Binding Mechanism of an SH3 Domain Studied by NMR and ITC
Bibliographic record
Abstract
Complexes between Src-homology 3 domains and proline-rich target peptides can have lifetimes on the order of milliseconds, making them too short-lived for kinetic characterization by conventional methods. Nuclear magnetic resonance (NMR) dynamics experiments are ideally suited to study such rapid binding equilibria, and additionally provide information on partly bound intermediate states. We used NMR together with isothermal titration calorimetry (ITC) to characterize the interaction of the SH3 domain from the Fyn tyrosine kinase with a 12-residue peptide at temperatures between 10 and 50 degrees C. NMR data at all temperatures are consistent with an effectively two-state binding reaction, such that any intermediates are either very weakly populated or exchange extremely rapidly with the free or bound forms. Dissociation rate constants, determined by CPMG and ZZ-exchange NMR experiments, range from k(off)(10 degrees C) = 4.5 s(-1) to k(off)(50 degrees C) = 331 s(-1). ITC data at all temperatures follow a simple two-state interaction model. Binding is favored enthalpically, with a dissociation enthalpy, DeltaH(D)(30 degrees C) = 15.4 kcal mol(-1), and disfavored entropically, with a dissociation entropy, DeltaS(D)(30 degrees C) = 20.0 cal mol(-1) K(-1). The free protein and peptide have significantly higher heat capacity than the bound complex, DeltaC(p) = 352 cal mol(-1) K(-1), which is consistent with the largely hydrophobic character of the binding interface. An Eyring plot of k(off) values gives an activation enthalpy of dissociation, DeltaH(D)(double dagger)(30 degrees C) = 19.3 kcal mol(-1) and exhibits slight curvature consistent with the ITC-derived value of DeltaC(p). The curvature suggests that nonpolar residues of the hydrophobic interface are solvated in the transition state for dissociation. Association rate constants were calculated as k(on) = k(off)/K(D), and range from k(on)(10 degrees C) = 1.03 x 10(8) M(-1) s(-1) to k(on)(50 degrees C) = 2.0 x 10(8) M(-1) s(-1), with an apparent activation enthalpy, DeltaH(A)(double dagger) = 3.4 kcal mol(-1). Both the magnitudes and temperature dependence of k(on) values are consistent with a diffusion-limited association mechanism. The combination of NMR and ITC data sheds light on how the Fyn tyrosine kinase is activated by binding to proline-rich targets, and represents a powerful approach for characterizing transient protein/ligand interactions.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".