Optimization of a Screening Hit toward M2912, an Oral Tankyrase Inhibitor with Antitumor Activity in Colorectal Cancer Models.

Constitutive activation of the canonical Wnt signaling pathway, in most cases driven by inactivation of the tumor suppressor APC, is a hallmark of colorectal cancer. Tankyrases are druggable key regulators in these malignancies and are considered as attractive targets for therapeutic interventions, although no inhibitor has been progressed to clinical development yet. We continued our efforts to develop tankyrase inhibitors targeting the nicotinamide pocket with suitable drug-like properties for investigating effects of Wnt pathway inhibition on tumor growth. Herein, the identification of a screening hit series and its optimization through scaffold hopping and SAR exploration is described. The systematic assessment delivered M2912, a compound with an optimal balance between excellent TNKS potency, exquisite PARP selectivity, and a predicted human PK compatible with once daily oral dosing. Modulation of cellular Wnt pathway activity and significant tumor growth inhibition was demonstrated with this compound in colorectal xenograft models in vivo.

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery.

BACKGROUND: The ability to supplement high-throughput metabolic clearance data with structural information defining the site of metabolism should allow design teams to streamline their synthetic decisions. However, broad application of metabolite identification in early drug discovery has been limited, largely due to the time required for data review and structural assignment. The advent of mass defect filtering and its application toward metabolite scouting paved the way for the development of software automation tools capable of rapidly identifying drug-related material in complex biological matrices. Two semi-automated commercial software applications, MetabolitePilot™ and Mass-MetaSite™, were evaluated to assess the relative speed and accuracy of structural assignments using data generated on a high-resolution MS platform. RESULTS/CONCLUSION: Review of these applications has demonstrated their utility in providing accurate results in a time-efficient manner, leading to acceleration of metabolite identification initiatives while highlighting the continued need for biotransformation expertise in the interpretation of more complex metabolic reactions.

Achieving conservation when opportunity costs are high: optimizing reserve design in Alberta's oil sands region.

Recent studies have shown that conservation gains can be achieved when the spatial distributions of biological benefits and economic costs are incorporated in the conservation planning process. Using Alberta, Canada, as a case study we apply these techniques in the context of coarse-filter reserve design. Because targets for ecosystem representation and other coarse-filter design elements are difficult to define objectively we use a trade-off analysis to systematically explore the relationship between conservation targets and economic opportunity costs. We use the Marxan conservation planning software to generate reserve designs at each level of conservation target to ensure that our quantification of conservation and economic outcomes represents the optimal allocation of resources in each case. Opportunity cost is most affected by the ecological representation target and this relationship is nonlinear. Although petroleum resources are present throughout most of Alberta, and include highly valuable oil sands deposits, our analysis indicates that over 30% of public lands could be protected while maintaining access to more than 97% of the value of the region's resources. Our case study demonstrates that optimal resource allocation can be usefully employed to support strategic decision making in the context of land-use planning, even when conservation targets are not well defined.