(+)-CPCA

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File:Nocaine.png

Nocaine was first reported in 1998 in the guise of a cocaine mimic.[1] Infact, phenylpiperidine derives from the same article in which phenyltropane was first discovered, but it was essentially impotent in tests conducted on mice. The (3R,4S) isomer of nocaine only manages to elicit weakly reinforcing effects, although it is several-fold less dangerous than cocaine. On this basis, it is hypothesized that nocaine might be a good substitute type of agent with potential uses in cocaine addiction therapy. Clearly, these compounds dont contain the necessary tropane 2C–linker, required to deliver high intensity ambulatory counts, although they are still able to interact with the BMA transporters in an inhibitory manner.

Mixed Ant/Agonist Properties of Nocaine vs. Cocaine

(Alan P. Kozikowski, et al. 2003)[2]
Developing an effective treatment for cocaine addiction continues to be a difficult task (Kosten, et al. 1989). The susceptibility to relapse to cocaine abuse is particularly high during the early weeks of drug withdrawal (Kosten, et al. 1994). There is an immediate need to develop a pharmacotherapeutic agent that will assist during this critical withdrawal stage. One approach that is widely being persued is to develop a compound that partially mimics or reduces the effects of cocaine with minimal abuse liability on its own. Such a compound presumably would help to retain addicts in the treatment program during the vulnerable withdrawal stage.

The behavioral and reinforcing effects of cocaine are thought to be mainly due to its inhibitory effect on DA transporters. There is some evidence suggesting the possible involvement of additional pharmacodynamic mechanisms in cocaines actions (Volkow, et al. 1999).[3] In this context, SERT dependent effects might play some kind of role in cocaine addiction (Belzung, et al. 2000).[4] Furthermore, serotonergic drugs have been shown to modulate DA transmission in the brain (Benloucif, et al. 1993). Thus, both of the DAT and the SERT might need to be 'highly occupied', inorder to elicit the full pharmacological actions of cocaine. Although there is conflicting evidence suggesting an aversive role of serotonin in cocaine reinforcement, it was reasoned that a cocaine analog with high affinity for the DAT, but a relatively low affinity for the SERT would be only partially cocaine-like. In light of this, several piperidine-cocaine analogs with relatively weak SERT affinity were synthesized (Kozikowski, et al. 1998); These molecules are truncated versions of RTI-31. Given their similarity and innovation compared with cocaine analogs, es wurde betrachtet 'worth-while' to explore their pharmacological activity.

Discussion

There are similarities as well as subtle, but important differences between the pharmacology of cocaine and these piperidine analogs. Like cocaine, (+)-CPCA and its isomer (–)-cis-CPCA bind to the DAT and inhibit DA uptake, stimulate LMA in rodents and completely substitute for cocaine in 2D tests. Pretreatment with either (+)-CPCA or (–)-cis-CPCA enhances discriminative stimulus effects of cocaine in rats. However, the maximal LMA effects of (+)-CPCA or (–)-cis-CPCA are much less than for cocaine. Interestingly, pretreatment of mice with with either (+)-CPCA or (–)-cis-CPCA, unlike cocaine, do not produce an addititive effect on cocaine induced convulsions in mice. Furthermore, pretreatment of mice with (+)-CPCA attenuates cocaine-induced locomotor stimulation. With regard to reinforcing effects, (–)-cis-CPCA seems to be similar to cocaine as revealed by their nearly identical inverted U-shaped dose-response curves in fixed-ratio self-administration tests in rats. (+)-CPCA, however, has a flat dose-response curve in fixed-ratio self-administration tests. Similarly, cocaine and (–)-cis-CPCA have nearly identical break points in progressive ratio self-administration test, whereas (+)-CPCA has a lower break point than either of these two drugs. These results suggest that there are subtle but distinct differences between cocaine and the present piperidine analogs. (+)-CPCA has behavioral pharmacological properties suggestive that it may be a suitable candidate for treating cocaine addiction.

