The molecular mechanism of nitrogen-containing bisphosphonates as antiosteoporosis drugs
Bibliographic record
Abstract
Osteoporosis and low bone mass are currently estimated to be a major public health risk affecting >50% of the female population over the age of 50. Because of their bone-selective pharmacokinetics, nitrogen-containing bisphosphonates (N-BPs), currently used as clinical inhibitors of bone-resorption diseases, target osteoclast farnesyl pyrophosphate synthase (FPPS) and inhibit protein prenylation. FPPS, a key branchpoint of the mevalonate pathway, catalyzes the successive condensation of isopentenyl pyrophosphate with dimethylallyl pyrophosphate and geranyl pyrophosphate. To understand the molecular events involved in inhibition of FPPS by N-BPs, we used protein crystallography, enzyme kinetics, and isothermal titration calorimetry. We report here high-resolution x-ray structures of the human enzyme in complexes with risedronate and zoledronate, two of the leading N-BPs in clinical use. These agents bind to the dimethylallyl/geranyl pyrophosphate ligand pocket and induce a conformational change. The interactions of the N-BP cyclic nitrogen with Thr-201 and Lys-200 suggest that these inhibitors achieve potency by positioning their nitrogen in the proposed carbocation-binding site. Kinetic analyses reveal that inhibition is competitive with geranyl pyrophosphate and is of a slow, tight binding character, indicating that isomerization of an initial enzyme-inhibitor complex occurs with inhibitor binding. Isothermal titration calorimetry indicates that binding of N-BPs to the apoenzyme is entropy-driven, presumably through desolvation entropy effects. These experiments reveal the molecular binding characteristics of an important pharmacological target and provide a route for further optimization of these important drugs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".