Human isoprenoid synthase enzymes as therapeutic targets
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the human body, the complex biochemical network known as the mevalonate pathway is responsible for the biosynthesis of all isoprenoids, which consists of a vast array of metabolites that are vital for proper cellular functions. Two key isoprenoids, farnesyl pyrophosphate (FPP) and geranylgeranyl pyrophosphate (GGPP) are responsible for the post-translational prenylation of small GTP-binding proteins, and serve as the biosynthetic precursors to numerous other biomolecules. The down-stream metabolite of FPP and GGPP is squalene, the precursor to steroids, bile acids, lipoproteins, and vitamin D. In the past, interest in prenyl synthase inhibitors focused mainly on the role of the FPP in lytic bone diseases. More recently pre-clinical and clinical studies have strongly implicated high levels of protein prenylation in a plethora of human diseases, including non-skeletal cancers, the progression of neurodegenerative diseases and cardiovascular diseases. In this review, we focus mainly on the potential therapeutic value of down-regulating the biosynthesis of FPP, GGPP, and squalene. We summarize the most recent drug discovery efforts and the structural data available that support the current on-going studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it