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- Title
A Computational Method for Unveiling the Target Promiscuity of Pharmacologically Active Compounds.
- Authors
Schneider, Petra; Schneider, Gisbert
- Abstract
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.
- Subjects
DRUG design; LIGANDS (Chemistry); MACROMOLECULAR synthesis; COMPUTATIONAL chemistry; POLYMERIC drugs; PHARMACEUTICAL chemistry
- Publication
Angewandte Chemie, 2017, Vol 129, Issue 38, p11678
- ISSN
0044-8249
- Publication type
Article
- DOI
10.1002/ange.201706376