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(+)-CPCA

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This is an old revision of this page, as edited by Nuklear (talk | contribs) at 10:43, 18 May 2007 (→Mixed Ant/Agonist Properties of Nocaine vs. Cocaine). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

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 fashion.

Mixed Ant/Agonist Properties of Nocaine vs. Cocaine

There has been good progress in developing drugs designed with the intent of treating cocaine addiction, although the exact identity of the agent for this still remains elusory (F. Vocci, et al. 2006),[2] even though RTI-336 has recently received a great deal of attention (F. Carroll, et al).[3] The propensity to relapse is arguably greatest during the early weeks of drug withdrawal (Kosten, et al. 1994). There is an urgent need to develop a substitute to aid chronic addicts in their withdrawal and/or abstinence from habitual drug use. The aim is development of a drug that does still produce some rewarding stimuli, although it should be only partially cocaine-like, otherwise it could turn-out to be highly abusable, which is a good excuse why no therapies are yet available. Certain characteristics are considered useful in the design protocol. Obviously, it must possess ↑ DAT affinity. Also, the onset to peak effects must be gradual and the duration-span needs to be appreciable, to lessen the probability of repeat-dosing, since this is a key contributory factor in the development of physical dependency, and also tolerance (S. Wee, et al. 2006).[4] The agent should cause moderate (but not excessive) enhancements in locomotor activity, and must not interfere with normal daily cycles like eating and sleeping, for example. In addition to this, the agent should have reasonable toxicology and agreeable side-effects, inorder to be well-tolerated. On a behavioral level, it may be pertinent to point out that certain substances have been linked to either suicidal or homocidal tendancies in vulnerable people. This is also a risk factor that is worth considering in the clinical trial stage of development.

The dopamine transporter has been suggested to be the initial target for cocaine in producing its reinforcing and addictive effects (Ritz, et al. 1987),[5] (Carroll, et al. 1992).[6] It is widely accepted that blockade of dopamine uptake by cocaine is the result of high-affinity binding of cocaine to the dopamine transporter (Reith, et al. 1986),[7] (Calligaro and Eldefrawi, 1987),[8] (Madras, et al. 1989).[9] The dopamine transporter (DAT) is a critical recognition site for cocaine and contributes to its significant abuse liability. Recent studies conducted on DAT knock-in mice have now definatively proven that the DA elevating actions of cocaine account for 100% of its reinforcing efficacy (R. Chen, et al. 2006).[10] More research may be needed though to elucidate if DA transporter occupancy is the sole mechanism accounting for DA elevating actions, infact presynaptic DA autoreceptors are also known to play a role (Qun Wu, et al. 2002).[11]

Conversely, SERT affinity actually lessens physical dependency, although there are a few reports suggesting that SSRI based drugs can lead to psychological dependency in certain individuals, it is still dubious to what extent this is actually widespread. (L. Howell, et al) E.g, RTI-112 is a nonselective PT analog with aprox equal in vitro SERT/DAT binding affinities, but this agent was only weakly self administered by monkeys though (K. Lindsey, et al. 2004),[12] (B. Ginsberg, et al. 2005).[13] Also, a number of studies where an SSRI or a serotonin agonist were administered in conjunction with cocaine or other DAT inhibitors were studied. Here, it was demonstrated that serotonin decreases the propensity for drug administration (P. Czoty, et al. 2001),[14] (L. Howell, et al. 2006/7).[15]

Some aromatic-isopropylamine based monamine releasers were recently prepared and their pharmacology tested (R. Rothman, et al. 2005),[16] (S. Negus, et al. 2006).[17] Although the serotonergic activity of these compounds dampens reinforcing efficacy, the study actually conveyed this property as a desirable feature. Presumably, this is because they were persuing treatments for chronic addicts, opposed to inexperienced users.

Thus, both the DAT and the SERT might need to be highly occupied, by the medication, inorder to elicit the full-spectrum of rewarding stimuli, without any of the problems associated with physical dependancy. The analogy for this is that if an artist is planning a painting, then it is likely that they are going to want to use all of the 1° colors, and not just the one that is corresponding to dopamine.

