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Dibenzazecine compounds with a novel dopamine/5HT2A receptor profile and 3D-QSAR analysis.

ABSTRACT: BACKGROUND: Antipsychotics are divided into typical and atypical compounds based on clinical efficacy and side effects. The purpose of this study was to characterize in vitro a series of novel azecine-type compounds at human dopamine D1-D5 and 5HT2A receptors and to assign them to different classes according to their dopamine/5HT2A receptor profile. RESULTS: Regardless of using affinity data (pKi values at D1-D5 and 5HT2A) or selectivity data (15 log (Ki ratios)), principal component analysis with azecine-type compounds, haloperidol, and clozapine revealed three groups of dopamine/5HT2A ligands: 1) haloperidol; 2) clozapine plus four azecine-type compounds; 3) two hydroxylated dibenzazecines. Reducing the number of Ki ratios used for principal component analysis from 15 to two (the D1/D2 and D2/5HT2A Ki ratios) obtained the same three groups of compounds. The most potent dibenzazecine clustering in the same group as clozapine was the non-hydroxylated LE410 which shows a slightly different D2-like receptor profile (D2L > D3 > D4.4) than clozapine (D4.4 > D2L > D3). The monohydroxylated dibenzacezine LE404 clusters in a separate group from clozapine/LE410 and from haloperidol and shows increased D1 selectivity. CONCLUSION: In conclusion, two compounds with a novel dopamine/5HT2A receptor profile, LE404 and LE410, with some differences in their respective D1/D2 receptor affinities including a validated pharmacophore-based 3D-QSAR model for D1 antagonists are presented.

SUBMITTER: Hamacher A

PROVIDER: S-EPMC1586004 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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Dibenzazecine compounds with a novel dopamine/5HT2A receptor profile and 3D-QSAR analysis.

Hamacher Alexandra A Weigt Mathias M Wiese Michael M Hoefgen Barbara B Lehmann Jochen J Kassack Matthias U MU

BMC pharmacology 20060915

<h4>Background</h4>Antipsychotics are divided into typical and atypical compounds based on clinical efficacy and side effects. The purpose of this study was to characterize in vitro a series of novel azecine-type compounds at human dopamine D1-D5 and 5HT2A receptors and to assign them to different classes according to their dopamine/5HT2A receptor profile.<h4>Results</h4>Regardless of using affinity data (pKi values at D1-D5 and 5HT2A) or selectivity data (15 log (Ki ratios)), principal componen ...[more]

PMID: 16978403

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Project description:Background: The dipeptide-alkylated nitrogen-mustard compound is a new kind of nitrogen-mustard derivative with a strong anti-tumor activity, which can be used as a potential anti-osteosarcoma chemotherapy drug. Objective: 2D- and 3D-QSAR (structure–activity relationship quantification) models were established to predict the anti-tumor activity of dipeptide-alkylated nitrogen-mustard compounds. Method: In this study, a linear model was established using a heuristic method (HM) and a non-linear model was established using the gene expression programming (GEP) algorithm, but there were more limitations in the 2D model, so a 3D-QSAR model was introduced and established through the CoMSIA method. Finally, a series of new dipeptide-alkylated nitrogen-mustard compounds were redesigned using the 3D-QSAR model; docking experiments were carried out on several compounds with the highest activity against tumors. Result: The 2D- and 3D-QSAR models obtained in this experiment were satisfactory. A linear model with six descriptors was obtained in this experiment using the HM through CODESSA software, where the descriptor “Min electroph react index for a C atom” has the greatest effect on the compound activity; a reliable non-linear model was obtained using the GEP algorithm model (the best model was generated in the 89th generation cycle, with a correlation coefficient of 0.95 and 0.87 for the training and test set, respectively, and a mean error of 0.02 and 0.06, respectively). Finally, 200 new compounds were designed by combining the contour plots of the CoMSIA model with each other, together with the descriptors in the 2D-QSAR, among which compound I1.10 had a high anti-tumor and docking ability. Conclusion: Through the model established in this study, the factors influencing the anti-tumor activity of dipeptide-alkylated nitrogen-thaliana compounds were revealed, providing direction and guidance for the further design of efficient chemotherapy drugs against osteosarcoma.

Dataset Information

Dibenzazecine compounds with a novel dopamine/5HT2A receptor profile and 3D-QSAR analysis.

Publications

Dibenzazecine compounds with a novel dopamine/5HT2A receptor profile and 3D-QSAR analysis.

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