Development of autotaxin inhibitors: A series of zinc binding triazoles.

A series of inhibitors of Autotaxin (ATX) has been developed using the binding mode of known inhibitor, PF-8380, as a template. Replacement of the benzoxazolone with a triazole zinc-binding motif reduced crystallinity and improved solubility relative to PF-8380. Modification of the linker region removed hERG activity and led to compound 12 - a selective, high affinity, orally-bioavailable inhibitor of ATX. Compound 12 concentration-dependently inhibits autotaxin and formation of LPA in vivo, as shown in pharmacokinetic-pharmacodynamic experiments.

Optimization of Platelet-Derived Growth Factor Receptor (PDGFR) Inhibitors for Duration of Action, as an Inhaled Therapy for Lung Remodeling in Pulmonary Arterial Hypertension.

A series of potent PDGFR inhibitors has been identified. The series was optimized for duration of action in the lung. A novel kinase occupancy assay was used to directly measure target occupancy after i.t. dosing. Compound 25 shows 24 h occupancy of the PDGFR kinase domain, after a single i.t. dose and has efficacy at 0.03 mg/kg, in the rat moncrotaline model of pulmonary arterial hypertension. Examination of PK/PD data from the optimization effort has revealed in vitro:in vivo correlations which link duration of action in vivo with low permeability and high basicity and demonstrate that nonspecific binding to lung tissue increases with lipophilicity.

Efficient and facile synthesis of acrylamide libraries for protein-guided tethering.

A kinetic template-guided tethering (KTGT) strategy has been developed for the site-directed discovery of fragments that bind to defined protein surfaces, where acrylamide-modified fragments can be irreversibly captured in a protein-templated conjugate addition reaction. Herein, an efficient and facile method is reported for the preparation of acrylamide libraries from a diverse range of amine fragments using a solid-supported quaternary amine base.

The design and implementation of a generic lipopeptide scanning platform to enable the identification of 'locally acting' agonists for the apelin receptor.

This Letter describes methodology to enable the identification of tool or therapeutic lipopeptides which modulate the function of membrane bound proteins. The choice of lipopeptides as a chemotype is the amalgamation of multiple medicinal chemistry considerations including duration of action, low systemic exposure and access to intracellular components. The 'lipopeptide shuffle' has been applied here to the APJ receptor and has rapidly resulted in the discovery of a 33 nM APJ agonist hit from an initial 369 member lipopeptide synthetic array.

Development of isoform selective PI3-kinase inhibitors as pharmacological tools for elucidating the PI3K pathway.

Using a parallel synthesis approach to target a non-conserved region of the PI3K catalytic domain a pan-PI3K inhibitor 1 was elaborated to provide alpha, delta and gamma isoform selective Class I PI3K inhibitors 21, 24, 26 and 27. The compounds had good cellular activity and were selective against protein kinases and other members of the PI3K superfamily including mTOR and DNA-PK.

Evolutionary computational methods to predict oral bioavailability QSPRs.

This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico.