| Literature DB >> 30730601 |
Gisbert Schneider1, David E Clark2.
Abstract
Medicinal chemistry and, in particular, drug design have often been perceived as more of an art than a science. The many unknowns of human disease and the sheer complexity of chemical space render decision making in medicinal chemistry exceptionally demanding. Computational models can assist the medicinal chemist in this endeavour. Provided here is an overview of recent examples of automated de novo molecular design, a discussion of the concepts and computational approaches involved, and the daring prediction of some of the possibilities and limitations of drug design using machine intelligence.Entities:
Keywords: artificial intelligence; drug discovery; machine learning; medicinal chemistry; synthesis
Mesh:
Year: 2019 PMID: 30730601 DOI: 10.1002/anie.201814681
Source DB: PubMed Journal: Angew Chem Int Ed Engl ISSN: 1433-7851 Impact factor: 15.336