An In Silico Model for Interpreting Polypharmacology in Drug–Target Networks

This article introduces an efficient in silico method for enumerating, from given drug–target pairs, all frequent subgraph–subsequence pairs, which can then be further examined by hypothesis testing for statistical significance. Unique features of the method are its scalability, computational efficiency, and technical soundness in terms of computer science and statistics. The presented method was applied to 11,219 drug–target pairs in DrugBank to obtain significant substructure pairs, which can divide most of the original 11,219 pairs into eight highly exclusive clusters, implying that the obtained substructure pairs are indispensable components for interpreting polypharmacology.
Source: Springer protocols feed by Pharmacology/Toxicology - Category: Drugs & Pharmacology Source Type: news