Temperature Dependence of Dynamics and Thermodynamics of the Regulatory Domain of Human Cardiac Troponin C
Bibliographic record
Abstract
Binding of Ca(2+) to the regulatory domain of troponin C (TnC) in cardiac muscle initiates a series of protein conformational changes and modified protein-protein interactions that initiate contraction. Cardiac TnC contains two Ca(2+) binding sites, with one site being naturally defunct. Previously, binding of Ca(2+) to the functional site in the regulatory domain of TnC was shown to lead to a decrease in conformational entropy (TDeltaS) of 2 and 0.5 kcal mol(-1) for the functional and nonfunctional sites, respectively, using (15)N nuclear magnetic resonance (NMR) relaxation studies [Spyracopoulos, L., et al. (1998) Biochemistry 37, 18032-18044]. In this study, backbone dynamics of the Ca(2+)-free regulatory domain are investigated by backbone amide (15)N relaxation measurements at eight temperatures from 5 to 45 degrees C. Analysis of the relaxation measurements yields an order parameter (S(2)) indicating the degree of spatial restriction for a backbone amide H-N vector. The temperature dependence of S(2) allows estimation of the contribution to protein heat capacity from pico- to nanosecond time scale conformational fluctuations on a per residue basis. The average heat capacity contribution (C(p,j)) from backbone conformational fluctuations for regions of secondary structure for the regulatory domain of cardiac apo-TnC is 6 cal mol(-1) K(-1). The average heat capacity for Ca(2+) binding site 1 is larger than that for site 2 by 1.3 +/- 0.8 cal mol(-1) K(-1), and likely represents a mechanism where differences in affinity between Ca(2+) binding sites for EF hand proteins can be modulated.
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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 | 0.001 |
| 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".