Coping with polypharmacology by computational medicinal chemistry.
Published
Journal Article
Predicting the macromolecular targets of drug-like molecules has become everyday practice in medicinal chemistry. We present an overview of our recent research activities in the area of polypharmacology-guided drug design. A focus is put on the self-organizing map (SOM) as a tool for compound clustering and visualization. We show how the SOM can be efficiently used for target-panel prediction, drug re-purposing, and the design of focused compound libraries. We also present the concept of virtual organic synthesis in combination with quantitative estimates of ligand-receptor binding, which we used for de novo designing target-selective ligands. We expect these and related approaches to enable the future discovery of personalized medicines.
Full Text
Duke Authors
Cited Authors
- Schneider, G; Reker, D; Rodrigues, T; Schneider, P
Published Date
- September 2014
Published In
Volume / Issue
- 68 / 9
Start / End Page
- 648 - 653
PubMed ID
- 25437786
Pubmed Central ID
- 25437786
International Standard Serial Number (ISSN)
- 0009-4293
Digital Object Identifier (DOI)
- 10.2533/chimia.2014.648
Language
- eng