A generalized model and high throughput data analysis system for functional modulation of receptor-agonist systems suitable for use in drug discovery.

Positive allosteric modulators (PAMs) of receptors represent a class of pharmacologic agents having the desirable property of acting only in the presence of cognate ligands. Discovery and optimization of the structure activity relationships of PAMs is complicated by the requirement of a second ligand to manifest their action, and by the need to quantify both affinity and intrinsic efficacy. Multivariate regression analysis is a statistical method capable of simultaneously obtaining affinity and intrinsic efficacy parameters from curve fits of multiple agonist dose-response functions generated in the presence of varying concentrations of PAMs. Capitalizing on the advantages of multivariate regression analysis for PAM optimization requires a theoretical framework and a system that facilitates efficient flow of information from data generation through data analysis, storage, and retrieval. We describe here the experimental design, mathematical model and informatics workflow enabling a multivariate regression approach for rapidly obtaining affinity and intrinsic efficacy values for PAMs in a drug discovery setting.

The T1R2/T1R3 sweet receptor and TRPM5 ion channel taste targets with therapeutic potential.

Taste signaling is a critical determinant of ingestive behaviors and thereby linked to obesity and related metabolic dysfunctions. Recent evidence of taste signaling pathways in the gut suggests the link to be more direct, raising the possibility that taste receptor systems could be regarded as therapeutic targets. T1R2/T1R3, the G protein coupled receptor that mediates sweet taste, and the TRPM5 ion channel have been the focus of discovery programs seeking novel compounds that could be useful in modifying taste. We review in this chapter the hypothesis of gastrointestinal taste signaling and discuss the potential for T1R2/T1R3 and TRPM5 as targets of therapeutic intervention in obesity and diabetes. Critical to the development of a drug discovery program is the creation of libraries that enhance the likelihood of identifying novel compounds that modulate the target of interest. We advocate a computer-based chemoinformatic approach for assembling natural and synthetic compound libraries as well as for supporting optimization of structure activity relationships. Strategies for discovering modulators of T1R2/T1R3 and TRPM5 using methods of chemoinformatics are presented herein.

Triphenylphosphine oxide is a potent and selective inhibitor of the transient receptor potential melastatin-5 ion channel.

Transient receptor potential melastatin-5 (TRPM5) is a calcium-gated monovalent cation channel expressed in highly specialized cells of the taste bud and gastrointestinal tract, as well as in pancreatic ß-cells. Well established as a critical signaling protein for G protein-coupled receptor-mediated taste pathways, TRPM5 also has recently been implicated as a regulator of incretin and insulin secretion. To date, no inhibitors of practical use have been described that could facilitate investigation of TRPM5 functions in taste or secretion of metabolic hormones. Using recombinant TRPM5-expressing cells in a fluorescence imaging plate reader-based membrane potential assay, we identified triphenylphosphine oxide (TPPO) as a selective and potent inhibitor of TRPM5. TPPO inhibited both human (IC50 = 12 µM) and murine TRPM5 (IC50 = 30 µM) heterologously expressed in HEK293 cells, but had no effect (up to 100 µM) on the membrane potential responses of TRPA1, TRPV1, or TRPM4b. TPPO also inhibited a calcium-gated TRPM5-dependent conductance in taste cells isolated from the tongues of transgenic TRPM5(+/)⁻ mice. In contrast, TPP had no effect on TRPM5 responses, indicating a strict requirement of the oxygen atom for activity. Sixteen additional TPPO derivatives also inhibited TRPM5 but none more potently than TPPO. Structure-activity relationship of tested compounds was used for molecular modeling-based analysis to clarify the positive and negative structural contributions to the potency of TPPO and its derivatives. TPPO is the most potent TRPM5 inhibitor described to date and is the first demonstrated to exhibit selectivity over other channels.

In silico design and synthesis of piperazine-1-pyrrolidine-2,5-dione scaffold-based novel malic enzyme inhibitors.

Fragment-based virtual library design and virtual screening have been conducted against malic enzyme (ME) homology model. Several scaffolds have been identified as promising motifs to target ME's NADP binding site. One small focused library has been synthesized and tested against ME. Several compounds from this library have shown sub-micromolar inhibitory activity against malic enzyme.

OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space.

Products from combinatorial libraries generally share a common core structure that can be exploited to improve the efficiency of virtual high-throughput screening (vHTS). In general, it is more efficient to find a method that scales with the total number of reagents (Sigma growth) rather with the number of products (Pi growth). The OptiDock methodology described herein entails selecting a diverse but representative subset of compounds that span the structural space encompassed by the full library. These compounds are docked individually using the FlexX program (Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. J. Mol. Biol. 1995, 251, 470-489) to define distinct docking modes in terms of reference placements for combinatorial core atoms. Thereafter, substituents in R-cores (consisting of the core structure substituted at a single variation site) are docked, keeping the core atoms fixed at the coordinates dictated by each reference placement. Interaction energies are calculated for each docked R-core with respect to the target protein, and energies for whole compounds are calculated by finding the reference core placement for which the sum of corresponding R-core energies is most negative. The use of diverse whole compounds to define binding modes is a key advantage of the protocol over other combinatorial docking programs. As a result, OptiDock returns better-scoring conformers than does serially applied FlexX. OptiDock is also better able to find a viable docked pose for each library member than are other combinatorial approaches.