Toward the Structural Characterization of the Gabapentin Binding site
Bibliographic record
Abstract
Gabapentinoids are prescription drugs used to relieve neuropathic pain, epilepsy and anxiety. One member of this family, gabapentin has been shown to bind with nanomolar affinity to the Ca V α2δ subunit of pre‐synaptic voltage‐gated calcium channels. We undertook a study to characterize the structural determinants of the gabapentin binding site on the extracellular N‐terminal domain of Ca V α2δ. The nucleotide sequence of a domain of 246 residues, including the putative binding site, was inserted in a pET28 vector. The protein, expressed in BL21(DE3) bacteria, was found to be mostly located in inclusion bodies and had to be solubilized in 8 M urea. Primary sequence of the purified protein was confirmed by MALDI mass spectrometry and protein refolding was promoted by removing urea through overnight dialysis. The recovery of the native‐like structure was validated using size exclusion chromatography, circular dichroism, and small‐angle X‐ray scattering. The protein was found to be stable at 4 ° C for 2 weeks. Interaction between the 246‐residue domain (2 µM) and gabapentin (2 µM, 20 µM and 40 µM) was examined using differential scanning fluorimetry. Preliminary data show that gabapentin does not significantly affect the stability of this domain. We have nonetheless undertaken crystallization trials with and without gabapentin to obtain a high‐resolution 3D structure of this domain. Other structural domains of Ca V α2 are concurrently in the process of purification using similar approaches. Altogether our studies will ultimately shed light on the molecular mechanism underlying the effect of gabapentin in pain management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".