Resumo Métodos de aprendizagem de máquina podem ser usados para auxiliar o projeto de edifícios energeticamente eficientes, reduzindo cargas de energia enquanto se mantém a temperatura interna desejada. Eles operam estimando uma resposta a partir de um conjunto de entradas tais como a geometria do edifício, propriedades do material, custos do projeto, condições do tempo no local e impacto ambiental. Esses métodos requerem uma fase de treinamento que considera uma base de dados construída a partir de variáveis selecionadas no domínio do problema. Este trabalho avalia o desempenho de quatro métodos de aprendizado de máquina na predição de cargas de resfriamento e aquecimento de edifícios residenciais. A base de dados do treinamento consiste de oito variáveis de entrada e duas variáveis de saída, todas derivadas de projetos de edifícios. Os métodos foram selecionados de acordo com uma pesquisa exaustiva e ajustados por uma estratégia com validação cruzada. Para a avaliação foram usadas quatro medidas estatísticas de desempenho e um índice de sintetização e resultados. Essa estratégia resultou em algoritmos com parâmetros otimizados e permitiu obter resultados competitivos com os apresentados na literatura.

In this work, we combined molecular modeling, computational docking and in vitro analysis to explore the antileishmanial effect of some resveratrol analogs (ResAn), focusing on their pro-oxidant effect. The molecular target was the trypanothione reductase of Leishmania braziliensis (LbTryR), an essential component of the antioxidant defenses in trypanosomatid parasites. Three-dimensional structures of LbTryR were modeled and molecular docking studies of ResAn1-5 compounds showed the following affinity: ResAn1 > ResAn2 > ResAn4 > ResAn5 > ResAn3. Positive correlation was observed between these compounds’ affinity to the LbTryR and the IC₅₀ values against Leishmania sp (ResAn1 < ResAn2 < ResAn4), which allows for TryR being considered an important target for them. As the compound ResAn1 showed the best antileishmanial activity, and docking studies showed its high affinity for NADP binding site (NS) of TryR, plus having been able to induce ROS production in L. braziliensis promastigotes treated, ResAn1 probably occupies NS interfering in the electron transfer processes responsible for the catalytic reaction. The in silico prediction of ADMET properties suggests that ResAn1 may be a promising drug candidate with properties to cross biological membranes and high gastrointestinal absorption, not violating Lipinski’s rules. Ultimately, the antileishmanial effect of ResAn can be associated with a pro-oxidant effect which, in turn, can be exploited as an antimicrobial agent. Communicated by Ramaswamy H. Sarma

Schistosomiasis, caused by parasites of the genus Schistosoma, is a neglected disease with high global prevalence, affecting more than 240 million people in several countries. Praziquantel (PZQ) is the only drug currently available for the treatment. S. mansoni NTPDases (known as SmNTPDases, ATP diphosphohydrolases or ecto-apyrases) are potential drug targets for the discovery of new antischistosomal drugs. In this study, we screen NTPDases inhibitors from Centella erecta (Apiaceae) using an ultrafiltration combined UHPLC-QTOF-MS method and potato apyrase, identifying asiaticoside as one of the apyrase-binding compounds. After isolation of asiaticoside from C. erecta extract, we assessed its in vivo antischistosomal activities against Schistosoma mansoni worms and its in vitro enzymatic apyrase inhibition. Also, molecular docking analysis of asiaticoside against potato apyrase, S. mansoni NTPDases 1 and 2 were performed. Asiaticoside showed a significant in vitro apyrase inhibition and molecular docking studies corroborate with its possible actions in potato apyrase and S. mansoni NTPDases. In mice harboring a patent S. mansoni infection, a single oral dose of asiaticoside (400 mg/kg. p.o.) showed significantly in vivo antischistosomal efficacy, markedly decreasing the total worm load and egg burden, giving support for further exploration of apyrase inhibitors as antischistosomal agents.

Mutation in the ethionamide (ETH) activating enzyme, EthA, is the main factor determining resistance to this drug, used to treat TB patients infected with MDR and XDR Mycobacterium tuberculosis isolates. Many mutations in EthA of ETH resistant (ETH-R) isolates have been described but their roles in resistance remain uncharacterized, partly because structural studies on the enzyme are lacking. Thus, we took a two-tier approach to evaluate two mutations (Y50C and T453I) found in ETH-R clinical isolates. First, we used a combination of comparative modeling, molecular docking, and molecular dynamics to build an EthA model in complex with ETH that has hallmark features of structurally characterized homologs. Second, we used free energy computational calculations for the reliable prediction of relative free energies between the wild type and mutant enzymes. The ΔΔG values for Y50C and T453I mutant enzymes in complex with FADH₂-NADP-ETH were 3.34 (+/−0.55) and 8.11 (+/−0.51) kcal/mol, respectively, compared to the wild type complex. The positive ΔΔG values indicate that the wild type complex is more stable than the mutants, with the T453I complex being the least stable. These are the first results shedding light on the molecular basis of ETH resistance, namely reduced complex stability of mutant EthA.