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Using a convergent synthetic route to enable multiple points of diversity, a series of glucocorticoid receptor modulators (GRM) were profiled for potency, selectivity, and drug-like properties

Abyssomicin C and its atropisomer are potent inhibitors of bacterial folate metabolism. They possess complex polycyclic structures, and their biosynthesis has been shown to involve several unusual enzymatic transformations. Using a combination of synthesis and in vitro assays we reveal that AbyV, a cytochrome P450 enzyme from the aby gene cluster, catalyses a key late-stage epoxidation required for the installation of the characteristic ether-bridged-core of abyssomicin C. The X-ray crystal structure of AbyV has been determined, which in combination with molecular dynamics simulations provides a structural framework for our functional data. This work demonstrates the power of combining selective carbon-13 labelling with NMR spectroscopy as a sensitive tool to interrogate enzyme-catalysed reactions in vitro with no need for purification.

The global impact of synthetic biology has been accelerating, because of the plummeting cost of DNA synthesis, advances in genetic engineering, growing understanding of genome organization, and explosion in data science. However, much of the discipline's application in the pharmaceutical industry remains enigmatic. In this review, we highlight recent examples of the impact of synthetic biology on target validation, assay development, hit finding, lead optimization, and chemical synthesis, through to the development of cellular therapeutics. We also highlight the availability of tools and technologies driving the discipline. Synthetic biology is certainly impacting all stages of drug discovery and development, and the recognition of the discipline's contribution can further enhance the opportunities for the drug discovery and development value chain.

Monoacylated diamines are common motifs present in pharmaceuticals, agrochemicals, and natural products. However, the synthesis of these compounds often requires selective protection/deprotection s...

Glucocorticoid receptor modulators (GRM) are the first-line treatment for many immune diseases, but unwanted side effects restrict chronic dosing. However, targeted delivery of a GRM payload via an immunology antibody-drug conjugate (iADC) may deliver significant efficacy at doses that do not lead to unwanted side effects. We initiated our α-TNF-GRM ADC project focusing on identifying the optimal payload and a linker that afforded stable attachment to both the payload and antibody, resulting in the identification of the synthetically accessible maleimide-Gly-Ala-Ala linker. DAR 4 purified ADCs were shown to be more efficacious in a mouse contact hypersensitivity model than the parent α-TNF antibody. Analysis of P1NP and corticosterone biomarkers showed there was a sufficient therapeutic window between efficacy and unwanted effects. In a chronic mouse arthritis model, α-TNF-GRM ADCs were more efficacious than both the parent α-TNF mAb and an isotype control bearing the same GRM payload.

Cyclopropanes are commonly employed structural moieties in drug design since their incorporation is often associated with increased target affinity, improved metabolic stability, and increased rigidity to access bioactive conformations. Robust chemical cyclopropanation procedures have been developed which proceed with high yield and broad substrate scope, and have been applied to labeled substrates. Recently, engineered enzymes have been shown to perform cyclopropanations with remarkable diastereoselectivity and enantioselectivity, but this biocatalytic approach has not been applied to labeled substrates to date. In this study, the use of enzyme catalysis for the synthesis of labeled cyclopropanes was investigated. Two readily available enzymes, a modified CYP450 enzyme and a modified Aeropyrum pernix protoglobin, were investigated for the cyclopropanation of a variety of substituted styrenes. For this biocatalytic transformation, the enzymes required the use of ethyl diazoacetate. Due to the highly energetic nature of this molecule, alternatives were investigated. The final optimized cyclopropanation was successfully demonstrated using n-hexyl diazoacetate, resulting in moderate to high enantiomeric excess. The optimized procedure was used to generate labeled cyclopropanes from

The late-stage functionalization (LSF) of peptides represents a valuable strategy for the design of potent peptide pharmaceuticals by enabling rapid exploration of chemical diversity and offering novel opportunities for peptide conjugation. While the C(sp2 )-H activation of tryptophan (Trp) is well documented, the resurgence of radical chemistry is opening new avenues for the C-H functionalization of other aromatic side-chains. Herein, we report the first example of LSF at C2 of histidine (His) utilizing a broad scope of aliphatic sulfinate salts as radical precursors. In this work, the exquisite selectivity for histidine functionalization was demonstrated through the alkylation of complex unprotected peptides in aqueous media. Finally, this methodology was extended for the installation of a ketone handle, providing an unprecedented anchor for selective oxime/hydrazone conjugation at histidine.

