Comparative Study of a Decadentate Acyclic Chelate, HOPO-O<sub>10</sub>, and Its Octadentate Analogue, HOPO-O<sub>8</sub>, for Radiopharmaceutical Applications
Bibliographic record
Abstract
Radiolanthanides and actinides are aptly suited for the diagnosis and treatment of cancer via nuclear medicine because they possess unique chemical and physical properties (e.g., radioactive decay emissions). These rare radiometals have recently shown the potential to selectively deliver a radiation payload to cancer cells. However, their clinical success is highly dependent on finding a suitable ligand for stable chelation and conjugation to a disease-targeting vector. Currently, the commercially available chelates exploited in the radiopharmaceutical design do not fulfill all of the requirements for nuclear medicine applications, and there is a need to further explore their chemistry to rationally design highly specific chelates. Herein, we describe the rational design and chemical development of a novel decadentate acyclic chelate containing five 1,2-hydroxypyridinones, 3,4,3,3-(LI-1,2-HOPO), referred to herein as HOPO-O 10, based on the well-known octadentate ligand 3,4,3-(LI-1,2-HOPO), referred to herein as HOPO-O 8, a highly efficient chelator for 89 Zr[Zr 4+ ]. Analysis by 1 H NMR spectroscopy and mass spectrometry of the La 3+ and Tb 3+ complexes revealed that HOPO-O 10 forms bimetallic complexes compared to HOPO-O 8, which only forms monometallic species. The radiolabeling properties of both chelates were screened with [ 135 La]La 3+, [ 155/161 Tb]Tb 3+, [ 225 Ac]Ac 3+ and, [ 227 Th]Th 4+ . Comparable high specific activity was observed for the [ 155/161 Tb]Tb 3+ complexes, outperforming the gold-standard 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid, yet HOPO-O 10 surpassed HOPO-O 8 with higher [ 227 Th]Th 4+ affinity and improved complex stability in a human serum challenge assay. A comprehensive analysis of the decadentate and octadentate chelates was performed with density functional theory for the La 3+, Ac 3+, Eu 3+, Tb 3+, Lu 3+, and Th 4+ complexes. The computational simulations demonstrated the enhanced stability of Th 4+ -HOPO-O 10 over Th 4+ -HOPO-O 8 . This investigation reveals the potential of HOPO-O 10 for the stable chelation of large tetravalent radioactinides for nuclear medicine applications and provides insight for further chelate development.
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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 | 0.000 |
| 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".