In order to simply the situation in an a priori sense, it was chosen first to explore piperidine-based cocaine analogs that showed catecholamine selectivity (A. Kozikowski, et al. 1998). Given the similarity and innovation of these analogs, comparing to PT based cocaine derivatives, steps were taken to explore their pharmacological activity (AP Kozikowski, et al. 2003),[18] (W. Woolverton, et al. 2002).[19]

Discussion

Like cocaine, SS and (+)-CPCA bind to the DAT and inhibit DA uptake, stimulate LMA in rodents and completely substitute for cocaine in 2D tests. Pretreatment with SS or (+)-CPCA enhances the cocaine discriminative stimulus in rats. However, the LMA effects of the piperidine based compounds are much less than those induced by cocaine. Pretreating mice with SS or (+)-CPCA does not increase cocaine induced convulsions in mice. Furthermore, pretreating mice with (+)-CPCA actually attenuated cocaine-induced locomotor stimulation. With regard to reinforcing effects, SS is 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, SS and cocaine had nearly identical break points in a PR self-administration test, whereas (+)-CPCA has a lower break point than either of these two drugs. These results suggest that there are clear-cut differences between cocaine and the present piperidine analogs. (+)-CPCA has behavioral pharmacological properties that might make it worth considering as a possible candidate for treating cocaine addiction.

Monoamine Reuptake Activity
Compound [3H]DA nM [3H]NE nM [3H]5HT nM
SS 67 ± 2498 ± 7390 ± 27
Cocaine275 ± 24119 ± 38177 ± 13
(+)-CPCA276 ± 3390 ± 55900 ± 400


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 SERT affinity between SS and (+)-CPCA might play a contributory role in accounting for the differences in the observed pharmacology. Catecholamine selective drugs, like TMP (threo methylphenidate), are reported to possess decent abuse potential though, so it is not easy to gauge why (+)-CPCA does not embody significant propensity for self-administration.

A possible explanation might be nocaine preferentially binds to the ↓-affinity DAT, in which case it would be expected to behave somewhat differently to cocaine.[20][21][22] Some sort of cholinergic effect might also be aversive. For example, muscarinic activity of benztropine analogs is well known to limit the reinforcing potential (Mu-Fa Zou, et al. 2006).[23] Ion-channel activity is another factor that can be used to explain certain differences in pharmacology.

It is possible that sigma receptor activity might also account for some of the differences between cocaine and these piperidine mimics (RR Matsumoto, et al. 2001,[24][25][26] 2003),[27] (Ping and Teruo, 2003 rev).[28] Sigma receptors are not specific to cocaine, other psychostimulants like methamphetamine (E. Nguyen, et al. 2005),[29] and phencyclidine are also linked to this neural target. An increased understanding of this receptor recently led to a novel AD being reported that is based around its pharmacology (Jiajia Wang, et al. 2007).[30]

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 DARI molecules.

3D-QSAR Methods

In the absence of knowledge of the 3D structure of the DAT, ligand-based 3D QSAR techniques like CoMFA and CoMSIA may be useful in identifying molecular features that improve activity (Cramer, et al. 1988) (G. Klebe, 1999).[31] These techniques require the use of a template conformer on which each 3D-QSAR model is based. For rigid molecules that can adopt only a limited no. conformations, selection of the template is rel. straightforward.

There is considerable evidence that many ligands dont bind to proteins in their vacuum phase GEM conformation (Perola and Charifson, 2004).[32] However, many pharmacophore models of DARI drugs are based around the GEM of the ligand, or very close to it (S. Kulkarni, et al. 2002),[33] (P. Benedetti, et al. 2002).[34] Other work has shown the necessity of considering conformations other than the GEM in pharmacophore modeling, esp. when modeling very flexible molecules (D. Bernard, et al. 2005).[35] For example, conformational analysis of TMP identified several local energy minimum conformers which closely match those of rigid TMP analog that has same DAT binding affinity as TMP (K. Gilbert, et al. 2004).[36] Since the rigid analog is assumed to contain the important pharmacophore elements in their binding orientation, this supports the notion that the GEM conformer need not be the bioactive conformer.

