Oral administration of VDAC1-derived small molecule peptides increases circulating testosterone levels in male rats
Bibliographic record
Abstract
Cholesterol is the precursor of all steroid hormones, and the entry of cholesterol into the mitochondria is the rate-limiting step of steroidogenesis. Voltage-dependent anion channel (VDAC1) is an outer mitochondrial protein part of a multiprotein complex that imports cholesterol. We previously reported that intratesticular administration of a 25 amino acid peptide blocking the interaction between 14-3-3ϵ with VDAC1 increased circulating levels of testosterone. This fusion peptide was composed of a HIV-1 transactivator of transcription (TAT) protein transduction domain cell-penetrating peptide, a glycine linker, and amino acids 159-172 of VDAC1 (TV159-172). Here, we describe the development of a family of small molecules that increase circulating testosterone levels after an oral administration. We first characterized an animal model where TV159-172 was delivered subcutaneously. This subcutaneous model allowed us to study the interactions between TV159-172 and the hypothalamus-pituitary-gonadal axis (HPG) and identify the biologically active core of TV159-172. The core consisted of the tetrapeptide RVTQ, which we used as a platform to design synthetic peptide derivatives that can be administered orally. We developed a second animal model to test various derivatives of RVTQ and found 11 active compounds. Dose-response experiments identified 4 synthetic peptides that robustly increased androgen levels in a specific manner. We selected RdVTQ as the leading VDAC1-core derivative and profiled the response across the lifespan of Brown-Norway rats. In summary, we present the development of a new class of therapeutics that act within the HPG axis to increase testosterone levels specifically. This new class of small molecules self-regulates, preventing abuse.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".