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Drug target prediction using chem- and bioinformatics

Rita C. Guedes
  • Research Institute for Medicines (iMed.Ulisboa), Faculdade de Farmácia da Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003, Lisboa, Portugal
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Tiago Rodrigues
  • Corresponding author
  • Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Av. Prof. Egas Moniz, 1649-028 Lisboa, Portugal
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Published Online: 2018-11-20 | DOI: https://doi.org/10.1515/psr-2018-0112


The biological pre-validation of natural products (NPs) and their underlying frameworks ensures an unrivaled source of inspiration for chemical probe and drug design. However, the poor knowledge of their drug target counterparts critically hinders the broader exploration of NPs in chemical biology and molecular medicine. Cutting-edge algorithms now provide powerful means for the target deconvolution of phenotypic screen hits and generate motivated research hypotheses. Herein, we present recent progress in artificial intelligence applied to target identification that may accelerate future NP-inspired molecular medicine.

Keywords: machine intelligence; cheminformatics; chemical biology; target identification; natural products


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Published Online: 2018-11-20

Citation Information: Physical Sciences Reviews, Volume 3, Issue 12, 20180112, ISSN (Online) 2365-659X, DOI: https://doi.org/10.1515/psr-2018-0112.

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