Novel diaryl ureas with efficacy in a mouse model of malaria

1-[2-(1H-Pyrrole-2-carbonyl)phenyl]-3-(4-methoxyphenyl)urea

For the synthesis of 1-(2-(1H-pyrrole-2-carbonyl)phenyl)-3-(4-methoxyphenyl)urea, the final product, two different methods were used, in one or two steps, from (2-aminophenyl)(1H-pyrrol-2-yl)methanone. The one-step synthesis entailed a carbonylation reaction with 1/3 equivalent of triphosgene in the presence of two equivalents of trimethylamine, followed by the addition of 4-methoxyaniline to the in situ generated aryl isocyanate. The two-step synthesis required first the preparation of phenyl(2-(1H-pyrrole-2-carbonyl)phenyl)carbamate and then a substitution reaction by 4-methoxyaniline. The first method produced the final product in 72% yield, which was the best yield. The structure of the final product was confirmed by FTIR, UV-VIS, 1H and 13C NMR spectroscopy and high resolution mass spectrometry.

Diaryl Ureas as an Antiprotozoal Chemotype

We now describe the physicochemical profiling, in vitro ADME, and antiparasitic activity of eight N,N'-diarylureas to assess their potential as a broad-spectrum antiprotozoal chemotype. Chromatographic LogD_7.4 values ranged from 2.5 to 4.5; kinetic aq. solubilities were ≤6.3 μg/mL, and plasma protein binding ranged from 95 to 99%. All of the compounds had low intrinsic clearance values in human, but not mouse, liver microsomes. Although no N,N'-diarylurea had submicromolar potency against Trypanosoma cruzi, two had submicromolar potencies against Toxoplasma gondii and Trypanosoma brucei rhodesiense, and five had submicromolar potencies against Leishmania donovani. Plasmodium falciparum appeared to be the most susceptible to growth inhibition by this compound series. Most of the N,N'-diarylureas had antiprotozoal selectivities ≥10. One N,N'-diarylurea had demonstrable activity in mouse models of malaria and toxoplasmosis.

Diarylureas: Repositioning from Antitumor to Antimicrobials or Multi-Target Agents against New Pandemics

Antimicrobials have allowed medical advancements over several decades. However, the continuous emergence of antimicrobial resistance restricts efficacy in treating infectious diseases. In this context, the drug repositioning of already known biological active compounds to antimicrobials could represent a useful strategy. In 2002 and 2003, the SARS-CoV pandemic immobilized the Far East regions. However, the drug discovery attempts to study the virus have stopped after the crisis declined. Today’s COVID-19 pandemic could probably have been avoided if those efforts against SARS-CoV had continued. Recently, a new coronavirus variant was identified in the UK. Because of this, the search for safe and potent antimicrobials and antivirals is urgent. Apart from antiviral treatment for severe cases of COVID-19, many patients with mild disease without pneumonia or moderate disease with pneumonia have received different classes of antibiotics. Diarylureas are tyrosine kinase inhibitors well known in the art as anticancer agents, which might be useful tools for a reposition as antimicrobials. The first to come onto the market as anticancer was sorafenib, followed by some other active molecules. For this interesting class of organic compounds antimicrobial, antiviral, antithrombotic, antimalarial, and anti-inflammatory properties have been reported in the literature. These numerous properties make these compounds interesting for a new possible pandemic considering that, as well as for other viral infections also for CoVID-19, a multitarget therapeutic strategy could be favorable. This review is meant to be an overview on diarylureas, focusing on their biological activities, not dwelling on the already known antitumor activity. Quite a lot of papers present in the literature underline and highlight the importance of these molecules as versatile scaffolds for the development of new and promising antimicrobials and multitarget agents against new pandemic events.

Synthesis and biological evaluation of a new series of 1-aryl-3-[4-(pyridin-2-ylmethoxy)phenyl]urea derivatives as new anticancer agents

The diaryl ureas are very important fragments in medicinal chemistry. By means of computer-aided design, 1-aryl-3-[4-(pyridin-2-ylmethoxy)phenyl]urea derivatives were designed and synthesized, and evaluated for their antiproliferative activity against A549, HCT-116, PC-3 cancer cell lines, and HL7702 human normal liver cell lines in vitro by using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide colorimetric assay. Most of the target compounds demonstrate significant antiproliferative effects on all the selective cancer cell lines. The calculated IC₅₀ values were reported. The target compound 1-(4-chlorophenyl)-3-{4-{[3-methyl-4-(2,2,2-trifluoroethoxy)pyridin-2-yl]methoxy}phenyl}urea (7u) demonstrated the most potent inhibitory activity (IC₅₀ = 2.39 ± 0.10 μM for A549 and IC₅₀ = 3.90 ± 0.33 μM for HCT-116), comparable to the positive-control sorafenib (IC₅₀ = 2.12 ± 0.18 μM for A549 and IC₅₀ = 2.25 ± 0.71 μM for HCT-116). Conclusively, 1-aryl-3-[4-(pyridin-2-ylmethoxy)phenyl]urea derivatives as the new anticancer agents were discovered, and could be used as the potential BRAF inhibitors for further research.

Design, Synthesis and Biological Evaluation of a New Series of 1-Aryl-3-{4-[(pyridin-2-ylmethyl)thio]phenyl}urea Derivatives as Antiproliferative Agents

To discover new antiproliferative agents with high efficacy and selectivity, a new series of 1-aryl-3-{4-[(pyridin-2-ylmethyl)thio]phenyl}urea derivatives (7a–7t) were designed, synthesized and evaluated for their antiproliferative activity against A549, HCT-116 and PC-3 cancer cell lines in vitro. Most of the target compounds demonstrated significant antiproliferative effects on all the selective cancer cell lines. Among them, the target compound, 1-[4-chloro-3-(trifluoromethyl)phenyl]-3-{4-{{[3-methyl-4-(2,2,2-trifluoroethoxy)pyridin-2-yl]methyl}thio}phenyl}urea (7i) was identified to be the most active one against three cell lines, which was more potent than the positive control with an IC₅₀ value of 1.53 ± 0.46, 1.11 ± 0.34 and 1.98 ± 1.27 μM, respectively. Further cellular mechanism studies confirmed that compound 7i could induce the apoptosis of A549 cells in a concentration-dependent manner and elucidated compound 7i arrests cell cycle at G1 phase by flow cytometry analysis. Herein, the studies suggested that the 1-aryl-3-{4-[(pyridin-2-ylmethyl)thio]phenyl}urea skeleton might be regarded as new chemotypes for designing effective antiproliferative agents.

Collaborative drug discovery and the Tres Cantos Antimalarial Set (TCAMS)

Malaria affects a population of over 200 million people worldwide. New drugs are needed because of widespread resistance, and the hunt for such drugs involves a coordinated research effort from the scientific community. The release of the Tres Cantos Antimalarial Set (TCAMS) in 2010 represented a landmark in the field of collaborative drug discovery for malaria. This set of >13 000 molecules with confirmed activity against several strains of Plasmodium falciparum was publicly released with the goal of fostering additional research beyond the GlaxoSmithKline (GSK) network of collaborators. Here, we examine the outcomes realized from TCAMS over the past 8 years and whether the expectations surrounding this initiative have become a reality.

Novel Trifluoromethylcoumarinyl Urea Derivatives: Synthesis, Characterization, Fluorescence, and Bioactivity

A series of novel trifluoromethylcoumarinyl urea derivatives were designed, synthesized, and characterized by ¹H-NMR, ¹³C-NMR, and HR-ESI-MS. The fluorescence spectra of the target compounds were recorded. The spectra show that most of the title compounds glow green with λ_max^em of 500-517 nm, while compounds 5r, 5s, 5u, and 5l (compounds named by authors) glow violet with λ_max^em of 381-443 nm. Moreover, the herbicidal and antifungal activities of the synthesized compounds were evaluated for their potential use as pesticides. The results indicate that compound 5f against the caulis of Amaranthusretroflexus and compounds 5j and 5l against the taproot of Digitariasanguinalis are equivalent to the commercial herbicide Acetochlor. Nine of the title compounds are more antifungal than commercial fungicide Carbendazim against Botrytis cinerea.

Plasmodium dihydrofolate reductase is a second enzyme target for the antimalarial action of triclosan

Malaria, caused by parasites of the genus Plasmodium, leads to over half a million deaths per year, 90% of which are caused by Plasmodium falciparum. P. vivax usually causes milder forms of malaria; however, P. vivax can remain dormant in the livers of infected patients for weeks or years before re-emerging in a new bout of the disease. The only drugs available that target all stages of the parasite can lead to severe side effects in patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency; hence, there is an urgent need to develop new drugs active against blood and liver stages of the parasite. Different groups have demonstrated that triclosan, a common antibacterial agent, targets the Plasmodium liver enzyme enoyl reductase. Here, we provide 4 independent lines of evidence demonstrating that triclosan specifically targets both wild-type and pyrimethamine-resistant P. falciparum and P. vivax dihydrofolate reductases, classic targets for the blood stage of the parasite. This makes triclosan an exciting candidate for further development as a dual specificity antimalarial, which could target both liver and blood stages of the parasite.