AZD1979 [(3-(4-(2-oxa-6-azaspiro[3.3]heptan-6-ylmethyl)phenoxy)azetidin-1-yl)(5-(4-methoxyphenyl)-1,3,4-oxadiazol-2-yl)methanone] is a melanin-concentrating hormone receptor 1 antagonist designed for the treatment of obesity. In this study, metabolite profiles of AZD1979 in human hepatocytes revealed a series of glutathione-related metabolites, including the glutathionyl, cysteinyl, cysteinylglycinyl, and mercapturic acid conjugates. The formation of these metabolites was not inhibited by coincubation with the cytochrome P450 (P450) inhibitor 1-aminobenzotriazole. In efforts to identify the mechanistic features of this pathway, investigations were performed to characterize the structure of the glutathionyl conjugate M12 of AZD1979 and to identify the enzyme system catalyzing its formation. Studies with various human liver subcellular fractions established that the formation of M12 was NAD(P)H-independent and proceeded in cytosol and S9 fractions but not in microsomal or mitochondrial fractions. The formation of M12 was inhibited by ethacrynic acid, an inhibitor of glutathione S-transferases (GSTs). Several human recombinant GSTs, including GSTA1, A2-2, M1a, M2-2, T1-1, and GST from human placenta, were incubated with AZD1979. All GSTs tested catalyzed the formation of M12, with GSTA2-2 being the most efficient. Metabolite M12 was purified from rat liver S9 incubations and its structure elucidated by NMR. These results establish that M12 is the product of the GST-catalyzed glutathione attack on the carbon atom α to the nitrogen atom of the strained spiro-azetidinyl moiety to give, after ring opening, the corresponding amino-thioether conjugate product, a direct conjugation pathway that occurs without the prior substrate bioactivation by P450. SIGNIFICANCE STATEMENT: The investigated compound, AZD1979, contains a 6-substituted-2-oxa-6-azaspiro[3.3]heptanyl derivative that is an example of strained heterocycles, including spiro-fused ring systems, that are widely used in synthetic organic chemistry. An unusual azetidinyl ring-opening reaction involving a nucleophilic attack by glutathione, which does not involve prior cytochrome P450-catalyzed bioactivation of the substrate and which is catalyzed by glutathione transferases, is reported. We propose a mechanism involving the protonated cyclic aminyl intermediate that undergoes nucleophilic attack by glutathione thiolate anion in this reaction, catalyzed by glutathione transferases.

5-Lipoxygenase activating protein (FLAP) inhibitors attenuate 5-lipoxygenase pathway activity and reduce the production of proinflammatory and vasoactive leukotrienes. As such, they are hypothesized to have therapeutic benefit for the treatment of diseases that involve chronic inflammation including coronary artery disease. Herein, we disclose the medicinal chemistry discovery and the early clinical development of the FLAP inhibitor AZD5718 (12). Multiparameter optimization included securing adequate potency in human whole blood, navigation away from Ames mutagenic amine fragments while balancing metabolic stability and PK properties allowing for clinically relevant exposures after oral dosing. The superior safety profile of AZD5718 compared to earlier frontrunner compounds allowed us to perform a phase 1 clinical study in which AZD5718 demonstrated a dose dependent and greater than 90% suppression of leukotriene production over 24 h. Currently, AZD5718 is evaluated in a phase 2a study for treatment of coronary artery disease.

The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.

This paper presents a face mask detection system that can be easily retrofitted to a standalone Access and Egress control system and can be deployed using any Edge processing subsystem. In this work, the widely available Raspberry Pi is used incorporating novel TensorFlow lite based training methods to demonstrate the utility of the approach. This subsystem achieves real-time face mask detection with high accuracy of over 89% in face mask detection at a confidence level of greater than 90% with excellent detection speeds of less than 3ms. The performance of the Raspberry Pi based implementation compares very favorably with GPU desktop-based alternative approaches that require excellent real time cloud enabled communications. The system is shown to work robustly with minimal human intervention and can be easily deployed at entrance points to lab or other employee facilities where face masks are mandatory for employee safety. The proposed algorithm consists of a single stage object detector together with an adaptive training dataset. This dataset comprises a hybrid combination of locally collected training data together with publicly available datasets and it is shown to be most appropriate for the face mask detection use case at hand.