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Drug target prediction using chem- and bioinformatics

  • Rita C. Guedes and Tiago Rodrigues EMAIL logo
Published/Copyright: November 20, 2018
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Abstract

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.

Acknowledgements

Rita Guedes thanks the funding received from the European Structural & Investment Funds through the COMPETE Programme and from National Funds through FCT under the Programme grant SAICTPAC/0019/2015, PDTC/QEQ-MED/7042/2014 and UID/DTP/04138/2013. Tiago Rodrigues thanks generous support by the Marie Curie Actions (IF grant 743640 and TWINN-2017 ACORN, Grant 807281) and FCT/FEDER (02/SAICT/2017, Grant 28333).

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Published Online: 2018-11-20

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