An in silico model for interpreting polypharmacology in drug-target networks.

Access this Article

Abstract

<Book Title> In Silico Models for Drug DiscoveryRecent analysis on polypharmacology leads to the idea that only small fragments of drugs and targets are a key to understanding their interactions forming polypharmacology. This idea motivates us to build an in silico approach of finding significant substructure patterns from drug-target (molecular graph-amino acid sequence) pairs. 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.

Journal

  • Methods in molecular biology

    Methods in molecular biology (993), 67-80, 2013-03-05

    Humana Press

Codes

  • NII Article ID (NAID)
    120005587804
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    1064-3745
  • Data Source
    IR 
Page Top