The mechanism underlying the observed behavioral similarities and differences between (+)-CPCA versus (–)-cis-CPCA and cocaine may relate to their pharmacodynamic differences. DAT binding and subsequent increased synaptic mesolimbic DA is thought to be the main mechanism underlying the reinforcing and other behavioral effects of cocaine (Ritz, et al. 1987), although serotonin systems are thought to play some kind of 'modulatory role'.[5] (–)-cis-CPCA is pharmacologically quite similar to cocaine, although it displays stronger DAT binding. (+)-CPCA is much less potent at the SERT than the other two compounds. "This suggests that the degree of inhibition of 5-HT transport may account for some of the differences between these two piperidine isomers" (c.f. Lomenzo, et al. wrt. ↑/↓ [±] DAT binding pockets).

Monoamine Reuptake Activity
Compound [3H]DA nM [3H]NE nM [3H]5HT nM
Cocaine275 ± 24119 ± 38177 ± 13
(+)-CPCA276 ± 3390 ± 55900 ± 400
(–)-cis-CPCA67 ± 2498 ± 7390 ± 27

Discussion

Although recent reports indicate the possible critical 5-HT involvement in cocaines behavioral and reinforcing effects, the precise mechanism is unclear. The generally lower efficacy of (+)-CPCA in locomotor and methamphetamine discrimination tests could result from the differential selectivity of the two isomers for the DAT relative to the SERT. That is, if serotonin receptor activation is requisite for maximal efficacy, the difference in affinities for the SERT exhibited by (+)-CPCA and (–)-cis-CPCA may be so large that 5HT transport is little affected at the doses tested. This difference in SERT affinity could also play a role in the suppression of response rates by doses of (+)-CPCA that engender cocaine-lever pressing. This rate effect, as well as that of partial generalization, has been attributed to incomplete coincidence of state produced by the training stimulus and test drug (Koek, et al. 1993). This interpretation supports the notion that (+)-CPCA is similar, but nonidentical to cocaine and methamphetamine. On the other hand, the ability of both piperidine isomers to potentiate the discriminability of a low dose of cocaine could be a consequence of their ability to inhibit DA and NE reuptake, because both NE- and DA-selective uptake inhibitors have been shown to potentiate cocaine discrimination (Kleven and Koek, 1998).

Vanoxerine is a ↑ affinity, ↓ potency inhibitor of DAT that blunts cocaines effects in a variety of paradigms (Rothman and Glowa, 1995). It is unconvincing that lack of SERT affinity is can be thought to lessen 'abuse potential', methylphenidate for example is a good totally synthetic laboratory approximation for cocaine if it is watered down with a local anesthetic. The lipophilicity and slow onset kinetics will help in accounting for the limited abuse potential of Vanoxerine (c.f. methadone vs. IV fentanyl). However, the "antagonistic" properties are better accounted for on the basis of the high discrimination-ratio of this compound (H.M. Deutsch, et al).<><><><> (+)-CPCA apparently also has a slower rate of DAT occupancy in the first few minutes after administration than does cocaine (Woolverton, et al. 2002).[6] Like I already said above, it is hypothesized trans-nocaine is undesirable because it is a '↓-type' ov DAT binder.<><><><>

In addition to the above-mentioned considerations, it is possible that some other unknown pharmacodynamic properties may be critical for the unique behavioral profile of these agents (σ-receptors). The ability of (+)-CPCA to antagonize cocaine-induced increase LMA in mice is not easily explained. It is also possible that this is not true pharmacological antagonism. Although it is conceivable that the apparent pharmacological differences between (+)-CPCA and cocaine are related to pharmacokinetic differences, it seems unlikely that they are due simply to differences in their duration of action, because the effects of high doses of both compounds seemed to have similar durations of action after i.p. administration. On the other side, there were apparent differences in time of peak effect that may play some role. The lack of seizure induction of nocaine agents vs. cocaine is also an interesting observation consistent with a possible lack of sigma receptor activity of the piperidine-based analogs (RR. Matsumoto, et al. 2001[7][8][9] 2003)[10] (Ping and Teruo, 2003 rev).[11] For example, sigma receptors not only cocaine, methamphetamine (E. Nguyen, et al. 2005),[12] and PCP also involve. Novel AD suggested recently on sigma receptor design platform (Jiajia Wang, et al. 2007).[13]

