Using a staged multi-objective optimization approach to find selective pharmacophore models.
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.
Clark
Robert D
RD
Tripos International, Saint Louis, MO 63144, USA. bclark@bcmetrics.com
Abrahamian
Edmond
E
D000465:Algorithms; D019295:Computational Biology; D004298:Dopamine / Q000737:chemistry* / Q000378:metabolism*; D015195:Drug Design; D006801:Humans; D008958:Models, Molecular; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000378:metabolism*; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D017447:Receptors, Dopamine D1 / Q000737:chemistry*; D017448:Receptors, Dopamine D2 / Q000737:chemistry*
D004364:Pharmaceutical Preparations; D017447:Receptors, Dopamine D1; D017448:Receptors, Dopamine D2; D004298:Dopamine