Antagonists of the human CCR5 receptor as anti-HIV-1 agents. Part 1: Discovery and initial structure–activity relationships for 1-amino-2-phenyl-4-(piperidin-1-yl)butanes

Dorn, Conrad P.; Finke, Paul E.; Oates, Bryan; Budhu, Richard J.; Mills, Sander G.; MacCoss, Malcolm; Malkowitz, Lorraine; Springer, Martin S.; Daugherty, Bruce L.; Gould, Sandra L.; DeMartino, Julie A.; Siciliano, Salvatore; Carella, Anthony; Carver, Gwen; Holmes, Karen; Danzeisen, Renee; Hazuda, Daria; Kessler, Joseph; Lineberger, Janet; Miller, Michael D.; Schleif, William A.; Emini, Emilio A.

doi:10.1016/s0960-894x(00)00637-5

Cited by 88 publications

(38 citation statements)

References 27 publications

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“…Thus, chemokine receptor antagonists could prove to be useful therapeutics in treating these and other inflammatory diseases. Based on these considerations, there has been a veritable explosion of activity to discover potent, selective, clinically useful chemokine receptor antagonists (Dhanak et al, 2001a,b;Dorn et al, 2001;Finke et al, 2001a,b,c;Forbes et al, 2000;Horuk et al, 2001;Ichiyama et al, 2003;Widdowson et al, 2004), and this has generated more than 250 patent applications and nine human clinical trials (Horuk, 2003).…”

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confidence: 99%

Identification and Characterization of a Potent, Selective Nonpeptide Agonist of the CC Chemokine Receptor CCR8

et al. 2005

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In this study, we report the first example of a nonpeptide chemokine receptor agonist, 2-{2-[4-(3-phenoxybenzyl)piperazin-1-yl]ethoxy}ethanol (ZK 756326), for the CC chemokine receptor CCR8. ZK 756326 inhibited the binding of the CCR8 ligand I-309 (CCL1), with an IC 50 value of 1.8 M. Furthermore, ZK 756326 was a full agonist of CCR8, dose-responsively eliciting an increase in intracellular calcium and cross-desensitizing the response of the receptor to CCL1. In addition, ZK 756326 stimulated extracellular acidification in cells expressing human CCR8. The ability of ZK 756326 to induce a response was receptor-specific and mediated through G␣ i , because it could be blocked by treatment with pertussis toxin. The CCR8 agonist activated cells expressing murine CCR8, eliciting their chemotaxis and inducing phosphorylation of extracellular signal-regulated kinase ERK1/2.

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confidence: 99%

Identification and Characterization of a Potent, Selective Nonpeptide Agonist of the CC Chemokine Receptor CCR8

et al. 2005

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“…There were total 154 piperidine derivatives in the source papers [22][23][24][25]. 35 compounds were excluded from our study due to lack of exact numerical activity values and infrequent occurrence of particular structural features.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, 119 compounds were selected in our study which are shown in Tables I to IV. In cases of racemic compounds (Tables I and II), only S configuration has been considered for modeling because the R isomers are less potent [22,23].…”

Section: Methodsmentioning

confidence: 99%

Predictive QSAR modeling of CCR5 antagonist piperidine derivatives using chemometric tools

Roy

Mandal

2008

Journal of Enzyme Inhibition and Medicinal Chemistry

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Quantitative structure-activity relationship (QSAR) studies have been performed on piperidine derivatives (n ¼ 119) as CCR5 antagonists. The whole data set was divided into a training set (75% of the dataset) and a test set (remaining 25%) on the basis of K-means clustering technique. Models developed from the training set were used to assess the predictive potential of the models using test set compounds. Initially classical type QSAR models were developed using structural, spatial, electronic, physicochemical and/or topological parameters using statistical methods like stepwise regression, partial least squares (PLS) and factor analysis followed by multiple linear regression (FA-MLR). Using topological and structural parameters, FA-MLR provided the best equation based on internal validation (Q 2 ¼ 0.514) but the best externally validated model was obtained with PLS (R 2 pred ¼ 0.565). When structural, physicochemical, spatial and electronic descriptors were used, the best Q 2 value (0.562) was obtained from the stepwise regression derived model whereas the best R 2 pred value (0.571) came from the PLS model. When topological descriptors were used in combination with the structural, physicochemical, spatial and electronic descriptors, the best Q 2 and R 2 pred values obtained were 0.530 (stepwise regression) and 0.580 (PLS) respectively. Attempt was made to develop 3D-QSAR models using molecular shape analysis descriptors in combination with structural, physicochemical, spatial and electronic parameters. Linear models were developed using genetic function algorithm coupled with multiple linear regression. However, the results from the 3D-QSAR study were not superior to those of the classical QSAR models. Finally, artificial neural network was employed for development of nonlinear models. The ANN models showed acceptable values of squared correlation coefficient for the observed and predicted values of the test set compounds. From the view point of external predictability, selected ANN models were superior to the linear QSAR models. All reported models satisfy the criteria of external validation as recommended by Golbraikh and Tropsha (J Mol Graphics Mod 2002; 20: 269 -276), whereas the majority of the models have modified r 2 (r 2 m ) value of the test set for external validation more than 0.5 as suggested by Roy and Roy (QSAR Comb Sci 2008; 27: 302-313).

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“…When DIBAL-H was used as the reduction reagent in toluene, the desired product (2) was obtained in 77% separation yield, 19 in contrast to the unsuccessful reaction in THF. Our explanation of this result is that the activity of the electrophilic reduction reagent DIBAL-H in toluene is higher than that in the comparatively more polar solvent THF.…”

Section: 16mentioning

confidence: 99%

“…that were developed into the antagonists illustrated in Figure 2. [17][18][19][20][21] Anibamine also has structural similarities to these compounds, in particular a potentially charged nitrogenic central moiety with two or more hydrophobic side chains attached. However, because of its structural novelty, we cannot dismiss the possibility that anibamine may possess a different binding modality than that proposed for the other CCR5 antagonists.…”

Section: Acknowledgmentmentioning

confidence: 99%

Anibamine and its Analogues as Novel Anti-Prostate Cancer Agents

Zhang¹

2009

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Antagonists of the human CCR5 receptor as anti-HIV-1 agents. Part 1: Discovery and initial structure–activity relationships for 1-amino-2-phenyl-4-(piperidin-1-yl)butanes

Cited by 88 publications

References 27 publications

Identification and Characterization of a Potent, Selective Nonpeptide Agonist of the CC Chemokine Receptor CCR8

Identification and Characterization of a Potent, Selective Nonpeptide Agonist of the CC Chemokine Receptor CCR8

Predictive QSAR modeling of CCR5 antagonist piperidine derivatives using chemometric tools

Anibamine and its Analogues as Novel Anti-Prostate Cancer Agents

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