The present study uses multiple, low-energy, representative conformations as templates for 3D-QSAR studies. No assumption is made that the GEM conformer is the conformation a molecule must achieve in order to bind to a target. Although the bioactive conformer may be one of the representative conformers, computations alone cannot prove that point.

Since very flexible molecules can assume a continuum of closely related conformations, they present a challenge to the application of 3D-QSAR techniques. The present work uses the output of a hierarchial clustering study of molecular conformations to input to CoMFA and CoMSIA analyses (K. Gilbert, et al. 2006).[37] Hierarchial clustering was shown to give similar results to fuzzy relational clustering (M. Misra, et al. 2006),[38] and singular value decomposition studies of the same data set of conformations (A. Fiorentino, et al. 2006).[39] Conformational analysis was carried out, and hierarchial clustering was used to select representative conformers to use as templates in 3D-QSAR studies. These templates were chosen to be representative of the 3D space occupied by the analogs. Each representative conformer was used as the template upon which a set of 45 analogs was built, constructing a conformational family of analogs, each with a structure similar to that of the template conformer. CoMFA and CoMSIA techniques were then used to evaluate predictive models for each of the families.

DAT Arylpiperidine CoMFA Study

(Hongbin Yuan, et al. 2004)[40] http://dx.doi.org/10.1021/jm0303296 http://dx.doi.org/10.1016/j.bmc.2006.09.070
The MATs have been studied extensively as the targets for addiction therapy in the past decade.[41] 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,[42] and a prohibited conical region about 5.5–10Å distant from the 3α-substituted piperidine ring.[43] 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.[44] 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.[45] 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,[46] 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: Ester and Amine Modifications

A series of novel N- and 3α-modified Nocaine analogs were synthesized and tested for their SNDRI activity and behavioral properties in mice (Petukhov, et al. 2002).[47]

interaction with the mGlu5 receptor may be involved as well (Chiamulera, et al. 2001).[48]

The rational design of ligands with a predetermined potency at and selectivivity for DA/NE/5HT transporters is hindered by the lack of knowledge about the 3D structure (U. Gether, et al. 2001; N. Chen, et al. 2000). In cases where the 3D structure of the binding site in a target protein is not well defined, as is the case for the MATs, one can perform ligand-based design to develop a pharmacophore. That is, by studying the conformational properties of a series of pharmacologically similar compounds, one can form hypotheses regarding the pharmacophore (Mark Froimowitz, et al. 2007).[49] Most of the potent tropane-based inhibitors, inc. coca, are believed to have at least 3 major interactions with the transporter binding site: one ionic or H-bonding interaction at the basic nitrogen, one dipole-dipole or H-bonding interaction of the ester group, and an interaction of the aryl group with a lipophilic binding pocket. This model was successfully used for the design of a novel piperidine-based DAT inhibitor that is economically affordable to manufacture (Shaomeng Wang, et al. 2K).[50]

Although the in vivo metabolism of (+)-CPCA is also likely to involve N-demethylation, metabolism to the corresponding free acid, to give a compound inactive at all BMAs will probably be the predominant pathway in vivo. It was reasoned that metabolism via esterase action can be avoided by replacing the ester group with a bioisosteric group that is more stable to metabolic degradation. In previous studies, it was found that oxadiazole, although completely cocaine-like, exhibits a significantly longer duration of action, prolly due to slower rate of metabolism. In general, relative to the corresponding N-methyl compounds, the norpiperidines exhibited an increased activity at the SERT/NET and only modest changes at the DAT.

File:Oxadiazole.gif
(+)-CPCA N-demethyl and Ester Modified QSAR
Identification Marker DAT / NET / SERT Ki, nM Uptake Ratio
Tag R N [3H]DA [3H]SER [3H]NE NE ÷ DA SER ÷ DA SER ÷ NE
1aMeOCOMe233 ± 628490 ± 1430252 ± 43
1bH279 ± 98434 ± 507.9 ± 3.0
2aHOCH2Me497 ± 581550 ± 360198 ± 53
2bH836 ± 35239 ± 2869 ± 6
3aOxadiazoleMe187 ± 35960 ± 80256 ± 17
3bH189 ± 24373 ± 434 ± 6

Norester is 20 and 32 x more active, alcohol is 6.5 and 2.9 x more active, and oxadiazole is 16.0 and 7.5 xs more active in blocking the reuptake at the SERT and NET. The activity at the DAT of the norester is similar to the N-methyl ester. The DAT activity of the oxazdiazole is almost unchanged, whereas the activity of the alcohol drops ~40% upon N-demethylation.

