2019
DOI: 10.1016/j.ejmech.2018.11.062
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Discovery of new potent hits against intracellular Trypanosoma cruzi by QSAR-based virtual screening

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Cited by 27 publications
(17 citation statements)
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“…In addition, many studies utilize computational approaches to identify potential inhibitors of T. cruzi crucial molecular targets (Scarim et al, 2018a,b). Melo-Filho et al, 2019 used a virtual screening based on quantitative structure-activity relationships (QSAR) model to prospect novel molecules against the T. cruzi in commercial database. This model made possible the identification of seven potent and selective compounds against the parasite, which were validated in in vitro experiments.…”
Section: Brief Perspectivementioning
confidence: 99%
“…In addition, many studies utilize computational approaches to identify potential inhibitors of T. cruzi crucial molecular targets (Scarim et al, 2018a,b). Melo-Filho et al, 2019 used a virtual screening based on quantitative structure-activity relationships (QSAR) model to prospect novel molecules against the T. cruzi in commercial database. This model made possible the identification of seven potent and selective compounds against the parasite, which were validated in in vitro experiments.…”
Section: Brief Perspectivementioning
confidence: 99%
“…Structure-based drug design by virtual screening and molecular docking studies has become a valuable primary step in the identification of novel lead molecules for the treatment of diseases [59,60], and proven to be a very efficient tool for antiviral [61][62][63][64] and antibacterial [65,66] and antiprotozoal [67,68] drug discovery. Therefore, a virtual screening experiment was conducted to determine the interaction of natural ligands of the NPASS database within the binding pocket of putative drug targets of the virus that was calculated in terms of docking scores and MM-GBSA values.…”
Section: Introductionmentioning
confidence: 99%
“…In particular, computational techniques directed to studies related to CD can be considered as powerful tools to help in the discovery and the design of selective, potent, and safer drug candidates [ 16 , 17 , 18 , 19 ]. In this study, seven bioactive neolignans ( 1 – 7 ) were isolated from the flower extract of N. leucantha and were, altogether with other related bioactive compounds ( 8 – 50 ), subjected to robust and predictive in silico models, using two-(2D) and three-(3D) dimensional techniques [ 20 , 21 , 22 , 23 , 24 ], as indicated in Figure 1 . It is also worth noting that the use of various techniques to construct predictive models is an important strategy since these approaches employ different and complementary molecular information (for example, bidimensional, steric/electrostatic/hydrophobic features), which helps in the design of new drug candidates.…”
Section: Introductionmentioning
confidence: 99%