Rigid Macrocycle Metal Complexes as CXCR4 Chemokine Receptor Antagonists: Influence of Ring Size
Bibliographic record
Abstract
Understanding the role of chemokine receptors in health and disease has been of increasing interest in recent years. Chemokine receptor CXCR4 has been extensively studied because of its defined role in immune cell trafficking, HIV infection, inflammatory diseases, and cancer progression. We have developed high affinity rigidified CXCR4 antagonists that incorporate metal ions to optimize the binding interactions with the aspartate side chains at the extracellular surface of the CXCR4 chemokine receptor and increase the residence time. Cross- and side-bridged tetraazamacrocylic complexes offer significant advantages over the non-bridged molecular structures in terms of receptor affinity, potential for radiolabelling, and use in therapeutic applications. Our investigation has been extended to the influence of the ring size on bridged tetraazamacrocyclic compounds with the addition of two novel chelators (bis-cross-bridged homocyclen and bis-cross-bridged cyclen) to compare to the bis-bridged cyclam, along with novel metal complexes formed with copper(II) or zinc(II). The in vitro biological assays showed that all of the zinc(II) complexes are high affinity antagonists with a marked increase in CXCR4 selectivity for the bis-cross-bridged cyclen complex, whereas the properties of the copper(II) complexes are highly dependent on metal ion geometry. X-ray crystal structural data and DFT computational studies allow for the rationalisation of the relative affinities and the aspartate residue interactions on the protein surface. Changing the ring size from 14-membered can increase the selectivity for the CXCR4 receptor whilst retaining potent inhibitory activity, improving the key pharmacological characteristics.
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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".