Background and Purpose Transmembrane Cav2.2 (N-type) voltage-gated calcium channels are genetically and pharmacologically validated pain targets. Clinical block of Cav2.2 (e.g., with Prialt) or indirect modulation (e.g., with gabapentinoids) mitigates chronic pain but is constrained by side effects. The cytosolic auxiliary subunit collapsin response mediator protein 2 (CRMP2) targets Cav2.2 to the sensory neuron membrane and regulates their function. A CRMP2-derived peptide (CBD3) uncouples the Cav2.2-CRMP2 interaction to inhibit calcium influx, transmitter release and pain. Homology-guided mutagenesis of CBD3 revealed an antinociceptive core at A1RSR4. Here, the A1R2 CBD3 dipeptide was identified as critical for Cav2.2 molecular recognition and served as a scaffold for identification of small molecule peptidomimetic allosteric regulators of Cav2.2. Experimental Approach We developed and applied a novel molecular dynamics approach to identify the Cav2.2 recognition motif of the core CBD3 peptide as the A1R2 dipeptide and used its presenting motif to design pharmacophore models to screen 27 million compounds in the open access server ZincPharmer. Of 200 curated hits, 77 compounds were assessed using depolarization‐evoked calcium influx in rat dorsal root ganglion (DRG) neurons. Nine compounds were tested using electrophysiology and one compound (CBD3063) was evaluated biochemically, electrophysiologically, and behaviorally effects in a model of experimental pain: Key Results CBD3063 reduced membrane Cav2.2 expression and currents, inhibited neuronal excitability, uncoupled the Cav2.2-CRMP2 interaction, and reversed mechanical allodynia in rats with spared nerve injury. Conclusions and Implications These results identify CBD3063, as a selective, first-in-class, CRMP2-based peptidomimetic, which allosterically regulates Cav2.2 to achieve analgesia.

Molecular shape is an important concept in drug design and virtual screening. Shape similarity typically uses either alignment methods, which dynamically optimize molecular poses with respect to the query molecular shape, or feature vector methods, which are computationally less demanding but less accurate. The computational cost of alignment can be reduced by pre-aligning shapes, as is done with the Volumetric-Aligned Molecular Shapes (VAMS) method. Here we introduce and evaluate Fragment Oriented Molecular Shapes (FOMS), where shapes are aligned based on molecular fragments. FOMS enables the use of _shape constraints_, a novel method for precisely specifying molecular shape queries that provides the ability to perform partial shape matching and supports search algorithms that function on an interactive time scale. When evaluated using the challenging Maximum Unbiased Validation dataset, shape constraints were able to extract significantly enriched subsets of compounds for the majority of targets, and FOMS matched or exceeded the performance of both VAMS and an optimizing alignment method of shape similarity search.