No abstract

Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools. We supplemented this with random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable putative BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a major addition to in-silico BGC identification.

Escherichia coli is a common inhabitant of the human microbiota and a beacon model organism in biology. However, an understanding of its signaling systems that regulate population-level phenotypes known as quorum sensing remain incomplete. Here, we define the structure and biosynthesis of autoinducer-3 (AI-3), a metabolite of previously unknown structure involved in the pathogenesis of enterohemorrhagic E. coli (EHEC). We demonstrate that novel AI-3 analogs are derived from threonine dehydrogenase (Tdh) products and “abortive” tRNA synthetase reactions, and they are distributed across a variety of Gram-negative and Gram-positive bacterial pathogens. In addition to regulating virulence genes in EHEC, we show that the metabolites exert diverse immunological effects on primary human tissues. The discovery of AI-3 metabolites and their biochemical origins now provides a molecular foundation for investigating the diverse biological roles of these elusive yet widely distributed bacterial signaling molecules.

Organic chemistry Z 0200 gem-Disubstituent Effect: Theoretical Basis and Synthetic Applications -[about 120 refs.]. -(JUNG, M. E.; PIIZZI, G.; Chem. Rev. (Washington, D. C.) 105 (2005) 5, 1735-1766; Dep. Chem. Biochem., Univ. Calif., Los Angeles, CA 90095, USA; Eng.) -Lindner 36-231

Cell-cell interactions drive essential biological processes critical to cell and tissue development, function, pathology, and disease outcome. The growing appreciation of immune cell interactions within disease environments has led to significant efforts to develop protein-and cell-based therapeutic strategies. A better understanding of these cell-cell interactions will enable the development of effective immunotherapies. However, characterizing these complex cellular interactions at molecular resolution in their native biological contexts remains challenging. To address this, we introduce photocatalytic cell tagging (PhoTag), a modality agnostic platform for profiling cell-cell interactions. Using photoactivatable flavin-based cofactors, we generate phenoxy radical tags for targeted labeling at the cell surface. Through various targeting modalities (e.g. MHC-Multimer, antibody, single domain antibody (VHH)) we deliver a flavin photocatalyst for cell tagging within monoculture, co-culture, and peripheral blood mononuclear cells. PhoTag enables highly selective tagging of the immune synapse between an immune cell and an antigen-presenting cell through targeted labeling at the cell-cell junction. This allowed for the ability to profile gene expression-level differences between interacting and bystander cell populations. Given the modality agnostic and spatio-temporal nature of PhoTag, we envision its broad utilization to detect and profile intercellular interactions within an immune synapse and other confined cellular regions for any biological system..

Antitumor agents (−)‐acylfulvene and (−)‐irofulven are prepared in an approach that employs the powerful enyne ring‐closing metathesis reaction to secure the spiro‐bicyclic AB rings. Other key features of this synthesis include an efficient aldol‐based introduction of the stereocenter at C2, a diazene‐mediated reductive allylic transposition, and a ring‐closing metathesis/oxidation sequence.

Over the past several decades, the frequency of antibacterial resistance in hospitals, including multidrug resistance (MDR) and its association with serious infectious diseases, has increased at alarming rates. Pseudomonas aeruginosa is a leading cause of nosocomial infections, and resistance to virtually all approved antibacterial agents is emerging in this pathogen. To address the need for new agents to treat MDR P. aeruginosa, we focused on inhibiting the first committed step in the biosynthesis of lipid A, the deacetylation of uridyldiphospho-3-O-(R-hydroxydecanoyl)-N-acetylglucosamine by the enzyme LpxC. We approached this through the design, synthesis, and biological evaluation of novel hydroxamic acid LpxC inhibitors, exemplified by 1, where cytotoxicity against mammalian cell lines was reduced, solubility and plasma-protein binding were improved while retaining potent anti-pseudomonal activity in vitro and in vivo.

Recent clinical evaluation of everolimus for seizure reduction in patients with tuberous sclerosis complex (TSC), a disease with overactivated mechanistic target of rapamycin (mTOR) signaling, has demonstrated the therapeutic value of mTOR inhibitors for central nervous system (CNS) indications. Given that everolimus is an incomplete inhibitor of the mTOR function, we sought to develop a new mTOR inhibitor that has improved properties and is suitable for CNS disorders. Starting from an in-house purine-based compound, optimization of the physicochemical properties of a thiazolopyrimidine series led to the discovery of the small molecule 7, a potent and selective brain-penetrant ATP-competitive mTOR inhibitor. In neuronal cell-based models of mTOR hyperactivity, 7 corrected the mTOR pathway activity and the resulting neuronal overgrowth phenotype. The new mTOR inhibitor 7 showed good brain exposure and significantly improved the survival rate of mice with neuronal-specific ablation of the Tsc1 gene. These results demonstrate the potential utility of this tool compound to test therapeutic hypotheses that depend on mTOR hyperactivity in the CNS.