Based on drugCIPHER-MS, a genome-wide map of biological fingerprints for 726 drugs is built, and unexpected drug relations, which imply potential novel drug applications and side effects, are generated.
By integrating TS and CS in pharmacological space and PPIs in genomic space, unexpected drug relations emerge, which demonstrate that the integration of existing multi-dimensional information may generate additional knowledge.
Systems pharmacology aims to integrate knowledge about drugs, drug-drug interactions, drug interactions with cells and organs, and drug relations to adverse events and desired effects in individual patients [ 1].
AUC values of simple algorithm are 0.679, 0.778, and 0.602, in Drug-Protein relation, Drug-Disease relation, and Protein-Disease relation, respectively.
At a significance level of 0.05 of the activity resemblance, 501 unexpected drug-drug relations are obtained (Table S1).
Based on drugCIPHER-MS, a genome-wide map of drug biological fingerprints for 726 drugs is constructed, within which unexpected drug-drug relations emerged in 501 cases, implying possible novel applications or side effects.
Applied to marketed drugs, a network of side-effect-driven drug-drug relations became apparent.
Several unexpected drug-drug relations are formed by chemically dissimilar drugs from different therapeutic indications, which implies new drug-target relations [ 51].
The definition of the network search can be changed to include multiple additional information types e.g. drug-relations.