Despite the fact that alcohol has only one electron donor atom in its 3α-substituent, it exhibits reuptake-blocking properties comparable to those of ester and oxadiazole compounds, with 2 and 3 electron donor atoms, respectively. Moreover, N-Me alcohol shows even 5.5 x higher activity at the SERT than the ester, while N-Me alcohol is 2.1 x less active at the DAT and 1.3 x more active at the NET. The fact that nor-alcohol also exhibits a 3-fold decrease in DAT activity, 1.8 fold increase in SERT activity, and a 8.7 fold decrease in NET activity compared to nor-ester indicates that the presence of an ester or an oxadiazole at the 3α position important for DAT reuptake blocks, whereas alcohol favor inhibiting reuptake SERT.

LMA tests in mice and 2D tests in rats were performed to explore pharmacology of these compounds.

Coca produced rapid and dose dependent enhancements in the dist traveled and stereotypic movements in mice. The duration of locomotor effex of coca lasted ~2 h at 30mg/kg. Although 2a is almost 2 x less potent at the DAT than cocaine, the parent compound 1a, and oxadiazole 3a, it produced significant and dose-dependent enhancements in the dist traveled and stereotypic movements. However the locomotor effex of 2a were relatively prolonged comparing to cocaine and lasted at least 2 h following 30-56 mg/kg doses of 2a. This may be due to its slower metabolism relative to cocaine, as 2a lacks an ester group and, thus, will not be subjected to rapid hydrolysis in vivo. The onset of action for 2a was relatively slower comparing to cocaine, esp. on stereotypic movements, which peaked about 90 min after injection.

In contrast to cocaine and alcohol 2a, norester 1b produced biphasic effex on LMA. There were initial and significant reductions in both dist traveled and stereotypic movements compared to the "vehicle control responses" 30 and 60 min following 10 and 30 mg/kg doses. Following these initial reductions, there were significant delayed enhancements in the dist traveled and stereotypic movements 90 and 120 min after the administration of 10 and 30 mg/kg doses of 1b. Doses of 1b greater than 30 mg/kg produced convulsions.

Cocaine produced dose-dependent and full substition for cocaine in cocaine-trained animals in a 2D test. Despite some differences in the locomotor effex of 2a and 1b, these compounds completely substituted for cocaine in the 2D test. The doses of cocaine, 2a, and 1b that produced 50% cocaine-appropriate lever responding were 3.48, 3.55, and 2.42 mg/kg, respectively. There were no significant differences in the rates of responding following cocaine injection and 1b. However both 1b and 2a, at high doses, produced either partial or complete supression of the responding in 3/10 and 4/12 animals.

An interesting difference between cocaine, ester 1a, alcohol 2a, and norester 1b is that the latter two compounds are substantially longer acting than cocaine in LMA tests. Although prolonged action is anticipated from compounds lacking the 3α ester group, like alcohol 2a and oxadiazole 3a, this is a surprising and intriguing fact for the norester 1b, because the 3α ester group should be equally susceptible to hydrolysis as the ester group of cocaine and 1a. Another interesting result of N-demethylation is the initial depressant action of 1b followed by delayed locomotor stimulation. Inc. GABA receptors might in-part, be responsible for this.

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.[51] It was no disappointment that a pair of NRIs were discovered in this study (John Musachio, et al).[52] It was no accident that the (3R,4S) isomer is eliciting +ve in vitro bioassay test results (Rong He, et al).[53] NRIs are important probes but they are not thought to function as robust or powerful reinforcers (Sunmee Wee, et al).[54]

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).[55] 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.

Reference

Pat Retrieval

[56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66]

References

  1. ^ [1]Alan P. Kozikowski, Gian Luca Araldi, John Boja, William M. Meil, Kenneth M. Johnson, Judith L. Flippen-Anderson, Clifford George, and Eddine Saiah J. Med. Chem.; 1998; 41(11) pp 1962 - 1969
  2. ^ [2]Medication Development for Addictive Disorders: The State of the Science. F. J. Vocci, J. Acri, and A. Elkashef (2005) Am J Psychiatry 162, 1432-1440
  3. ^ [3]Carroll FI, Howard JL, Howell LL, Fox BS, Kuhar MJ. Development of the Dopamine Transporter Selective RTI-336 as a Pharmacotherapy for Cocaine Abuse. AAPS Journal. 2006; 8(1): E196-E203. DOI: 10.1208/aapsj080124
  4. ^ [4]Neuropsychopharmacology (2006) 31, 351–362. doi:10.1038/sj.npp.1300795; published online 15 June 2005 Preclinical Research A Reduced Rate of In Vivo Dopamine Transporter Binding is Associated with Lower Relative Reinforcing Efficacy of Stimulants Sunmee Wee, F Ivy Carroll and William L Woolverton.
  5. ^ [5]Science 4 September 1987: Vol. 237. no. 4819, pp. 1219 - 1223 DOI: 10.1126/science.2820058
  6. ^ [6]Carroll, F. I., Lewin, A. H., Boja, J. W. and Kuhar, M. J.: Cocaine receptor: Biochemical characterization and structure-activity relationships of cocaine analogues at the dopamine transporter. J. Med. Chem. 35: 969-981, 1992
  7. ^ [7]Reith, M. E. A., Meisler, B. E., Sershen, H. and Lajtha, A.: Structural requirements for cocaine congeners to interact with dopamine and serotonin uptake sites in mouse brain and to induce stereotyped behavior. Biochem. Pharmacol. 35: 1123-1129, 1986
  8. ^ [8]Calligaro, D. O. and Eldefrawi, M. E.: High affinity stereospecific binding of [3H]cocaine in striatum and its relationship to the dopamine transporter. Membr. Biochem. 7: 87-106, 1987
  9. ^ [9]Madras, B. K., Spealman, R. D., Fahey, M. A., Neumeyer, J. L., Saha, J. K. and Milius, R. A.: Cocaine receptors labeled by [3H]2-carbomethoxy-3-(4-fluorophenyl)tropane. Mol. Pharmacol. 36: 518-524, 1989
  10. ^ [10]Abolished cocaine reward in mice with a cocaine-insensitive dopamine transporter. R. Chen, M. R. Tilley, H. Wei, F. Zhou, F.-M. Zhou, S. Ching, N. Quan, R. L. Stephens, E. R. Hill, T. Nottoli, D. D. Han, and H. H. Gu (2006) PNAS 103, 9333-9338
  11. ^ [11]The Journal of Neuroscience, July 15, 2002, 22(14):6272-6281 Concurrent Autoreceptor-Mediated Control of Dopamine Release and Uptake during Neurotransmission: An In Vivo Voltammetric Study Qun Wu, Maarten E. A. Reith, Q. David Walker, Cynthia M. Kuhn, F. Ivy Carroll, and Paul A. Garris.
  12. ^ [12]Journal of Pharmacology And Experimental Therapeutics Fast Forward First published on February 24, 2004; DOI: 10.1124/jpet.103.060293
  13. ^ [13]Interaction of cocaine and dopamine transporter inhibitors on behavior and neurochemistry in monkeys Pharmacology Biochemistry and Behavior, Volume 80, Issue 3, March 2005, Pages 481-491 Brett C. Ginsburg, Heather L. Kimmel, F. Ivy Carroll, Mark M. Goodman and Leonard L. Howell
  14. ^ [14]Paul W. Czoty, Brett C. Ginsburg, and Leonard L. Howell Serotonergic Attenuation of the Reinforcing and Neurochemical Effects of Cocaine in Squirrel Monkeys J. Pharmacol. Exp. Ther. 2002 300: 831-837.
