Characterization of the KRas G12D-inhibitor interactions by differential HDX-MS and molecular dynamics simulations
Bibliographic record
Abstract
Hydrogen-deuterium exchange (HDX) combined with mass spectrometry (MS) is a powerful technique for studying changes in protein structure and dynamics upon ligand binding. Protein-ligand complexes can result in increased protection of peptide-bond amides in HDX indicating protein structure stabilization. We have characterized the interaction of small-molecule inhibitors towards the KRas G12D oncoprotein by intact-protein and bottom-up HDX-MS, in combination with molecular dynamics (MD) simulations. Significant differences in HDX protection were detected upon inhibitor binding in the flexible switch-II pocket of the protein. MD simulations of the free and inhibitor-bound KRas G12D proteins also revealed changes in the hydrogen bond network of backbone amides in the switch-II region upon inhibitor binding, explaining the observed HDX protection changes. We have proposed simple semi-empirical metrics which relate changes in HDX-MS experimental values and observed in MD simulations changes in individual backbone hydrogen-bonds between free- and ligand-bound protein states. This combined HDX-MS and MD approach provides an atomistic picture of changes in the KRas G12D secondary structure upon ligand binding and may be a useful tool for future drug design efforts.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".