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Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

Figure 1

Schematic diagram of (A) drug-based similarity inference (DBSI), (B) target-based similarity inference (TBSI) and (C) network-based inference (NBI) methods.

The entire workflow includes five steps: (i) collection of known drug-target interaction data and construction of bipartite drug-target graphs; (ii) calculation of drug-drug two dimensional structural similarity (SC), target-target genomic sequence similarity (Sg) and drug-target topology network similarity; (iii) application of new methods in prediction of new drugs for a given target (pink square) or new targets for a given drug (pink circle); (iv) validation of new drug-target interactions by experimental assays (D); (v) visualization of experimental results using drug-target-disease associations network analysis (E). In A–C, given drug node (pink circle) denotes the drug which we want to predict new target for, given target node (pink square) denotes the target which we want to predict new drug for, drug with resource (green circle) denotes that this drug have resource, target with resource (green square) denotes that this target have resource, the more resource a node possesses, the darker the color is, blue edges denote the drug-target interactions with known experimental evidence, black arrows denote the resource diffusion direction. In E, green circle: drug node, red square: on-target node, blue square: off-target node, yellow square: new off-target node, violet square: disease node.

Figure 1

doi: https://doi.org/10.1371/journal.pcbi.1002503.g001