Advertisement

Knowledge-Based Identification of Multicomponent Therapies

  • Francesca Vitali
  • Francesca Mulas
  • Pietro Marini
  • Riccardo Bellazzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

In recent years, several approaches have been proposed to improve the capacity of pharmaceutical research to support personalized care. An approach that takes advantages of the large amount of biological knowledge continuously collected in different repositories could improve the drug discovery process. In this context, networks are increasingly used as universal platforms to integrate the knowledge available on a complex disease. The objective of this work is to provide a knowledge-based strategy to support polypharmacology, a new promising approach for drug discovery. Given a specific disease, the proposed method is able to identify the possible targets by analysing the topological features of the related network. The network-based analysis defines a score aimed at ranking the targets and selecting their best combinations. The results obtained on Type 2 Diabetes Mellitus highlight the ability of the method to retrieve novel target candidates related to the considered disease.

Keywords

polypharmacology network-based bioinformatics drug discovery target ranking 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hwang, W., Cho, R.M.: Bridging centrality: Identifying bridging nodes in scale-free networks. Technical Report, Department of Computer Science and Engineering, University at Buffalo (2006)Google Scholar
  2. 2.
    Leung, E.L., Cao, Z.W., Jiang, Z.H., Zhou, H., Liu, L.: Network-based drug discovery by integrating systems biology and computational technologies. Briefings in Bioinformatics (2012)Google Scholar
  3. 3.
    Li, Q., Li, X., Li, C., Chen, L., Song, J., Tang, Y., Xu, X.: A network-based multi-target computational estimation scheme for anticoagulant activities of compounds. PLoS ONE 6(3), e14774 (2011)Google Scholar
  4. 4.
    Li, S., Zhang, B., Zhang, N.: Network target for screening synergistic drug combinations with application to traditional chinese medicine. BMC Systems Biology 5(suppl. 1), S10 (2011)Google Scholar
  5. 5.
    Vallabhajosyula, R.R., Chakravarti, D., Lutfeali, S., Ray, A., Raval, A.: Identifying hubs in protein interaction networks. PLoS ONE 4(4), e5344 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Francesca Vitali
    • 1
  • Francesca Mulas
    • 1
  • Pietro Marini
    • 2
  • Riccardo Bellazzi
    • 1
  1. 1.Dipartimento di Ingegneria Industriale e dell’InformazioneUniversity of PaviaItaly
  2. 2.Demetra PharmaceuticalPiacenzaItaly

Personalised recommendations