Although the self-administration data in rats suggest that this analog has limited reinforcing effects, studies in cocaine-experienced rhesus monkeys as assessed using a standard substitution procedure suggested that (+)-CPCA has dose-dependent reinforcing effects. However, this procedure is not designed to compare the relative reinforcing efficacy of cocaine and other reinforcing drugs (Balster, 1991). Even weak stimulants such as modafinil and ephedrine show reinforcing effects under essentially identical conditions as these (Gold and Balster, 1996). Mild reinforcing effects may be desirable in facilitating medication compliance and treatment acceptability. Human testing will be required to determine whether the abuse potential of (+)-CPCA is compatible with its therapeutic use in cocaine addiction.

In summary, (+)-CPCA has lower potency and efficacy than than cocaine in increasing LMA in rodents. (+)-CPCA only manages to produce partial methamphetamine-like discriminative stimulus effects, although it is fully cocaine-like in cocaine-trained animals. (+)-CPCA has lower reinforcing potential than cocaine as assessed by fixed and progressive ratio IV self-administration tests in rats, with its reinforcing effects confirmed by rhesus monkeys. Furthermore, (+)-CPCA dose dependently antagonizes cocaine-induced LMA and potentiates the discriminative stimulus effects of a low dose of cocaine. (+)-CPCA, unlike cocaine, does not enhance cocaine-induced convulsions. These results suggest that (+)-CPCA completely mimics certain behavioral actions of cocaine, whereas acting like a weak partial agonist in others, inc. its ability to attenuate cocaine-induced increase in LMA and to serve as a +ve reinforcing agent in rodents. Thus, (+)-CPCA may have potential utility in the treatment of cocaine addiction, and also offer valuable pharmacological info., furthering our understanding of cocaines mechanism of action, because it exhibits fundamental differences from other related DARIs.

DAT Arylpiperidine CoMFA Study

(Hongbin Yuan, et al. 2004)[14]
The MATs have been studied extensively as the targets for addiction therapy in the past decade.[15] It has been shown that cocaine and other abused drugs have the ability to bind to the MATs. Substantial evidence suggest that the DAT is the key target for psychostimulants in the CNS even though the mechanisms that mediate the addictive character of cocaine are more complex.

A generally recognized pharmacophore model for cocaine and PT's comprises two electrostatic interactions of the basic nitrogen and the ester group of the C-2 substituent, and one hydrophobic interaction of the C-3 aryl group. This model has been disputed because of the finding that in certain compounds neither the basic N nor the ester group was necessary for high binding affinity and inhibition of MAR. Instead, a hydrophobic pocket was proposed to exist in the vicinity of the C-2 carbon. On the contrary, Crippen et al. reported that the C-2 substituent did not have a significant effect on the binding activity of cocaine analogs. Carroll et al., however, provided further evidence for an electrostatic interaction at the C-2β-position in a later study.

Other models proposed for the DAT binding site include a linear fashion binding pocket for the 3β-substituted PT analogs,[16] and a prohibited conical region about 5.5–10Å distant from the 3α-substituted piperidine ring.<> Noticeably, high potency at the DAT of dimeric piperidine-based esters and amides suggested that the flexible linker combining the two piperidine units was able to adjust its orientation and to avoid unfavorable interactions with the binding site.<> All these lines of evidence suggest that the DAT binding site is much more complicated than the proposed pharmacophore models.

