of a stabilized CaMKIIα (6x mutant) hub construct revealed details of the binding mode of PIPA, which involved outward placement of tryptophan 403 (Trp403), a central residue in a flexible loop close to the upper hub cavity. Small‐angle X‐ray scattering (SAXS) solution structures and mass photometry of the CaMKIIα wild‐type hub domain in the presence of PIPA revealed a high degree of ordered self‐association (stacks of CaMKIIα hub domains). This stacking neither occurred with the smaller compound 3‐hydroxycyclopent‐1‐enecarboxylic acid (HOCPCA), nor when Trp403 was replaced with leucine (W403L). Additionally, CaMKIIα W403L hub was stabilized to a larger extent by PIPA compared to CaMKIIα hub wild type, indicating that loop flexibility is important for holoenzyme stability. Thus, we propose that ligand‐induced outward placement of Trp403 by PIPA, which promotes an unforeseen mechanism of hub domain stacking, may be involved in the observed reduction in CaMKIIα kinase activity. Altogether, this sheds new light on allosteric regulation of CaMKIIα activity via the hub domain. [ABSTRACT FROM AUTHOR]

Transient melting of the duplex‐DNA (B‐DNA) during DNA transactions allows repeated sequences to fold into non‐B‐DNA structures, including DNA junctions and G‐quadruplexes. These noncanonical structures can act as impediments to DNA polymerase progression along the duplex, thereby triggering DNA damage and ultimately jeopardizing genomic stability. Their stabilization by ad hoc ligands is currently being explored as a putative anticancer strategy since it might represent an efficient way to inflict toxic DNA damage specifically to rapidly dividing cancer cells. The relevance of this strategy is only emerging for three‐way DNA junctions (TWJs) and, to date, no molecule has been recognized as a reference TWJ ligand, featuring both high affinity and selectivity. Herein, we characterize such reference ligands through a combination of in vitro techniques comprising affinity and selectivity assays (competitive FRET‐melting and TWJ Screen assays), functional tests (qPCR and Taq stop assays) and structural analyses (molecular dynamics and NMR investigations). We identify novel azacryptands TrisNP‐amphi and TrisNP‐ana as the most promising ligands, interacting with TWJs with high affinity and selectivity. These ligands represent new molecular tools to investigate the cellular roles of TWJs and explore how they can be exploited in innovative anticancer therapies. [ABSTRACT FROM AUTHOR]

Six new complexes (1–6), [Ru(η6‐p‐cymene)(FA)Cl] (1), [Ru(η6‐p‐cymene)(PA)Cl] (2), [Ru(η6‐p‐cymene)(SA)Cl] (3), [Ru(η6‐p‐cymene)(FA)PPh3]Cl (4), [Ru(η6‐p‐cymene)(PA)PPh3]Cl (5), [Ru(η6‐p‐cymene)(SA)PPh3]Cl(6), [HFA = ferulic acid, HPA = p‐coumaric acid, HSA = sinapinic acid], were synthesized and well characterized by various spectroscopic, analytical techniques and computational studies. Amongst these six complexes, complexes 4, 5, and 6 were found to be selectively cytotoxic toward melanoma (A375) cell lines and were non‐cytotoxic toward non‐cancerous cell lines (HEK 293 T). Further investigation on the probable bio‐molecular interaction mechanisms revealed that all the complexes show strong groove binding interactions with the DNA, however, complexes 3, 4 and 3, 6 show strong interaction with BSA and HSA, respectively. Through Hoechst staining it can be elucidated that complexes 4–6 cause characteristic apoptotic nuclear changes in the cells indicating apoptosis as the cell death mechanism caused by complexes 4–6. To further confirm the cell death mechanism, protein expression analysis was done through western blotting, which showed a decrease in anti‐apoptotic protein (Bcl‐xL) expression and increased pro‐apoptotic protein (PARP) expression, which confirms the cell death by apoptosis. Using DCFDA staining, we observed that complexes 4, 5, and 6 produced more ROS in the cells, which also might be the cause of cell death by the complexes. Along with that the complexes show enhanced anti‐migratory abilities depicted through wound healing assay. [ABSTRACT FROM AUTHOR]