Effects of Excipients on the Structure and Dynamics of Filgrastim Monitored by Thermal Unfolding Studies by CD and NMR Spectroscopy
Bibliographic record
Abstract
Product excipients are used to confer a number of desirable properties on the drug substance to maintain or improve stability and facilitate drug delivery. This is especially important for products where the active pharmaceutical ingredient (API) is a recombinant protein. In this study, we aimed to determine if excipients and formulation conditions affect the structure and/or modulate the dynamics of the protein API of filgrastim products. Samples of uniformly labeled 15N-Met-granulocyte-colony stimulating factor (GCSF) were prepared at 100 μM (near formulation concentration) with various concentrations of individual components (polysorbate-20 and -80, sorbitol) and three pH values. Nuclear magnetic resonance (NMR) spectroscopy techniques were applied to measure chemical shift perturbation (CSP) to detect structural changes, and relaxation parameters (T1, T2, and heteronuclear Overhauser effect) were measured to probe the effects on protein backbone motions. In parallel, the same solution conditions were subjected to protein thermal unfolding studies monitored by circular dichroism spectropolarimetry (CD). Detergents (polysorbate-20 and 80) do not induce any observable changes on the protein structure and do not modify its dynamics at formulation concentration. Lowering pH to 4.0, a condition known to stabilize the conformation of filgrastim, as well as the addition of sorbitol produced changes of the fast motion dynamics in the nanosecond and picosecond timescale. NMR-derived order parameters, which measure the local conformational entropy of the protein backbone, show that lowering pH leads to a compaction of the four-helix bundle while the addition of sorbitol relaxes helices B and C, thereby reducing the mobility of loop CD. CSPs and measurements of protein dynamics via NMR-derived order parameters provide a description in structural and motional terms at an atomic resolution on how formulation components contribute to the stabilization of filgrastim products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".