In an attempt to uncover the details of the DAT binding site, a number of 3D-QSAR studies were performed. Several QSAR/CoMFA studies focused on PTs concluded that an increased negative electrostatic potential in the regions around the 3β-substituent of the tropane ring and the para-poition of the phenyl ring favored high potency in inhibiting the MATs. Recent studies of aryltropanes and piperidinols suggested that the DAT and SERT have a large cavity that can accomodate bulky C-2 substituents of tropanes,<> and the size of the substituents at the para-position in both phenyl rings of piperidinols is important for inhibition of DA reuptake.[17] Wright et al. studied the role of the 3β-substituent of tropanes in binding to the DAT and blocking DA reuptake. Their CoMFA model indicated that the 3β-substituent binding site is barrel-shaped and hydrophobic interactions make a dominant contribution to the binding,[18] which is consistent with the studies of 3α-substituted tropane analogs reported by Newman et al. Newman and co-authors also studied N-substituted tropanes and concluded that the steric interaction of the N-substituent with the DAT is a principle factor for the binding affinity.

Results and Discussion

The discovery of active conformers and structure alignment are two critical steps in CoMFA modeling, especially for flexible compounds such as 3α-substituted piperidine-based analogues of cocaine. The advantage of using feature alignment approaches comparing to scaffold superposition based on the RMS fitting, which is commonly used in CoMFA modelling, is that they provide an effective way to align flexible and diverse compounds.

Since GASP can effectively generate pharmacophore models only for a limited number of ligands, three ligands were chosen based on the following three criteria: First, a representative molecule should be DAT-active; 2nd, it should have meaningful functional groups, which could be used in pharmacophore search; and 3rd, the 3α-substituents of these molecules should be relatively rigid with only a few rotatable bonds, thus limiting the number of distinct models obtained for further evaluation by CoMFA modeling. A total of 8 pharmacophore models were generated by GASP based on these three compounds. For each pharmacophore model, all compounds from the C1, C2, and C3 series were superimposed onto (2i) using the flexible superposition algorithm FlexS. The initial CoMFA models were constructed using the top-ranked conformers of the ligands in the training set for all pharmacophore models.

Summary of Statistics and Field Contributions for Models 1 and 2
model 1model 2
initialoptimizedinitialoptimized
no. of training compounds36363636
no. of test compounds6666
optimal no. of components4636
q2.515.828.296.849
standard error of prediction.599.369.71.346
r2.900.997.837.993
standard error of estimate.271.051.342.074
F values70.11462.354.8688.8
probability of r2=00000
steric.472.621.498.493
electrostatic.526.379.502.507

Among all of the eight initial CoMFA models, only one had a cross-validated coefficient q2 above 0.5, and the second-best model had a q2 value of 0.296. The pharmacophore A differs from B by the location of the H-bond donor site. In pharmacophore A, DS_1 is on the same side of the piperidine ring as the H-bond acceptor site whereas in pharmacophore B, DS_1 is located on the opposite side of AS_1. Both pharmacophore models have a lipophilic site corresponding to the centroid of the p-chlorophenyl ring.

One possiblity for the low predictivity of the CoMFA models is that these pharmacophores, which were derived from the three representative structures 1p, 2i, and 3c by GASP, were not suitable for all molecules. On the other hand, it is also possible that the top conformers of the training compounds found by FlexS, which were initially utilized for CoMFA modeling, did not ideally fit the pharmacophore model and hence produced large deviations between the observed and predicted biological data. Assuming that the latter problem was more likely to cause the low predictivity of the initial CoMFA models, an additional refinement of the structure alignment was performed. In the two best CoMFA models 1 and 2, the top conformer identified by FlexS was replaced with different conformers for each compound, and the overall superposition of all training compounds was re-evaluated repeatedly until the final CoMFA model with high accuracy and predictive power was achieved.