  15. ^ [15]Effects of Combined Dopamine and Serotonin Transporter Inhibitors on Cocaine Self-Administration in Rhesus Monkeys. L. L. Howell, F. I. Carroll, J. R. Votaw, M. M. Goodman, and H. L. Kimmel (2007) J. Pharmacol. Exp. Ther. 320, 757-765
  16. ^ [16]J Pharmacol Exp Ther 2005 313: 1361-1369. Published online March 10, 2005; 10.1124/jpet.104.082503
  17. ^ [17]. S. S. Negus, N. K. Mello, B. E. Blough, M. H. Baumann, and R. B. Rothman Monoamine Releasers with Varying Selectivity for Dopamine/Norepinephrine versus Serotonin Release as Candidate "Agonist" Medications for Cocaine Dependence: Studies in Assays of Cocaine Discrimination and Cocaine Self-Administration in Rhesus Monkeys J. Pharmacol. Exp. Ther. 2007 320: 627-636.
  18. ^ [18]J. Pharmacol. Exp. Ther. 2003 305: 143-150. Nocaine
  19. ^ [19]W. L. Woolverton, R. Ranaldi, Z. Wang, G. A. Ordway, I. A. Paul, P. Petukhov, and A. Kozikowski Reinforcing Strength of a Novel Dopamine Transporter Ligand: Pharmacodynamic and Pharmacokinetic Mechanisms J. Pharmacol. Exp. Ther. 2002 303: 211-217.
  20. ^ [20]Lomenzo, S. A.; Rhoden, J. B.; Izenwasser, S.; Wade, D.; Kopajtic, T.; Katz, J. L.; Trudell, M. L. J. Med. Chem.; (Article); 2005; 48(5); 1336-1343.
  21. ^ [21]Bioorganic & Medicinal Chemistry Letters, Volume 9, Issue 23, 6 December 1999, Pages 3273-3276 Stacey A. Lomenzo, Sari Izenwasser, Robert M. Gerdes, Jonathan L. Katz, Theresa Kopajtic and Mark L. Trudell
  22. ^ [22]Bioorganic & Medicinal Chemistry Volume 13, Issue 19, 1 October 2005, Pages 5623-5634
  23. ^ [23]Structure-Activity Relationship Studies on a Novel Series of (S)-2-Substituted 3-[Bis(4-fluoro- or 4-chlorophenyl)methoxy]tropane Analogues for in Vivo Investigation Zou, M.-F.; Cao, J.; Kopajtic, T.; Desai, R. I.; Katz, J. L.; Newman, A. H.J. Med. Chem.; (Article); 2006; 49(21); 6391-6399.
  24. ^ [24]Rimcazole analogs attenuate the convulsive effects of cocaine: correlation with binding to σ-receptors rather than dopamine transporters Neuropharmacology, Volume 41, Issue 7, December 2001, Pages 878-886 Rae R. Matsumoto, Kizzy L. Hewett, Buddy Pouw, Wayne D. Bowen, Stephen M. Husbands, Jian Jing Cao and Amy Hauck Newman
  25. ^ [25]Conformationally restricted analogs of BD1008 and an antisense oligodeoxynucleotide targeting σ1 receptors produce anti-cocaine effects in mice European Journal of Pharmacology, Volume 419, Issues 2-3, 11 May 2001, Pages 163-174 Rae R. Matsumoto, Kari A. McCracken, Michele J. Friedman, Buddy Pouw, Brian R. De Costa and Wayne D. Bowen
  26. ^ [26]Involvement of sigma receptors in the behavioral effects of cocaine: evidence from novel ligands and antisense oligodeoxynucleotides Neuropharmacology, Volume 42, Issue 8, June 2002, Pages 1043-1055 Rae R. Matsumoto, Kari A. McCracken, Buddy Pouw, Ying Zhang and Wayne D. Bowen
  27. ^ [27]σ Receptors: potential medications development target for anti-cocaine agents European Journal of Pharmacology, Volume 469, Issues 1-3, 23 May 2003, Pages 1-12 Rae R. Matsumoto, Yun Liu, Megan Lerner, Eric W. Howard and Daniel J. Brackett
