Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds

N Baurin, R Baker, C Richardson, I Chen, N Foloppe, A Potter, A Jordan, S Roughley, M Parratt, P Greaney, D Morley, R E Hubbard

Research output: Contribution to journalArticlepeer-review

Abstract

We have implemented five drug-like filters, based on ID and 2D molecular descriptors, and applied them to characterize the drug-like properties of commercially available chemical compounds. In addition to previously published filters (Lipinski and Veber), we implemented a filter for medicinal chemistry tractability based on lists of chemical features drawn up by a panel of medicinal chemists. A filter based on the modeling of aqueous solubility (>1 muM) was derived in-house, as well as another based on the modeling of Caco-2 passive membrane permeability (>10 nm/s). A library of 2.7 million compounds was collated from the 23 compound suppliers and analyzed with these filters, highlighting a tendency toward highly lipophilic compounds. The library contains 1.6M unique structures, of which 37% (607 223) passed all five drug-like filters. None of the 23 suppliers provides all the members of the drug-like subset, emphasizing the benefit of considering compounds from various compound suppliers as a source of diversity for drug discovery.

Original languageEnglish
Pages (from-to)643-651
Number of pages9
JournalJOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
Volume44
Issue number2
DOIs
Publication statusPublished - 2004

Keywords

  • AQUEOUS SOLUBILITY
  • ORGANIC-COMPOUNDS
  • STATE INDEXES
  • DIVERSE SET
  • PREDICTION
  • CLASSIFICATION
  • PERMEABILITY
  • ABSORPTION
  • DISCOVERY
  • TRANSPORT

Cite this