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