The electrostatic maps show that there is one positive charge favorable area located close to the first atom of the 3α-substituent in model 1, whereas model 2 has two smaller +ve charge favorable areas on both sides of the 3α-substituent. Negatively charged 3α-substituents near these areas would produce a –ve effect on affinity. It is consistent with the result that the carboxylic acids in the C2 and C3 series are more active than the C1 carboxylate acid, assuming that the carboxyl groups are –vely charged under physiological conditions. For the same reason, compounds in the C1 series may, in general, be less potent than compounds in the C2 and C3 series, as the former compounds are closer to these –vely charged areas in the DAT than the functional groups in the C2 and C3 ligands. Both models 1 and 2 display several electron density favorable regions around the 3α-substituent spanning from its third to sixth atoms; which may suggest that the DAT in this area has several H-bond donor sites rather than the only one depicted in the pharmacophore A and B. Generally, the binding affinity can be increased by introducing electron-rich atoms in this area. This is consistent with the observation that the N-monosubstituted amides exhibit only moderate potency, whereas disubsituted amide exhibits 12–58 x higher activity.

Both CoMFA models have a large steric favorable area in which bulky groups increase binding affinity. In both models these areas are located opposite to the corresponding H-bond donor site in pharmacopores A and B. The presence of the steric favorable area close to the piperidine ring in model 1 may be one of the reasons why tropane-based ligands are generally more active than piperidine-based compounds, as the additional 2-carbon bridge in tropane-based ligands would be positioned close to this sterically favorable area.

Conclusions

A successful strategy of pharmacophore-based alignment of the fittest conformers was designed and applied to determine the details of DAT binding site in proximity of the 3α-substituent of the piperidine-based analogues of cocaine. Two highly predictive and statistically significant CoMFA models were constructed. Both CoMFA models suggest that steric and electrostatic interactions play important roles in DAT binding of the 3α-substituent of the piperidine-based ligands. The fact that two distinct models were obtained indicates that the 3α-substituent may adopt multiple binding modes. Overall, these findings provide guidance for the design and improvement of compounds with DAt activity.

Nocaine: Sulfur Appendage

File:Snocaine.gif

The carboxymethyl locus of (d)-(3R,4S) Nocaine was used to generate a cluster of new side-chains, each imbuing various different shapes and sizes etcetera. One such example is a rigorously functionalized thioalkyl chain. The (eugeroic) "wakefulness promoting agent" modafinil was used as a punitative lead to fuel these compounds discovery, although it turns out that the SAR of the pharmacophoric elements are infact, only fleetingly related to one another.[19] It was no disappointment that a pair of NRIs were discovered in this study (John Musachio, et al).[20] It was no accident that the (3R,4S) isomer is eliciting +ve in vitro bioassay test results (Rong He, et al).[21] NRIs are important probes but they are not thought to function as robust or powerful reinforcers (Sunmee Wee, et al).[22]

MAT Binding Properties of Snocaine Compounds
Identification Marker NET / DAT / SERT IC50, nM (Ki, nM) IC50 Ratio
D X Y [3H]Norepinephrine [3H]Dopamine [3H]Serotonin DA/NE SER/DA SER/NA
MeEsterOMe25 ± 680 ± 23208 ± 473.22.68.32
H.56 ± .0951 ± 1613 ± 391.07.254923.21
MeAmideHNH39 ± 5159 ± 19557 ± 1504.0773.50314.28
H10 ± .1114 ± 32170 ± 611.41.49117
MeHNOH15 ± 285 ± 19227 ± 75.6672.67115.13
HNMe25 ± 213 ± 3110 ± 45.528.4624.4
MeNMe27 ± 7116 ± 4688 ± 224.296.75863.259
isopropyl-NH.8 ± .11.0 ± .21.1 ± .41.251.11.375
pyrrolidino.68 ± .2583 ± 14.5 ± .8122.1.054226.618
ReducedOH.94 ± .2716 ± 5158 ± 517.029.875168.1
OMe6 ± 250 ± 15191 ± 578.3333.8231.83
OAc3.6 ± 1.535 ± 1157 ± 189.7221.62315.83
OBz4.5 ± 1.268 ± 226.7 ± 1.515.11.098531.489

However, more focus has been tuned in to the ligand that has low nanomolar affinity at all three monoamine transporters, the first broadcasted piperidine compound developed to show such potent "triple reuptake inhibition".