Identification of potential aryl hydrocarbon receptor ligands by virtual screening of industrial chemicals

We have developed a virtual screening procedure to identify potential ligands to the aryl hydrocarbon receptor (AhR) among a set of industrial chemicals. AhR is a key target for dioxin-like compounds, which is related to these compounds' potential to induce cancer and a wide range of endocrine and immune system-related effects. The virtual screening procedure included an initial filtration aiming at identifying chemicals with structural similarities to 66 known AhR binders, followed by 3 enrichment methods run in parallel. These include two ligand-based methods (structural fingerprints and nearest neighbor analysis) and one structure-based method using an AhR homology model. A set of 6445 commonly used industrial chemicals was processed, and each step identified unique potential ligands. Seven compounds were identified by all three enrichment methods, and these compounds included known activators and suppressors of AhR. Only approximately 0.7% (41 compounds) of the studied industrial compounds was identified as potential AhR ligands and among these, 28 compounds have to our knowledge not been tested for AhR-mediated effects or have been screened with low purity. We suggest assessment of AhR-related activities of these compounds and in particular 2-chlorotrityl chloride, 3-p-hydroxyanilino-carbazole, and 3-(2-chloro-4-nitrophenyl)-5-(1,1-dimethylethyl)-1,3,4-oxadiazol-2(3H)-one.

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data

PURPOSE

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability.

METHODS

Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism).

RESULTS

"Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h.

CONCLUSIONS

Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Databases and collaboration require standards for human stem cell research

Stem cell research is at an important juncture: despite significant potential for human health and several countries with key initiatives to expedite commercialization, there are gaps in capturing and exploiting the results of past and current research. Here, we propose a concerted plan that could be taken to foster a more collaborative approach and ensure that all research efforts can be leveraged across the community. The creation of a definitive centralized database repository, or at least harmonized data repositories, for stem cell groups in academia and industry, enabling secure selective sharing of data when needed, could provide the core structure that is sought globally and protect intellectual property. The development of minimum information about stem cell experiments (MIASCE) could be key to this development.

Bigger data, collaborative tools and the future of predictive drug discovery

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas.

Identification of novel phenyl butenonyl C-glycosides with ureidyl and sulfonamidyl moieties as antimalarial agents

A new series of C-linked phenyl butenonyl glycosides bearing ureidyl(thioureidyl) and sulfonamidyl moieties in the phenyl rings were designed, synthesized, and evaluated for their in vitro antimalarial activities against Plasmodium falciparum 3D7 (CQ sensitive) and K1 (CQ resistant) strains. Among all the compounds screened the C-linked phenyl butenonyl glycosides bearing sulfonamidyl moiety (5a) and ureidyl moiety in the phenyl ring (7d and 8c) showed promising antimalarial activities against both 3D7 and K1 strains with IC50 values in micromolar range and low cytotoxicity offering new HITS for further exploration.

Computational models for neglected diseases: gaps and opportunities

Neglected diseases, such as Chagas disease, African sleeping sickness, and intestinal worms, affect millions of the world's poor. They disproportionately affect marginalized populations, lack effective treatments or vaccines, or existing products are not accessible to the populations affected. Computational approaches have been used across many of these diseases for various aspects of research or development, and yet data produced by computational approaches are not integrated and widely accessible to others. Here, we identify gaps in which computational approaches have been used for some neglected diseases and not others. We also make recommendations for the broad-spectrum integration of these techniques into a neglected disease drug discovery and development workflow.

Animal models of efficacy to accelerate drug discovery in malaria

The emergence of resistance to artemisinins and the renewed efforts to eradicate malaria demand the urgent development of new drugs. In this endeavour, the evaluation of efficacy in animal models is often a go/no go decision assay in drug discovery. This important role relies on the capability of animal models to assess the disposition, toxicology and efficacy of drugs in a single test. Although the relative merits of each efficacy model of malaria as human surrogate have been extensively discussed, there are no critical analyses on the use of such models in current drug discovery. In this article, we intend to analyse how efficacy models are used to discover new antimalarial drugs. Our analysis indicates that testing drug efficacy is often the last assay in each discovery stage and the experimental designs utilized are not optimized to expedite decision-making and inform clinical development. In light of this analysis, we propose new ways to accelerate drug discovery using efficacy models.