Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension

  • M. Stuart Armstrong
  • Paul W. Finn
  • Garrett M. Morris
  • W. Graham. Richards
Article

Abstract

In a previous paper, we presented the ElectroShape method, which we used to achieve successful ligand-based virtual screening. It extended classical shape-based methods by applying them to the four-dimensional shape of the molecule where partial charge was used as the fourth dimension to capture electrostatic information. This paper extends the approach by using atomic lipophilicity (alogP) as an additional molecular property and validates it using the improved release 2 of the Directory of Useful Decoys (DUD). When alogP replaced partial charge, the enrichment results were slightly below those of ElectroShape, though still far better than purely shape-based methods. However, when alogP was added as a complement to partial charge, the resulting five-dimensional enrichments shows a clear improvement in performance. This demonstrates the utility of extending the ElectroShape virtual screening method by adding other atom-based descriptors.

Keywords

Molecular similarity Molecular descriptors Ligand-based virtual screening Drug design Lipophilicity Electrostatics 

References

  1. 1.
    Armstrong MS, Morris GM, Finn PW, Sharma R, Moretti L, Cooper RI, Richards WG (2010) Electroshape: fast molecular similarity calculations incorporating shape, chirality and electrostatics. J Comput Aided Mol Des 24(9):789–801CrossRefGoogle Scholar
  2. 2.
    Ballester PJ, Finn PW, Richards WG (2009) Ultrafast shape recognition: evaluating a new ligand-based virtual screening technology. J Mol Graph Model 27:836–845CrossRefGoogle Scholar
  3. 3.
    Ballester PJ, Richards WG (2007) Ultrafast shape recognition to search compound databases for similar molecular shapes. J Comput Chem 28:1711–1723CrossRefGoogle Scholar
  4. 4.
    Armstrong MS, Morris GM, Finn PW, Sharma R, Richards WG (2009) Molecular similarity including chirality. J Mol Graph Model 28:368–370CrossRefGoogle Scholar
  5. 5.
    Wildman SA, Crippen GM (1999) Prediction of physiochemical parameters by atomic contributions. J Chem Inf Comput Sci 39:868–873CrossRefGoogle Scholar
  6. 6.
    Chemical Computing Group, Montreal, Canada, MOE 2008.10, http://www.chemcomp.com
  7. 7.
    Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49(23):6789–6801CrossRefGoogle Scholar
  8. 8.
    Halgren TA (1996) The merck force field. J Comp Chem 17:490–641CrossRefGoogle Scholar
  9. 9.
    Dewar MJS, Zoebisch EG, Healy F, Stewart JJP (1985) AM1: a new general purpose quantum mechanical molecular model. J Am Chem Soc 107(13):3902–3909. doi:10.1021/ja00299a024 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • M. Stuart Armstrong
    • 1
  • Paul W. Finn
    • 1
  • Garrett M. Morris
    • 1
  • W. Graham. Richards
    • 2
  1. 1.InhibOx, Oxford Centre for InnovationOxfordUK
  2. 2.Department of ChemistryUniversity of OxfordOxfordUK

Personalised recommendations