Cancer is the second most common cause of death worldwide. It can easily acquire resistance to treatments, demanding new therapeutic strategies, such as simultaneous inhibition of kinase and HDAC e... Graphical abstract

We report a series of 1,3-diphenylureido hydroxamate HDAC inhibitors evaluated against sensitive and drug-resistant P. falciparum strains. Compounds 8a–d show potent antiplasmodial activity, indicating that a phenyl spacer allows improved potency relative to cinnamyl and di-hydrocinnamyl linkers. In vitro, mechanistic studies demonstrated target activity for PfHDAC1 on a recombinant level, which agreed with cell quantification of the acetylated histone levels. Compounds 6c, 7c, and 8c, identified as the most active in phenotypic assays and PfHDAC1 enzymatic inhibition. Compound 8c stands out as a remarkable inhibitor, displaying an impressive 85% inhibition of PfHDAC1, with an IC₅₀ value of 0.74 µM in the phenotypic screening on Pf3D7 and 0.8 µM against multidrug-resistant PfDd2 parasites. Despite its potent inhibition of PfHDAC1, 8c remains the least active on human HDAC1, displaying remarkable selectivity. In silico studies suggest that the phenyl linker has an ideal length in the series for permitting effective interactions of the hydroxamate with PfHDAC1 and that this compound series could bind as well as in HsHDAC1. Taken together, these results highlight the potential of diphenylurea hydroxamates as a privileged scaffold for the generation of potent antimalarial HDAC inhibitors with improved selectivity over human HDACs.

O objetivo deste artigo é identificar as preocupações da comunidade de Ciências Exatas e Tecnológicas (C&T) no que tange à igualdade de gênero. Analisamos 16 artigos científicos, publicados entre 2008 e 2017, em periódicos de ciências exatas, tecnológicas e multidisciplinares. Eles trataram de: carreira; comunicação; educação; produção científica e perspectiva histórica do debate de gênero e C&T. Constatamos que a produção científica relacionando gênero e C&T nas áreas analisadas é marginal, focando em participação feminina e aspectos culturais, sem considerar o gênero como estruturante do próprio conhecimento, nem a diversidade entre as mulheres. O fechamento dessa lacuna exige abrir a caixa-preta da produção de C&T, o que demanda um esforço coletivo, envolvendo profissionais de C&T e de outras áreas, a fim de alargar nosso entendimento sobre as relações entre gênero e C&T, bem como propor ações que efetivamente contribuam para a redução das desigualdades de gênero considerando também as diferenças entre as mulheres.

Hematological cancer treatment with hybrid kinase/HDAC inhibitors is a novel strategy to overcome the challenge of acquired resistance to drugs. We collected IC ₅₀ datasets from the ChEMBL database for 13 cancer cell lines (72 h cytotoxicity, measured by MTT), known inhibitors for 38 kinases, and 10 HDACs isoforms, that we identified by target fishing and literature review. The data was subjected to rigorous biological and chemical curation leaving the final datasets ranging from 76 to 8173 compounds depending on the target. We generated Random Forest classification models, whereby 14 showed greater than 80% predictability after 5-fold external cross-validation. We screened 30 hybrid kinase/HDAC inhibitor analogs through each of these models. Fragment-contribution maps were constructed to aid the understanding of SARs and the optimization of these compounds as selective kinase/HDAC inhibitors for cancer treatment. Among the predicted compounds, 9 representative hybrids were synthesized and subjected to biological evaluation to validate the models. We observed high hit rates after biological testing for the following models: K562 (62.5%), MV4-11 (75.0%), MM1S (100%), NB-4 (62.5%), U937 (75.0), and HDAC6 (86.0%). This aided the identification of 6b and 6k as potent anticancer inhibitors with IC ₅₀ of 0.2-0.8 µM in three cancer cell lines, linked to HDAC6 inhibition below 2 nM, and blockade of AKT2 phosphorylation at 2 μM, validating the ability of our models to predict novel drug candidates. Graphical Highlights: Novel kinase/HDAC inhibitors for cancer treatment were found using machine learning 61 QSAR models for hematological cancers and its targets were built and validated K562, MV4-11, MM1S, NB-4, U937, and HDAC6 models had hit rates above 62.5% in tests 6b and 6k presented potent IC ₅₀ of 0.2-0.8 µM in three cancer cell lines 6b and 6k inhibited HDAC6 below 2 nM, and blockade of AKT2 phosphorylation at 2 μM