J Chem Inf Model - Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening.

Tópicos

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Resumo

Quantitative structure-activity relationship (QSAR) models have been developed for a data set of 3133 compounds defined as either active or inactive against P. falciparum. Because the data set was strongly biased toward inactive compounds, different sampling approaches were employed to balance the ratio of actives versus inactives, and models were rigorously validated using both internal and external validation approaches. The balanced accuracy for assessing the antimalarial activities of 70 external compounds was between 87% and 100% depending on the approach used to balance the data set. Virtual screening of the ChemBridge database using QSAR models identified 176 putative antimalarial compounds that were submitted for experimental validation, along with 42 putative inactives as negative controls. Twenty five (14.2%) computational hits were found to have antimalarial activities with minimal cytotoxicity to mammalian cells, while all 42 putative inactives were confirmed experimentally. Structural inspection of confirmed active hits revealed novel chemical scaffolds, which could be employed as starting points to discover novel antimalarial agents.

Resumo Limpo

quantit structureact relationship qsar model develop data set compound defin either activ inact p falciparum data set strong bias toward inact compound differ sampl approach employ balanc ratio activ versus inact model rigor valid use intern extern valid approach balanc accuraci assess antimalari activ extern compound depend approach use balanc data set virtual screen chembridg databas use qsar model identifi putat antimalari compound submit experiment valid along putat inact negat control twenti five comput hit found antimalari activ minim cytotox mammalian cell putat inact confirm experiment structur inspect confirm activ hit reveal novel chemic scaffold employ start point discov novel antimalari agent

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