Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures.

ABSTRACT: The parasite Plasmodium falciparum is the most lethal species of Plasmodium to cause serious malaria infection in humans, and with resistance developing rapidly novel treatment modalities are currently being sought, one of which being combinations of existing compounds. The discovery of combinations of antimalarial drugs that act synergistically with one another is hence of great importance; however an exhaustive experimental screen of large drug space in a pairwise manner is not an option. In this study we apply our machine learning approach, Combination Synergy Estimation (CoSynE), which can predict novel synergistic drug interactions using only prior experimental combination screening data and knowledge of compound molecular structures, to a dataset of 1,540 antimalarial drug com

SUBMITTER: Mason DJ 

PROVIDER: S-EPMC6176478 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature