Using a staged multi-objective optimization approach to find selective pharmacophore models
Using a staged multi-objective optimization approach to find selective pharmacophore models
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DOI：
10.1007/s10822-008-9227-2
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发表时间：
2009-11-01
影响因子：
3.5
通讯作者：
Abrahamian, Edmond
中科院分区：
文献类型：
--
作者：
Clark, Robert D.;Abrahamian, Edmond
在进行基于配体的药物设计时，往往很难有效地区分相关的G蛋白偶联受体及其亚型。Galahad使用多目标评分系统来生成多个比对，涉及相互冲突的愿望之间的替代权衡，以最大限度地减少内部压力，同时最大化配体之间的药效和立体(药形)一致性。通过检查，获得的各种覆盖物可以与不同的亚型相关，即使可用的配体不能完全区分受体，也没有使用任何特异性信息来偏向比对过程。这使得Galahad成为识别区分模型的一个潜在的强大工具，如这里使用的一组多巴胺能激动剂所示，这些激动剂的d1和d2受体选择性不同。
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.