Transcriptomics-Guided In Silico Drug Repurposing: Identifying New Candidates with Dual-Stage Antiplasmodial Activity

Malaria remains a significant public health threat in tropical and subtropical regions, causing approximately 247 million cases annually. In the absence of a viable vaccine, timely and effective treatment is critical. However, increasing parasite resistance to existing drugs highlights the urgent need for new antimalarial therapies.
In this study, we sought to identify novel drug candidates against Plasmodium falciparum, the primary causative agent of malaria, by analyzing transcriptomic data across different parasite life stages. Using publicly available datasets, we identified genes expressed throughout the parasite’s life cycle—including the asexual blood stage, gametocyte stage, liver stage, and sexual stages in the insect vector. Our analysis revealed 674 overlapping genes, 409 of which are essential.
By cross-referencing drug target databases, we identified 70 HSP990 potential drug targets and 75 associated bioactive compounds. Expanding our search to structurally similar compounds, we compiled a list of 1,557 candidates and predicted their activity using machine learning models trained on five Plasmodium life stages. Two compounds, HSP-990 and silvestrol aglycone, were selected for experimental validation. Both exhibited potent inhibitory activity against the P. falciparum 3D7 strain at nanomolar concentrations. Notably, silvestrol aglycone demonstrated low cytotoxicity in mammalian cells, transmission-blocking potential, and efficacy comparable to established antimalarials.
These findings support further investigation of silvestrol aglycone as a promising dual-acting antimalarial with transmission-blocking potential for malaria control.