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A Computational Method for Unveiling the Target Promiscuity of Pharmacologically Active Compounds

Schneider, Petra ; Schneider, Gisbert

Angewandte Chemie International Edition, 11 September 2017, Vol.56(38), pp.11520-11524 [Peer Reviewed Journal]

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  • Title:
    A Computational Method for Unveiling the Target Promiscuity of Pharmacologically Active Compounds
  • Author: Schneider, Petra ; Schneider, Gisbert
  • Subjects: Celecoxib ; Drug Discovery ; Machine Learning ; Medicinal Chemistry ; Off-Target Effects
  • Is Part Of: Angewandte Chemie International Edition, 11 September 2017, Vol.56(38), pp.11520-11524
  • Description: Drug discovery is governed by the desire to find ligands with defined modes of action. It has been realized that even designated selective drugs may have more macromolecular targets than is commonly thought. Consequently, it will be mandatory to consider multitarget activity for the design of future medicines. Computational models assist medicinal chemists in this effort by helping to eliminate unsuitable lead structures and spot undesired drug effects early in the discovery process. Here, we present a straightforward computational method to find previously unknown targets of pharmacologically active compounds. Validation experiments revealed hitherto unknown targets of the natural product resveratrol and the nonsteroidal anti‐inflammatory drug celecoxib. The obtained results advocate machine learning for polypharmacology‐based molecular design, drug re‐purposing, and the “de‐orphaning” of phenotypic drug effects. : A new computational method led to the discovery of hitherto unknown activities of the natural product resveratrol and the non‐steroidal anti‐inflammatory drug celecoxib.
  • Language: English
  • Identifier: ISSN: 1433-7851 ; E-ISSN: 1521-3773 ; DOI: 10.1002/anie.201706376

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