Rational Design of PROTAC Linkers Featuring Ferrocene as a Molecular Hinge to Enable Dynamic Conformational Changes
Bibliographic record
Abstract
Proteolysis Targeting Chimeras (PROTACs) are bifunctional molecules that induce ubiquitination and degradation of a target protein via recruitment to an E3 ligase. The linker influences many steps of the PROTAC mode of action, from cellular permeability to ternary complex formation and target degradation. Much interest has therefore been devoted to linker design to fine-tune molecular and mechanistic properties of PROTACs. In this study, we present FerroTACs, a novel PROTAC design strategy incorporating ferrocene as the linker chemotype. We exemplify the approach across three different PROTAC systems: VHL-VHL (homo-PROTACs), VHL-CRBN, and VHL-BETs. We find that ferrocene’s unique organometallic structure, featuring freely rotating cyclopentadienyl rings around a central Fe(II) ion, acts as a molecular hinge enabling dynamic conformational changes i.e., chameleonicity. Conformational analyses via NMR spectroscopy support ferrocene's role in fostering intramolecular interactions that result in a more folded state in an apolar environment. This property promotes compact conformations, improving cellular permeability and reducing efflux liabilities. Cellular assays demonstrate that FerroTACs exhibit robust target degradation and cell permeability profiles, en-par or enhanced compared to benchmark PROTACs CM11, 14a and MZ1. These findings highlight ferrocene’s potential as a new linker design strategy, offering a versatile platform to install and control molecular chameleonicity into next-generation PROTACs.
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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".