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Using a staged multi-objective optimization approach to find selective pharmacophore models

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Abstract

It is often difficult to differentiate effectively between related G-protein coupled receptors and their subtypes when doing ligand-based drug design. GALAHAD uses a multi-objective scoring system to generate multiple alignments involving alternative trade-offs between the conflicting desires to minimize internal strain while maximizing pharmacophoric and steric (pharmacomorphic) concordance between ligands. The various overlays obtained can be associated with different subtypes by examination, even when the ligands available do not discriminate completely between receptors and when no specificity information has been used to bias the alignment process. This makes GALAHAD a potentially powerful tool for identifying discriminating models, as is illustrated here using a set of dopaminergic agonists that vary in their D1 vs. D2 receptor selectivity.

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Notes

  1. Just as for bitmaps, the count vector is actually created and manipulated in compressed form.

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Acknowledgment

The suggestions provided by anonymous reviewers contributed significantly to the clarity and readability of this paper, and the authors appreciate their thoughtful criticisms.

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Authors and Affiliations

  1. Tripos International, 1699 South Hanley Road, Saint Louis, MO, 63144, USA

    Robert D. Clark & Edmond Abrahamian

  2. Biochemical Infometrics, PO Box 411431, Creve Coeur, MO, 63141, USA

    Robert D. Clark

Authors
  1. Robert D. Clark
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  2. Edmond Abrahamian
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Correspondence to Robert D. Clark.

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Clark, R.D., Abrahamian, E. Using a staged multi-objective optimization approach to find selective pharmacophore models. J Comput Aided Mol Des 23, 765–771 (2009). https://doi.org/10.1007/s10822-008-9227-2

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