CoMFA-Based Prediction of Agonist Affinities at Recombinant Wild Type versus Serine to Alanine Point Mutated D2 Dopamine Receptors

Agonist affinity changes dramatically as a result of serine to alanine mutations (S193A, S194A, and S197A) within the fifth transmembrane region of D2 dopamine receptors and other receptors for monoamine neurotransmitters. However, agonist 2D-structure does not predict which drugs will be sensitive...

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Veröffentlicht in:Journal of medicinal chemistry 2000-08, Vol.43 (16), p.3005-3019
Hauptverfasser: Wilcox, Richard E, Huang, Wen-Hsin, Brusniak, Mi-Youn Kim, Wilcox, David M, Pearlman, Robert S, Teeter, Martha M, DuRand, Curtiss J, Wiens, Brenda L, Neve, Kim A
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Sprache:eng
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Zusammenfassung:Agonist affinity changes dramatically as a result of serine to alanine mutations (S193A, S194A, and S197A) within the fifth transmembrane region of D2 dopamine receptors and other receptors for monoamine neurotransmitters. However, agonist 2D-structure does not predict which drugs will be sensitive to which point mutations. Modeling drug−receptor interactions at the 3D level offers considerably more promise in this regard. In particular, a comparison of the same test set of agonists across receptors differing minimally (point mutations) offers promise to enhance the understanding of the structural bases for drug−receptor interactions. We have previously shown that comparative molecular field analysis (CoMFA) can be applied to comparisons of affinity at recombinant D1 and D2 dopamine receptors for the same set of agonists, a differential QSAR. Here, we predicted agonist K L for the same set of agonists at wild type D2 vs S193A, S194A, and S197A receptors using CoMFA. Each model used bromocriptine as the template. ln(1/K L) values for the low-affinity agonist binding conformation at recombinant wild type and mutant D2 dopamine receptors stably expressed in C6 glioma cells were used as the target property for the CoMFA of the 16 aligned agonist structures. The resulting CoMFA models yielded cross-validated R 2 (q 2) values ranging from 0.835 to 0.864 and simple R 2 values ranging from 0.999 to 1.000. Predictions of test compound affinities at WT and each mutant receptor were close to measured affinity values. This finding confirmed the predictive ability of the models and their differences from one another. The results strongly support the idea that CoMFA models of the same training set of compounds applied to WT vs mutant receptors can accurately predict differences in drug affinity at each. Furthermore, in a “proof of principle”, two different templates were used to derive the CoMFA model for the WT and S193A mutant receptors. Pergolide was chosen as an alternate template because it showed a significant increase in affinity as a result of the S193A mutation. In this instance both the bromocriptine- and pergolide-based CoMFA models were similar to one another but different from those for the WT receptor using bromocriptine- or pergolide- as templates. The pergolide-based S193A model was more strikingly different from that of the WT receptor than was the bromocriptine-based S193A model. This suggests that a “dual-template” approach to differential CoMFA may h
ISSN:0022-2623
1520-4804
DOI:10.1021/jm990526y