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Background: New anti-malarial drugs are needed to meet the challenge of artemisinin resistance and to achieve malaria elimination and eradication. The new anti-malarial compounds are expected to have many desirable properties, such as activity against multiple stages of Plasmodium , low host cytotoxicity, and low propensity for resistance development, but whether and how these properties might be linked to each other is not clear. A better understanding of the relationship between activities of compounds against different stages of Plasmodium could help in the development of strategies to prioritize compounds with maximum potential for further development.  Methods: We utilized the large amount of data that has recently been generated on 400 anti-malarial Malaria Box compounds and performed statistical analyses, such as rank correlation, hierarchical clustering, and principal-component analyses, to test associations between activities against different stages of Plasmodium , other pathogens, and human cells.  Results: We found significant positive correlations between the activities of compounds against different stages of Plasmodium . Our results also show toxicity associated with assays conducted at higher compound concentrations. Principal-component analyses (PCA) of the data allowed differentiation of Plasmodium -specific activity from general toxicity and predicted success in in vitro evolution of resistance. We found that a single principal-component can capture most of the desirable properties of Malaria Box compounds and can be used to rank compounds from most desirable to least desirable activity-profile.  Conclusions: Here, we provide a systematic strategy to prioritize Malaria Box compounds for further development. This approach may be applied for prioritization of anti-malarial compounds in general.

Dimension reduction of Malaria Box data allows efficient compound prioritization