Computational drug repurposing to predict approved and novel drug-disease associations.

Khalid Z., Sezerman O. U.

Journal of molecular graphics & modelling, cilt.85, ss.91-96, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 85
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.jmgm.2018.08.005
  • Dergi Adı: Journal of molecular graphics & modelling
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.91-96
  • Anahtar Kelimeler: Drug repurposing, Binding site similarity, Multiple data sources, Similarity measures, Integrative method, Common pathways, Drug promiscuity, Drug repositioning, DATABASE, DISCOVERY
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Hayır

Özet

The Drug often binds to more than one targets defined as polypharmacology, one application of which is drug repurposing also referred as drug repositioning or therapeutic switching. The traditional drug discovery and development is a high-priced and tedious process, thus making drug repurposing a popular alternate strategy. We proposed an integrative method based on similarity scheme that predicts approved and novel Drug targets with new disease associations. We combined PPI, biological pathways, binding site structural similarities and disease-disease similarity measures. The results showed 94% Accuracy with 0.93 Recall and 0.94 Precision measure in predicting the approved and novel targets surpassing the existing methods. All these parameters help in elucidating the unknown associations between drug and diseases for finding the new uses for old drugs. (C) 2018 Elsevier Inc. All rights reserved.