Triple Monoamine QSAR

Based upon the results reported in the tropane series, it became desirable to modify the aryl-arecoline nucleus in ways that were predicted to improve SERT affinity, and also maintain/strengthen DAT/NET binding (Amir Tamiz, Jianrong Zhang).[23] A series of Nocaine analogs were tested for their ability to inhibit the high affinity synaptic re/uptake of tritium radiolabelled biogenic monoamines, at DA/NE/5HT neurotransporters. The uptake data and selectivity profiles of these compounds are listed in the table. The 3-(2-naphthyl) 2-CO2Me compound is related to RTI-318. The p-allyl compound is a piperidine based mimic of RTI-301. It is depicted as the terminal alkene, although it should be emphasized that the olefin will internalize upon exposure to light. Then there are two isomers, each with a different code.

Tritiated Monoamine Radiotracer Nocaine Triple QSAR
Identification Marker SERT / DAT / NET IC50, nM (Ki, nM) IC50 ÷ Ki IC50 Ratio
Config X N [3H]Serotonin [3H]Dopamine [3H]Noradrenaline SER DA NE DA/5HT NE/5HT NE/DA
SSp-VinylMe155 ± 3.9 (138 ± 3.5)144 ± 20 (131 ± 18)204 ± 5.6 (175 ± 4.8)1.1231.0991.1660.94931.2681.336
SSp-EthylMe275 ± 39 (255 ± 37)>1800 (>1700)>1300 (>1100)1.0781.0591.182>6.667>4.3140.6471
SSp-AllylMe334 ± 48 (309 ± 44)>1000 (964 ± 100)>1200 (>1000)1.081>1.0371.23.120>3.2361.037
SSp-EthynylMe189 ± 37 (175 ± 34)213 ± 30 (187 ± 26)399 ± 12 (364 ± 9.2)1.0801.1391.0961.0692.0801.947
SSp-PhenylMe67 ± 4.5 (62 ± 4.1)184 ± 30 (173 ± 26)239 ± 42 (203 ± 36)1.0811.0641.1772.7903.2741.173
SS2-NaphthylMe8.2 ± 0.3 (7.6 ± 0.2)23 ± 1.0 (21 ± 0.9)n.d. (34 ± 0.8)1.0791.0952.7634.4741.619
(3R,4S)2-NaphthylMe46 ± 4.4 (42 ± 4.0)>1000 (947 ± 135)n.d. (241 ± 1.7)1.095>1.05622.555.7380.2545
RR2-NaphthylMe209 ± 17 (192 ± 16)94 ± 9.6 (87 ± 8.9)n.d. (27 ± 1.6)1.0891.0800.45310.14060.3103
(3S,4R)2-NaphthylMe13 ± 0.7 (12 ± 0.7)293 ± 6.4 (271 ± 5.9)n.d. (38 ± 4.0)1.083 1.08122.583.1670.140
(3S,4R)2-NaphthylH2Cl3.9 ± 0.5 (3.5 ± 0.5)97 ± 8.6 (90 ± 8.0)34 ± 2.5 (30 ± 2.3)1.1141.0781.13325.718.5710.3333
β±1-NaphthylMe113 ± 4.3 (101 ± 3.8)326 ± 1.2 (304 ± 1.1)337 ± 37 (281 ± 30)1.119 1.0721.1993.0102.7820.9243
All data are mean values ± range or SEM of 2–5 separate experiments each conducted with 6 drug concentrations in triplicate.

http://www.unmc.edu/Pharmacology/receptortutorial/competition/analysis_sample4.htm

The vinyl compound was picked to represent this series of compounds in LMA studies. Both cocaine and the vinyl compound stimulated LMA. However, cocaine is ~2.5 x more potent in increasing the distance traveled. In contrast, the vinyl compound is about ~2.4 x more potent in enhancing stereotypic movements. Both cocaine and vinyl-Nocaine had a similar time-course on locomotor effects, which was ~2 h.

External links

Pat Retrieval

[24] [25] [26] [27] [28] [29] [30] [31] [32] [33]

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