Light-gated Integrator for Highlighting Kinase Activity in Living Cells.

Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into "permanent" fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GαsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.

PECAN Predicts Patterns of Cancer Cell Cytostatic Activity of Natural Products Using Deep Learning.

Many machine learning techniques are used as drug discovery tools with the intent to speed characterization by determining relationships between compound structure and biological function. However, particularly in anticancer drug discovery, these models often make only binary decisions about the biological activity for a narrow scope of drug targets. We present a feed-forward neural network, PECAN (Prediction Engine for the Cytostatic Activity of Natural product-like compounds), that simultaneously classifies the potential antiproliferative activity of compounds against 59 cancer cell lines. It predicts the activity to be one of six categories, indicating not only if activity is present but the degree of activity. Using an independent subset of NCI data as a test set, we show that PECAN can reach 60.1% accuracy in a six-way classification and present further evidence that it classifies based on useful structural features of compounds using a "within-one" measure that reaches 93.0% accuracy.

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Structure and Biosynthesis of Hectoramide B, a Linear Depsipeptide from Marine Cyanobacterium Moorena producens JHB Discovered via Coculture with Candida albicans.

The tropical marine cyanobacterium Moorena producens JHB is a prolific source of secondary metabolites with potential biomedical utility. Previous studies on this strain led to the discovery of several novel compounds such as hectochlorins and jamaicamides. However, bioinformatic analyses of its genome indicate the presence of numerous cryptic biosynthetic gene clusters that have yet to be characterized. To potentially stimulate the production of novel compounds from this strain, it was cocultured with Candida albicans. From this experiment, we observed the increased production of a new compound that we characterize here as hectoramide B. Bioinformatic analysis of the M. producens JHB genome enabled the identification of a putative biosynthetic gene cluster responsible for hectoramide B biosynthesis. This work demonstrates that coculture competition experiments can be a valuable method to facilitate the discovery of novel natural products from cyanobacteria.

Orthogonal Deprotection Strategy of Fmoc Provides Improved Synthesis of Sensitive Peptides: Application to Z-Arg-Lys-AOMK.

Protecting groups (PGs) in peptide synthesis have inspired advanced design principles that incorporate "orthogonality" for selective C- and N-terminus and side-chain deprotections. The conventionally acid-stable 9-fluorenylmethoxycarbonyl (Fmoc) group is one of the most widely used N-protection groups in solid- and solution-phase synthesis. Despite the versatility of Fmoc, deprotection by the removal of the Fmoc group to unmask primary amines requires the use of a basic secondary amine nucleophile, but this stratagem poses challenges in sensitive molecules that bear reactive electrophilic groups. An expansion of PG versatility, a tunable orthogonality, in the late-stage synthesis of peptides would add flexibility to the synthetic design and implementation. Here, we report a novel Fmoc deprotection method using hydrogenolysis under mildly acidic conditions for the synthesis of Z-Arg-Lys-acyloxymethyl ketone (Z-R-K-AOMK). This new method is not only valuable for Fmoc deprotection in the synthesis of complex peptides that contain highly reactive electrophiles, or other similar sensitive functional groups, that are incompatible with traditional Fmoc deprotection conditions but also tolerant of N-Boc groups present in the substrate.

Lake Avernus Has Turned Red: Bioindicator Monitoring Unveils the Secrets of "Gates of Hades".

Lake Avernus is a volcanic lake located in southern Italy. Since ancient times, it has inspired numerous myths and legends due to the occurrence of singular phenomena, such as coloring events. Only recently has an explanation been found for them, i.e., the recurring color change over time is due to the alternation of cyanobacterial blooms that are a consequence of natural nutrient inputs as well as pollution resulting from human activities. This current report specifically describes the red coloring event that occurred on Lake Avernus in March 2022, the springtime season in this region of Italy. Our innovative multidisciplinary approach, the 'Fast Detection Strategy' (FDS), was devised to monitor cyanobacterial blooms and their toxins. It integrates remote sensing data from satellites and drones, on-site sampling, and analytical/bioinformatics analyses into a cohesive information flow. Thanks to FDS, we determined that the red color was attributable to a bloom of Planktothrix rubescens, a toxin-producing cyanobacterium. Here, we report the detection and identification of 14 anabenopeptins from this P. rubescens strain, seven of which are known and seven are newly reported herein. Moreover, we explored the mechanisms and causes behind this cyclic phenomenon, confirming cyanobacteria's role as reliable indicators of environmental changes. This investigation further validates FDS's effectiveness in detecting and characterizing cyanobacterial blooms and their associated toxins, expanding its potential applications.

