Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds. Baurin, N., Baker, R., Richardson, C., Chen, I., Foloppe, N., Potter, A., Jordan, A., Roughley, S., Parratt, M., Greaney, P., Morley, D., & Hubbard, R. E. Journal of Chemical Information and Computer Sciences, 44(2):643-651, 2004.
Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds. [link]_mendeley  Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds. [link]Paper  abstract   bibtex   
We have implemented five drug-like filters, based on 1D 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 microM) 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 1.6 M 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.
@article{ mendeley_4180617263,
  isauthor = {1},
  abstract = {We have implemented five drug-like filters, based on 1D 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 microM) 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 1.6 M 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.},
  canonical_id = {d6061f70-6cff-11df-a2b2-0026b95e3eb7},
  added = {1317635361},
  year = {2004},
  isstarred = {0},
  id = {4180617263},
  discipline = {Chemistry},
  journal = {Journal of Chemical Information and Computer Sciences},
  title = {Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds.},
  institution = {Vernalis (Cambridge) Ltd., Granta Park, Abington, Cambridge, CB1 6GB, UK. n.baurin@vernalis.com},
  deletionpending = {0},
  version = {1359627129},
  pmid = {15032546},
  number = {2},
  url_mendeley = {http://www.mendeley.com/catalog/drug-like-annotation-duplicate-analysis-23-supplier-chemical-database-totalling-2-7-million-compound/},
  volume = {44},
  isread = {0},
  author = {N {Baurin} and R {Baker} and C {Richardson} and I {Chen} and N {Foloppe} and A {Potter} and A {Jordan} and S {Roughley} and M {Parratt} and P {Greaney} and D {Morley} and R E {Hubbard}},
  pages = {643-651},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/15032546},
  type = {Journal Article},
  modified = {1359627129},
  journal = {Journal of Chemical Information and Computer Sciences},
  subdiscipline = {None}
}

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