title: Drug combinatorics and side effect estimation on the signed human drug-target network.
abstract: The mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of multiple drugs on the ensemble of common targets.
  
  
  
  In this paper it is shown that for the signed human drug-target network the majority of drug pairs tend to have synergistic effects on the common targets, i.e., drug pairs tend to have modes of action with the same sign on most of the shared targets, especially for the principal pharmacological targets of a drug. Methods are proposed to compute this synergism, as well as to estimate the influence of the drugs on the side effect of another drug.
  
  
  
  Enriching a drug-target network with information of functional nature like the sign of the interactions allows to explore in a systematic way a series of network properties of key importance in the context of computational drug combinatorics.
authors.affiliation: School of Telecommunications Engineering, Universitat Politècnica de Catalunya, 1-3 Jordi Girona Street, Barcelona, 08034, Spain.
authors.forename: Núria Ballber
authors.initials: NB
authors.lastname: Torres
authors.affiliation: Division of Automatic Control, Dept. of Electrical Engineering, Linköping University, SE-58183 Linköping, Sweden. claudio.altafini@liu.se.
authors.forename: Claudio
authors.initials: C
authors.lastname: Altafini
mesh_terms: D019295:Computational Biology; D055808:Drug Discovery; D004347:Drug Interactions; D004357:Drug Synergism; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D058990:Molecular Targeted Therapy