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Covalent Macrocyclic Proteasome Inhibitors Mitigate Resistance in Plasmodium falciparum.

The Plasmodium proteasome is a promising antimalarial drug target due to its essential role in all parasite lifecycle stages. Furthermore, proteasome inhibitors have synergistic effects when combined with current first-line artemisinin and related analogues. Linear peptides that covalently inhibit the proteasome are effective at killing parasites and have a low propensity for inducing resistance. However, these scaffolds generally suffer from poor pharmacokinetics and bioavailability. Here we describe the development of covalent, irreversible, macrocyclic inhibitors of the Plasmodium falciparum proteasome. We identified compounds with excellent potency and low cytotoxicity; however, the first generation suffered from poor microsomal stability. Further optimization of an existing macrocyclic scaffold resulted in an irreversible covalent inhibitor carrying a vinyl sulfone electrophile that retained high potency and low cytotoxicity and had acceptable metabolic stability. Importantly, unlike the parent reversible inhibitor that selected for multiple mutations in the proteasome, with one resulting in a 5,000-fold loss of potency, the irreversible analogue only showed a 5-fold loss in potency for any single point mutation. Furthermore, an epoxyketone analogue of the same scaffold retained potency against a panel of known proteasome mutants. These results confirm that macrocycles are optimal scaffolds to target the malarial proteasome and that the use of a covalent electrophile can greatly reduce the ability of the parasite to generate drug resistance mutations.

Artificial intelligence for natural product drug discovery.

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.

Evaluation of bumetanide as a potential therapeutic agent for Alzheimer's disease.

Therapeutics discovery and development for Alzheimer's disease (AD) has been an area of intense research to alleviate memory loss and the underlying pathogenic processes. Recent drug discovery approaches have utilized in silico computational strategies for drug candidate selection which has opened the door to repurposing drugs for AD. Computational analysis of gene expression signatures of patients stratified by the APOE4 risk allele of AD led to the discovery of the FDA-approved drug bumetanide as a top candidate agent that reverses APOE4 transcriptomic brain signatures and improves memory deficits in APOE4 animal models of AD. Bumetanide is a loop diuretic which inhibits the kidney Na+-K+-2Cl- cotransporter isoform, NKCC2, for the treatment of hypertension and edema in cardiovascular, liver, and renal disease. Electronic health record data revealed that patients exposed to bumetanide have lower incidences of AD by 35%-70%. In the brain, bumetanide has been proposed to antagonize the NKCC1 isoform which mediates cellular uptake of chloride ions. Blocking neuronal NKCC1 leads to a decrease in intracellular chloride and thus promotes GABAergic receptor mediated hyperpolarization, which may ameliorate disease conditions associated with GABAergic-mediated depolarization. NKCC1 is expressed in neurons and in all brain cells including glia (oligodendrocytes, microglia, and astrocytes) and the vasculature. In consideration of bumetanide as a repurposed drug for AD, this review evaluates its pharmaceutical properties with respect to its estimated brain levels across doses that can improve neurologic disease deficits of animal models to distinguish between NKCC1 and non-NKCC1 mechanisms. The available data indicate that bumetanide efficacy may occur at brain drug levels that are below those required for inhibition of the NKCC1 transporter which implicates non-NKCC1 brain mechansims for improvement of brain dysfunctions and memory deficits. Alternatively, peripheral bumetanide mechanisms may involve cells outside the central nervous system (e.g., in epithelia and the immune system). Clinical bumetanide doses for improved neurological deficits are reviewed. Regardless of mechanism, the efficacy of bumetanide to improve memory deficits in the APOE4 model of AD and its potential to reduce the incidence of AD provide support for clinical investigation of bumetanide as a repurposed AD therapeutic agent.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data.

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Enzymatic Halogenation of Terminal Alkynes.

The biosynthetic installation of halogen atoms is largely performed by oxidative halogenases that target a wide array of electron-rich substrates, including aromatic compounds and conjugated systems. Halogenated alkyne-containing molecules are known to occur in Nature; however, halogen atom installation on the terminus of an alkyne has not been demonstrated in enzyme catalysis. Herein, we report the discovery and characterization of an alkynyl halogenase in natural product biosynthesis. We show that the flavin-dependent halogenase from the jamaicamide biosynthetic pathway, JamD, is not only capable of terminal alkyne halogenation on a late-stage intermediate en route to the final natural product but also has broad substrate tolerance for simple to complex alkynes. Furthermore, JamD is specific for terminal alkynes over other electron-rich aromatic substrates and belongs to a newly identified family of halogenases from marine cyanobacteria, indicating its potential as a chemoselective biocatalyst for the formation of haloalkynes.

Structural elucidation of recombinant Trichomonas vaginalis 20S proteasome bound to covalent inhibitors.

Proteasomes are essential for protein homeostasis in mammalian cells1-4 and in protozoan parasites such as Trichomonas vaginalis (Tv).5 Tv and other protozoan 20S proteasomes have been validated as druggable targets.6-8 However, in the case of Tv 20S proteasome (Tv20S), biochemical and structural studies were impeded by low yields and purity of the native proteasome. We successfully made recombinant Tv20S by expressing all seven α and seven ß subunits together with the Ump-1 chaperone in insect cells. We isolated recombinant proteasome and showed that it was biochemically indistinguishable from the native enzyme. We confirmed that the recombinant Tv20S is inhibited by the natural product marizomib (MZB)9 and the recently developed peptide inhibitor carmaphycin-17 (CP-17)8,10. Specifically, MZB binds to the ß1, ß2 and ß5 subunits, while CP-17 binds the ß2 and ß5 subunits. Next, we obtained cryo-EM structures of Tv20S in complex with these covalent inhibitors at 2.8Å resolution. The structures revealed the overall fold of the Tv20S and the binding mode of MZB and CP-17. Our work explains the low specificity of MZB and higher specificity of CP-17 towards Tv20S as compared to human proteasome and provides the platform for the development of Tv20S inhibitors for treatment of trichomoniasis.

DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.

The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra. However, the number of reference NMR spectra available is limited and has mostly facilitated annotation of commercially available derivatives. Here, we introduce DeepSAT, a neural network-based structure annotation and scaffold prediction system that directly extracts the chemical features associated with molecular structures from their NMR spectra. Using only the 1H-13C HSQC spectrum, DeepSAT identifies related known compounds and thus efficiently assists in the identification of molecular structures. DeepSAT is expected to accelerate chemical and biomedical research by accelerating the identification of molecular structures.

Structure and Biosynthesis of Hectoramide B, a Linear Depsipeptide from the Marine Cyanobacterium Moorena producens JHB Discovered via Co-culture with Candida albicans.

The tropical marine cyanobacterium Moorena producens JHB is a prolific source of secondary metabolites with potential biomedical utility. Previous studies of this strain led to the discovery of several novel compounds such as the hectochlorins and jamaicamides; however, bioinformatic analyses of its genome suggested that there were many more cryptic biosynthetic gene clusters yet to be characterized. To potentially stimulate the production of novel compounds from this strain, it was co-cultured with Candida albicans. From this experiment, we observed the increased production of a new compound that we characterize here as hectoramide B. Bioinformatic analysis of the M. producens JHB genome enabled the identification of a putative biosynthetic gene cluster responsible for hectoramide B biosynthesis. This work demonstrates that co-culture competition experiments can be a valuable method to facilitate the discovery of novel natural products from cyanobacteria.

Development of subunit selective substrates for Trichomonas vaginalis proteasome.

