Crystal structures of hFPPS in complex with novel anticancer drug leads
Bibliographic record
Abstract
Human farnesyl pyrophosphate synthase (hFPPS) produces farnesyl pyrophosphate, an isoprenoid required for a variety of essential cellular processes. Inhibition of hFPPS has been well established as the mechanism of action of the nitrogen-containing bisphosphonate (N-BP) drugs, currently best known for their anti-bone resorptive effects. Recent investigations indicate that hFPPS inhibition also produces potent anticancer effects both in vitro and vivo: N-BPs inhibit proliferation, motility, and viability of tumor cells, and act in synergy with other anticancer agents [1,2]. However, the physicochemical properties of the current N-BP drugs seriously compromise their full anticancer potential in non-skeletal tissues. They show poor membrane permeability and extreme affinity to bone, due mainly to their highly charged bisphosphonate moiety, which mimics the pyrophosphate of the substrates of hFPPS. Both the substrates and N-BPs bind to hFPPS via Mg ion-mediated interactions between their pyrophosphate/bisphosphonate moiety and two aspartate-rich surfaces of the enzyme's active site cavity. Recently, we took a structure-guided approach to develop bisphosphonates with higher lipophilicity for enhanced uptake into non-skeletal tissues. Surprisingly, some of the new compounds were found to bind to hFPPS even in the absence of Mg ions. Crystal structures of hFPPS in complex with a representative compound revealed that this bisphosphonate binds to the enzyme's active site in the presence of Mg ions, but also to a nearby allosteric inhibitory site in their absence. Furthermore, removal of a phosphonate group from the bisphosphonate moiety of this compound resulted in an inhibitor that binds exclusively to the allosteric site. Based on the crystal structures with these lead compounds, we generated of a novel class of non-bisphosphonate, allosteric inhibitors of hFPPS with superior physicochemical properties than those of the current N-BP drugs for broader tissue distribution.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".