Pentazocine Lactate

There currently are no medications proven to be effective for the treatment of stimulant-use disorder (SUD). Sigma-receptor (σR) antagonists block many effects of stimulant drugs but not the reinforcing effects assessed with self-administration in rats. However, a recent study suggests that σR antagonism combined with a dopamine (DA) transporter (DAT) blockade selectively attenuates stimulant self-administration. A compound with potential for dual DAT/σR inhibition, CM699, was synthesized and had the necessary ex vivo affinities of 311 and 14.1 nM at DAT and σ₁Rs, respectively. CM699 inhibited DA uptake ex vivo. Antagonist effects at σ₁Rs by CM699 were confirmed with a recently reported pharmacological assay: CM699 increased, whereas the σ₁R agonist, (+)-pentazocine, decreased σ₁R multimers detected in nondenaturing protein gels, and CM699 blocked the effects of (+)-pentazocine. CM699 after intravenous administration (5.0 mg/kg) in rats had an elimination half-life of 4.4 h. In rats, CM699 after intraperitoneal administration blunted the stimulatory effects of cocaine on DA levels in the nucleus accumbens and insurmountably blocked cocaine self-administration, indicating efficacy as a cocaine antagonist in vivo. When given alone, CM699 was not self-administered nor had significant effects on nucleus accumbens DA, suggesting minimal, if any, abuse potential. Further, in a biochemical assay designed to probe the conformation of DAT, (+)-pentazocine potentiated cocaine-induced cysteine accessibility of DAT transmembrane domain 6a, suggesting a shift in the conformational equilibrium of DAT toward outward-facing, whereas CM699 blocked this effect. The results provide preclinical proof of concept for dual DAT/σR inhibition as a novel DAT-conformational approach for the development of medications to treat SUD.

Retention of molecules on immobilized artificial membrane (IAM) chromatography is a key physicochemical property for predictive models of permeability across biological barriers, with applications in drug design and ecotoxicology. Currently, IAM retention is solely experimentally determined, which limits its utility for screening virtual compound libraries or for predictions of yet not synthesized molecules. The present study focuses on developing predictive models of IAM retention factors (logk_w(IAM)) for a structurally diverse set of drug compounds, scrutinizing the role of lipophilicity, experimental and calculated, as well as the contribution of additional molecular parameters, selected from a pool of physicochemical, constitutional, topological and 3D descriptors. After obtaining a data overview by principal component analysis, both multiple linear regression (MLR) and partial least squares (PLS) analyses were used to construct lipophilicity-based models and lipophilicity-independent models. Bulk, polarity and fraction of anionic species were common descriptors in all models. It was demonstrated that calculated lipophilicity values introduced additional uncertainty, depending on the software used. On the other hand, lipophilicity-independent MLR and PLS models, which relied solely on computational descriptors, showed comparable performance with lipophilicity-based models, while offering the advantage to more useful for screening large libraries in early drug discovery. The reliability of lipophilicity-independent MLR and PLS models was assessed by external validation as well as by using a blind test set. Error distribution between lipophilicity-based and lipophilicity-independent models was also investigated and found to be comparable, while it was better than the differences between experimental and calculated lipophilicity values.