RESUMEN
In the present study, we examined the antinociceptive and anti-inflammatory activities of a guanylhydrazone derivative, (E)-(3,5-di-tert-butyl-4-hydroxybenzylidene)-2-guanylhydrazone hydrochloride (LQM10), in mice. The antinociceptive effect was determined by assessing behavioural responses in different pain models, while anti-inflammatory activity was examined in carrageenan-induced pleurisy. Intraperitoneal LQM10 administration reduced the acetic acid-induced nociceptive behaviour, a phenomenon that was unaltered by pretreatment with yohimbine, atropine, naloxone or glibenclamide. In the formalin assay, LQM10 reduced nociceptive behaviour only in the second phase, indicating an inhibitory effect on inflammatory pain. LQM10 did not alter the pain latency in the hot plate assay and did not impact the locomotor activity of mice in the rotarod assay. In the carrageenan-induced pleurisy assay, LQM10 treatment inhibited critical events involved in inflammatory responses, namely, leucocyte recruitment, plasma leakage and increased inflammatory mediators (tumour necrosis factor Like Properties of Chalchones and Flavonoid Derivatives [TNF]-α and interleukin [IL]-1ß) in the pleural exudate. Overall, these results indicate that LQM10 exhibits antinociceptive effects associated with peripheral mechanisms and anti-inflammatory activity mediated via a reduction in leucocyte migration and proinflammatory mediators, rendering this compound a promising candidate for treating pain and inflammatory process.
Asunto(s)
Analgésicos , Pleuresia , Animales , Ratones , Analgésicos/efectos adversos , Carragenina , Nocicepción , Antiinflamatorios/farmacología , Antiinflamatorios/uso terapéutico , Dolor/tratamiento farmacológico , Extractos Vegetales/farmacología , Pleuresia/inducido químicamente , Pleuresia/tratamiento farmacológico , Factor de Necrosis Tumoral alfa , Edema/inducido químicamente , Edema/tratamiento farmacológicoRESUMEN
The Flaviviridae virus family consists of the genera Hepacivirus, Pestivirus, and Flavivirus, with approximately 70 viral types that use arthropods as vectors. Among these diseases, dengue (DENV) and zika virus (ZIKV) serotypes stand out, responsible for thousands of deaths worldwide. Due to the significant increase in cases, the World Health Organization (WHO) declared DENV a potential threat for 2019 due to being transmitted by infected travelers. Furthermore, ZIKV also has a high rate of transmissibility, highlighted in the outbreak in 2015, generating consequences such as Guillain-Barré syndrome and microcephaly. According to clinical outcomes, those infected with DENV can be asymptomatic, and in other cases, it can be lethal. On the other hand, ZIKV has severe neurological symptoms in newborn babies and adults. More serious symptoms include microcephaly, brain calcifications, intrauterine growth restriction, and fetal death. Despite these worrying data, no drug or vaccine is approved to treat these diseases. In the drug discovery process, one of the targets explored against these diseases is the NS2B-NS3 complex, which presents the catalytic triad His51, Asp75, and Ser135, with the function of cleaving polyproteins, with specificity for basic amino acid residues, Lys- Arg, Arg-Arg, Arg-Lys or Gln-Arg. Since NS3 is highly conserved in all DENV serotypes and plays a vital role in viral replication, this complex is an excellent drug target. In recent years, computer-aided drug discovery (CADD) is increasingly essential in drug discovery campaigns, making the process faster and more cost-effective, mainly explained by discovering new drugs against DENV and ZIKV. Finally, the main advances in computational methods applied to discover new compounds against these diseases will be presented here. In fact, molecular dynamics simulations and virtual screening is the most explored approach, providing several hit and lead compounds that can be used in further optimizations. In addition, fragment-based drug design and quantum chemistry/molecular mechanics (QM/MM) provides new insights for developing anti-DENV/ZIKV drugs. We hope that this review offers further helpful information for researchers worldwide and stimulates the use of computational methods to find a promising drug for treating DENV and ZIKV.