A novel antibiotic class targeting the lipopolysaccharide transporter.

Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a major global pathogen with limited treatment options1. No new antibiotic chemical class with activity against A. baumannii has reached patients in over 50 years1. Here we report the identification and optimization of tethered macrocyclic peptide (MCP) antibiotics with potent antibacterial activity against CRAB. The mechanism of action of this molecule class involves blocking the transport of bacterial lipopolysaccharide from the inner membrane to its destination on the outer membrane, through inhibition of the LptB2FGC complex. A clinical candidate derived from the MCP class, zosurabalpin (RG6006), effectively treats highly drug-resistant contemporary isolates of CRAB both in vitro and in mouse models of infection, overcoming existing antibiotic resistance mechanisms. This chemical class represents a promising treatment paradigm for patients with invasive infections due to CRAB, for whom current treatment options are inadequate, and additionally identifies LptB2FGC as a tractable target for antimicrobial drug development.

Machine Learning C-N Couplings: Obstacles for a General-Purpose Reaction Yield Prediction.

Pd-catalyzed C-N couplings are commonplace in academia and industry. Despite their significance, finding suitable reaction conditions leading to a high yield, for instance, remains a challenging and time-consuming task which usually requires screening over many sets of conditions. To help select promising reaction conditions in the vast space of reagent combinations, machine learning is an emerging technique with a lot of promise. In this work, we assess whether the reaction yield of C-N couplings can be predicted from databases of chemical reactions. We test the generalizability of models both on challenging data splits and on a dedicated experimental test set. We find that, provided the chemical space represented by the training set is not left, the models perform well. However, the applicability domain is quickly left even for simple reactions of the same type, as, for instance, present in our plate test set. The results show that yield prediction for new reactions is possible from the algorithmic side but in practice is hindered by the available data. Most importantly, more data that cover the diversity in reagents are needed for a general-purpose prediction of reaction yields. Our findings also expose a challenge to this field in that it appears to be extremely deceiving to judge models based on literature data with test sets which are split off the same literature data, even when challenging splits are considered.

What can reaction databases teach us about Buchwald-Hartwig cross-couplings?

Despite the widespread and increasing usage of Pd-catalyzed C-N cross couplings, finding good conditions for these reactions can be challenging. Practitioners mostly rely on few methodology studies or anecdotal experience. This is surprising, since the advent of data-driven experimentation and the large amount of knowledge in databases allow for data-driven insight. In this work, we address this by analyzing more than 62 000 Buchwald-Hartwig couplings gathered from CAS, Reaxys and the USPTO. Our meta-analysis of the reaction performance generates data-driven cheatsheets for reaction condition recommendation. It also provides an interactive tool to find rarer ligands with optimal performance regarding user-selected substrate properties. With this we give practitioners promising starting points. Furthermore, we study bias and diversity in the literature and summarize the current state of the reaction data, including its pitfalls. Hence, this work will also be useful for future data-driven developments such as the optimization of reaction conditions via machine learning.

Therapy with a Selective Cannabinoid Receptor Type 2 Agonist Limits Albuminuria and Renal Injury in Mice with Type 2 Diabetic Nephropathy.

BACKGROUND/AIMS: A critical involvement of the endocannabinoid/cannabinoid receptor system in diabetes and its complications has been recognized. Experimental evidence suggested that activation of the cannabinoid receptor type 2 (CB2), which is expressed in the kidney by podocytes and inflammatory cells, had a protective role in early streptozotocin-induced type 1 diabetes in mice. No experimental evidence is so far available on the effects of CB2 agonists in type 2 diabetes. In this study, we investigated the effects of a CB2 agonist given at a phase of overt disease on renal functional and structural changes in BTBR ob/ob mice, a model of type 2 diabetic nephropathy. METHODS: BTBR ob/ob mice received, from 10 to 21 weeks of age, vehicle, the selective CB2 agonist HU910, or lisinopril used as standard therapy for comparison. BTBR wild-type mice served as controls. RESULTS: Treatment with CB2 agonist reduced progressive albuminuria of BTBR ob/ob mice to a similar extent as ACE inhibitor. The antiproteinuric effect of CB2 agonist was associated with the amelioration of the defective nephrin expression in podocytes of diabetic mice. CB2 agonist limited mesangial matrix expansion, fibronectin accumulation and sclerosis. Glomerular infiltration of Mac-2-positive monocytes/machrophages was attenuated by CB2 agonist, at least in part due to the drug's ability to reduce MCP-1 chemotactic signals. Renoprotective effects of CB2 were similar to those achieved by ACE inhibitor. CONCLUSION: These results suggest that CB2 agonism is a potential option to be added to the available therapeutic armamentarium for type 2 diabetic nephropathy.

A Robust, Recyclable Resin for Decagram Scale Resolution of (±)-Mefloquine and Other Chiral N-Heterocycles.

Decagram quantities of enantiopure (+)-mefloquine have been produced via kinetic resolution of racemic mefloquine using a ROMP-gel supported chiral acyl hydroxamic acid resolving agent. The requisite monomer was prepared in a few synthetic steps without chromatography and polymerization was safely performed on a >30 gram scale under ambient conditions. The reagent was readily regenerated and reused multiple times for the resolution of 150 grams of (±)-mefloquine and other chiral N-heterocylces.

Novel Triazolopyrimidine-Derived Cannabinoid Receptor 2 Agonists as Potential Treatment for Inflammatory Kidney Diseases.

The cannabinoid receptor 2 (CB2) system is described to modulate various pathological conditions, including inflammation and fibrosis. A series of new heterocyclic small-molecule CB2 receptor agonists were identified from a high-throughput screen. Lead optimization gave access to novel, highly potent, and selective (over CB1) triazolopyrimidine derivatives. A preliminary structure-activity relationship was established, and physicochemical properties in this compound class were significantly improved toward better solubility, lipophilicity, and microsomal stability. An optimized triazolopyrimidine derivative, (3S)-1-[5-tert-butyl-3-[(1-cyclopropyltetrazol-5-yl)methyl]triazolo[4,5-d]pyrimidin-7-yl]pyrrolidin-3-ol (39), was tested in a kidney ischemia-reperfusion model, in which it showed efficacy at a dose of 10 mg kg(-1) (p.o.). A significant depletion of the three measured kidney markers indicated a protective role of CB2 receptor activation toward inflammatory kidney damage. Compound 39 was also protective in a model of renal fibrosis. Oral treatment with 39 at 3 mg kg(-1) per day significantly decreased the amount of fibrosis by ∼ 40% which was induced by unilateral ureter obstruction.