The protozoan parasite, Trichomonas vaginalis (Tv) causes trichomoniasis, the most common, non-viral, sexually transmitted infection in the world. Only two closely related drugs are approved for its treatment. The accelerating emergence of resistance to these drugs and lack of alternative treatment options poses an increasing threat to public health. There is an urgent need for novel effective anti-parasitic compounds. The proteasome is a critical enzyme for T. vaginalis survival and was validated as a drug target to treat trichomoniasis. However, to develop potent inhibitors of the T. vaginalis proteasome, it is essential that we understand which subunits should be targeted. Previously, we identified two fluorogenic substrates that were cleaved by T. vaginalis proteasome, however after isolating the enzyme complex and performing an in-depth substrate specificity study, we have now designed three fluorogenic reporter substrates that are each specific for one catalytic subunit. We screened a library of peptide epoxyketone inhibitors against the live parasite and evaluated which subunits are targeted by the top hits. Together we show that targeting of the ß5 subunit of T. vaginalis is sufficient to kill the parasite, however, targeting of ß5 plus either ß1 or ß2 results in improved potency.

Mitigating the risk of antimalarial resistance via covalent dual-subunit inhibition of the Plasmodium proteasome.

The Plasmodium falciparum proteasome constitutes a promising antimalarial target, with multiple chemotypes potently and selectively inhibiting parasite proliferation and synergizing with the first-line artemisinin drugs, including against artemisinin-resistant parasites. We compared resistance profiles of vinyl sulfone, epoxyketone, macrocyclic peptide, and asparagine ethylenediamine inhibitors and report that the vinyl sulfones were potent even against mutant parasites resistant to other proteasome inhibitors and did not readily select for resistance, particularly WLL that displays covalent and irreversible binding to the catalytic ß2 and ß5 proteasome subunits. We also observed instances of collateral hypersensitivity, whereby resistance to one inhibitor could sensitize parasites to distinct chemotypes. Proteasome selectivity was confirmed using CRISPR/Cas9-edited mutant and conditional knockdown parasites. Molecular modeling of proteasome mutations suggested spatial contraction of the ß5 P1 binding pocket, compromising compound binding. Dual targeting of P. falciparum proteasome subunits using covalent inhibitors provides a potential strategy for restoring artemisinin activity and combating the spread of drug-resistant malaria.

Kalkitoxin: A Potent Suppressor of Distant Breast Cancer Metastasis.

Bone metastasis resulting from advanced breast cancer causes osteolysis and increases mortality in patients. Kalkitoxin (KT), a lipopeptide toxin derived from the marine cyanobacterium Moorena producens (previously Lyngbya majuscula), has an anti-metastatic effect on cancer cells. We verified that KT suppressed cancer cell migration and invasion in vitro and in animal models in the present study. We confirmed that KT suppressed osteoclast-soup-derived MDA-MB-231 cell invasion in vitro and induced osteolysis in a mouse model, possibly enhancing/inhibiting metastasis markers. Furthermore, KT inhibits CXCL5 and CXCR2 expression, suppressing the secondary growth of breast cancer cells on the bone, brain, and lungs. The breast-cancer-induced osteolysis in the mouse model further reveals that KT plays a protective role, judging by micro-computed tomography and immunohistochemistry. We report for the first time the novel suppressive effects of KT on cancer cell migration and invasion in vitro and on MDA-MB-231-induced bone loss in vivo. These results suggest that KT may be a potential therapeutic drug for the treatment of breast cancer metastasis.

Development of Potent and Highly Selective Epoxyketone-Based Plasmodium Proteasome Inhibitors.

Here, we present remarkable epoxyketone-based proteasome inhibitors with low nanomolar in vitro potency for blood-stage Plasmodium falciparum and low cytotoxicity for human cells. Our best compound has more than 2,000-fold greater selectivity for erythrocytic-stage P. falciparum over HepG2 and H460 cells, which is largely driven by the accommodation of the parasite proteasome for a D-amino acid in the P3 position and the preference for a difluorobenzyl group in the P1 position. We isolated the proteasome from P. falciparum cell extracts and determined that the best compound is 171-fold more potent at inhibiting the ß5 subunit of P. falciparum proteasome when compared to the same subunit of the human constitutive proteasome. These compounds also significantly reduce parasitemia in a P. berghei mouse infection model and prolong survival of animals by an average of 6 days. The current epoxyketone inhibitors are ideal starting compounds for orally bioavailable anti-malarial drugs.