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Abstract
This research aimed to identify new antimalarial drug candidates against Plasmodium falciparum by analyzing parasite transcriptomes across different life stages. They identified 674 overlapping highly expressed genes (409 essential), leading to 70 potential drug targets and 75 associated compounds. Further analysis using machine learning models on similar compounds identified two promising candidates: HSP-990 and silvestrol aglycone. Silvestrol aglycone showed potent nanomolar inhibitory activity against the asexual blood stage, low cytotoxicity, transmission-blocking potential, and efficacy comparable to established antimalarials, warranting further investigation as a dual-acting antimalarial.
Publisher
ACS Omega
Published On
Sep 05, 2023
Authors
Joyce V B Borba, Beatriz Rosa De Azevedo, Larissa A Ferreira, Aline Rimoldi, Luís C Salazar Alvarez, Juliana Calit, Daniel Y Bargieri, Fabio T M Costa, Carolina Horta Andrade
Tags
antimalarial
Plasmodium falciparum
drug candidates
silvestrol aglycone
machine learning

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