Discovery and Optimization of Selective Nav1.8 Modulator Series That Demonstrate Efficacy in Preclinical Models of Pain.

Voltage-gated sodium channels, in particular Nav1.8, can be targeted for the treatment of neuropathic and inflammatory pain. Herein, we described the optimization of Nav1.8 modulator series to deliver subtype selective, state, and use-dependent chemical matter that is efficacious in preclinical models of neuropathic and inflammatory pain.

Optimisation of a novel series of selective CNS penetrant CB(2) agonists.

A series of benzimidazole CB(2) receptor agonists were prepared and their properties investigated. Optimisation of the three benzimidazole substituents led to the identification of compound 23, a potent CB(2) full agonist (EC(50) 2.7nM) with excellent selectivity over the CB(1) receptor (>3000-fold). Compound 23 demonstrated good CNS penetration in rat. Further optimisation led to the identification of compound 34 with improved selectivity over hERG and excellent CNS penetration in rat.

Structural pairwise comparisons of HLM stability of phenyl derivatives: Introduction of the Pfizer metabolism index (PMI) and metabolism-lipophilicity efficiency (MLE).

Data mining by pairwise comparison of over 150,000 human liver microsome (HLM) intrinsic clearance values stored within the internal Pfizer database has been performed by an automated tool. Systematic probability tables of specific structural changes on the intrinsic clearance of phenyl derivatives have been generated. From these data two new parameters, the Pfizer Metabolism Index (PMI) and Metabolism-Lipophilicity Efficiency (MLE) are introduced for each fragment. The findings are applied to a Topliss style analysis that focuses on metabolic stability.

A novel series of highly selective inhibitors of MMP-3.

The design and synthesis of a series of highly selective hydroxamate inhibitors of stromelysin-1 (MMP-3) is described. Substitution of a 4-biaryl piperidine sulfonamide core, which binds at the S1' subsite of MMP-3, was optimised to give potent inhibitors of MMP-3, with greater than 300-fold selectivity over MMP-1, MMP-2, MMP-9 and MMP-14. Compounds 26 and 27 were identified as having the best balance of pharmacology and properties required for topical drug delivery.

Predicting penetration across the blood-brain barrier from simple descriptors and fragmentation schemes.

The ability to cross the blood brain barrier (BBB), sometimes expressed as BBB+ and BBB-, is a very important property in drug design. Several computational methods have been employed for the prediction of BBB-penetrating (BBB+) and nonpenetrating (BBB-) compounds with overall accuracies from 75 to 97%. However, most of these models use a large number of descriptors (67-199), and it is not easy to implement the models in order to predict values of BBB+/-. In this work, 19 simple molecular descriptors calculated from Algorithm Builder and fragmentation schemes were used for the analysis of 1593 BBB+/- data. The results show that hydrogen-bonding properties of compounds play a very important role in modeling BBB penetration. Several BBB models based on hydrogen-bonding properties, such as Abraham descriptors, polar surface area (PSA), and number of hydrogen bonding donors and acceptors, have been built using binomial-PLS analysis. The results show that the overall classification accuracy for a training set is over 90%, and overall prediction accuracy for a test set is over 95%.