  28. ^ [28]Understanding the Molecular Mechanism of Sigma-1 Receptors: Towards A Hypothesis that Sigma-1 Receptors are Intracellular Amplifiers for Signal Transduction pp. 2073-2080(8) Authors: Su Tsung-Ping; Hayashi Teruo
  29. ^ [29]Involvement of sigma (σ) receptors in the acute actions of methamphetamine: Receptor binding and behavioral studies Neuropharmacology, Volume 49, Issue 5, October 2005, Pages 638-645 Emily C. Nguyen, Kari A. McCracken, Yun Liu, Buddy Pouw and Rae R. Matsumoto
  30. ^ [30]
  31. ^ [31]Comparative Molecular Similarity Index Analysis (CoMSIA) to study hydrogen-bonding properties and to score combinatorial libraries Journal Journal of Computer-Aided Molecular Design
  32. ^ [32]Conformational Analysis of Drug-Like Molecules Bound to Proteins: An Extensive Study of Ligand Reorganization upon Binding Perola, E.; Charifson, P. S. J. Med. Chem.; (Article); 2004; 47(10); 2499-2510.
  33. ^ [33]Three-Dimensional Quantitative Structure-Activity Relationships of Mazindol Analogues at the Dopamine Transporter Kulkarni, S. S.; Newman, A. H.; Houlihan, W. J. J. Med. Chem.; (Article); 2002; 45(19); 4119-4127.
  34. ^ [34]GBR Compounds and Mepyramines as Cocaine Abuse Therapeutics: Chemometric Studies on Selectivity Using Grid Independent Descriptors (GRIND) Benedetti, P.; Mannhold, R.; Cruciani, G.; Pastor, M. J. Med. Chem.; (Article); 2002; 45(8); 1577-1584.
  35. ^ [35]Conformationally Sampled Pharmacophore for Peptidic Opioid Ligands Bernard, D.; Coop, A.; MacKerell, A. D., Jr. J. Med. Chem.; (Article); 2005; 48(24); 7773-7780.
  36. ^ [36]Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods Journal Journal of Computer-Aided Molecular Design
  37. ^ [37]Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs Journal Journal of Computer-Aided Molecular Design
  38. ^ [38]Novel Feature Extraction Technique for Fuzzy Relational Clustering of a Flexible Dopamine Reuptake Inhibitor Milind Misra, Amit Banerjee, Rajesh N. Davé, and Carol A. Venanzi pp 610 - 623
  39. ^ [39]Singular value decomposition of torsional angles of analogs of the dopamine reuptake inhibitor GBR 12909 Journal of Computational Chemistry Volume 27, Issue 5, Date: 15 April 2006, Pages: 609-620 Anna Fiorentino, Deepangi Pandit, Kathleen M. Gilbert, Milind Misra, Rose Dios, Carol A. Venanzi
  40. ^ [40]Yuan, H.; Kozikowski, A. P.; Petukhov, P. A. J. Med. Chem.; (Article); 2004; 47(25); 6137-6143.
  41. ^ [41]Molecular Psychiatry (2002) 7, 21-26.
  42. ^ [42]J. Med. Chem.; (Article); 1998; 41(6); 864-876.
  43. ^ [43]SAR Studies of Piperidine-Based Analogues of Cocaine. Part 3: Oxadiazoles Bioorganic & Medicinal Chemistry Letters, Volume 11, Issue 16, 20 August 2001, Pages 2079-2083 Pavel A. Petukhov, Mei Zhang, Kenneth J. Johnson, Srihari R. Tella and Alan P. Kozikowski
  44. ^ [44]Pharmacological and Behavioral Analysis of the Effects of Some Bivalent Ligand-Based Monoamine Reuptake Inhibitors Tamiz, A. P.; Bandyopadhyay, B. C.; Zhang, J.; Flippen-Anderson, J. L.; Zhang, M.; Wang, C. Z.; Johnson, K. M.; Tella, S.; Kozikowski, A. P. J. Med. Chem.; (Article); 2001; 44(10); 1615-1622.
