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Quantitative Estimate of Drug-likeness in StarDrop

Thursday, 21 February 2013 01:29
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Matt Segall

In a recent article, Bickerton et al. (2012) “The Chemical Beauty of Drugs” Nature Chemistry 4, 90–98, the authors proposed a measure of ‘drug-likeness’, the Quantitative Estimate of Drug-likeness (QED), that relates the similarity of a compound’s properties to those of oral drugs based on eight commonly used molecular properties:

  • Molecular weight (MW)
  • Lipophilicity (logP)
  • Number of hydrogen bond donors (HBD)
  • Number of hydrogen bond acceptors (HBA)
  • Polar surface area (PSA)
  • Number of rotatable bonds (ROTB)
  • Number of aromatic rings (AROM)
  • Count of alerts for undesirable substructures (ALERTS)

The QED is based on a method for multi-parameter optimisation known as ‘desirability functions’. A desirability function relates the value of a compound characteristic to the ‘desirability’ of that outcome. The desirability is a number between zero and one, where a value of one indicates that the outcome is ideal and a value of zero indicates that the outcome is completely unacceptable. Desirability functions are equivalent to the scoring functions used in StarDrop’s Probabilistic Scoring approach, making this approach very amenable to implementation in StarDrop.

 

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