  45. ^ [45]Wang, S.; Sakamuri, S.; Enyedy, I. J.; Kozikowski, A. P.; Deschaux, O.; Bandyopadhyay, B. C.; Tella, S. R.; Zaman, W. A.; Johnson, K. M. J. Med. Chem.; (Expedited Article); 2000; 43(3); 351-360.
  46. ^ [46]J. Med. Chem.; (Article); 1998; 41(6); 864-876.
  47. ^ [47]Pavel A. Petukhov, Jianrong Zhang, Alan P. Kozikowski, Cheng Z. Wang, Yan Ping Ye, Kenneth M. Johnson, and Srihari R. Tella J. Med. Chem.; 2002; 45(15) pp 3161 - 3170
  48. ^ [48]Nature Neuroscience 4, 873 - 874 (2001) Published online: 13 August 2001; | doi:10.1038/nn0901-873 Reinforcing and locomotor stimulant effects of cocaine are absent in mGluR5 null mutant mice
  49. ^ [49]Froimowitz, M.; Gu, Y.; Dakin, L. A.; Nagafuji, P. M.; Kelley, C. J.; Parrish, D.; Deschamps, J. R.; Janowsky, A. J. Med. Chem.; (Article); 2007; 50(2); 219-232.
  50. ^ [50]Discovery of a Novel Dopamine Transporter Inhibitor, 4-Hydroxy-1-methyl-4-(4-methylphenyl)-3-piperidyl 4-Methylphenyl Ketone, as a Potential Cocaine Antagonist through 3D-Database Pharmacophore Searching. Molecular Modeling, Structure-Activity Relationships, and Behavioral Pharmacological Studies Wang, S.; Sakamuri, S.; Enyedy, I. J.; Kozikowski, A. P.; Deschaux, O.; Bandyopadhyay, B. C.; Tella, S. R.; Zaman, W. A.; Johnson, K. M. J. Med. Chem.
  51. ^ [51]J. Med. Chem.; (Letter); 2004; 47(24); 5821-5824. Zhou, J.; He, R.; Johnson, K. M.; Ye, Y.; Kozikowski, A. P.
  52. ^ [52] John L. Musachio, Jinsoo Hong, Masanori Ichise, Nicholas Seneca, Amira K. Brown, Jeih-San Liow, Christer Halldin, Robert B. Innis, Victor W. Pike, Rong He, Jia Zhou and Alan P. Kozikowski, Bioorganic & Medicinal Chemistry Letters Volume 16, Issue 12, 15 June 2006, Pages 3101-3104
  53. ^ [53]He, R.; Kurome, T.; Giberson, K. M.; Johnson, K. M.; Kozikowski, A. P. J. Med. Chem.; (Article); 2005; 48(25); 7970-7979.
  54. ^ [54]Drug and Alcohol Dependence Volume 82, Issue 2, 28 April 2006, Pages 151-157
  55. ^ [55]Amir P. Tamiz, Jianrong Zhang, Judith L. Flippen-Anderson, Mei Zhang, Kenneth M. Johnson, Olivier Deschaux, Srihari Tella, and Alan P. Kozikowski. J. Med. Chem.; 2000; 43(6) pp 1215 - 1222
  56. ^ DE1110159 Publication date: 1961-07-06 Improvements in or relating to Amino-Norcamphane compounds
  57. ^ United States Patent 3,813,404 Issue Date: May 28, 1974
  58. ^ Kozikowski; Alan P.; Araldi; Gian Luca, Analogs of cocaine, US6180648, 2001.
  59. ^ United States Patent 6,376,673 Moldt, et al.
  60. ^ Kozikowski; Alan P.; Araldi; Gian Luca, Analogs of cocaine, US6472422, 2002.
  61. ^ Kozikowski; Alan P.; Araldi; Gian Luca, Analogs of cocaine, US6806281, 2004.
  62. ^ Kozikowski; Alan P.; Araldi; Gian Luca, Analogs of cocaine, WO9845263, 1998
  63. ^ Kozikowski; Alan P.; Araldi; Gian Luca; Tamiz; Amir P., WO0020390, 2000.
  64. ^ WO2004039778 Date: 2004-05-13 Inventor: WAETJEN FRANK (DK) Applicant: NEUROSEARCH AS (DK); WAETJEN FRANK (DK)
  65. ^ KOZIKOWSKI ALAN P (US); ZHOU JIA (US), WO2005041875, 2005.
  66. ^ KOZIKOWSKI ALAN P (US); ZHOU JIA (US); EP1680113, 2006-07-19; UNIV GEORGETOWN (US)
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