Evaluation of the Utility of NMR Structures Determined from Minimal NOE-Based Restraints for Structure-Based Drug Design, Using MMP-1 as an Example
Bibliographic record
Abstract
The application of deuterium labeling and residual dipolar coupling constants in combination with other structural information has demonstrated the potential for significantly expanding the range of viable protein targets for structural analysis by NMR. A previous study by Clore et al. [(1999) J. Am. Chem. Soc. 121, 6513-6514] demonstrated that a significant improvement in the overall protein structure occurs with the combination of residual dipolar coupling constants and minimal tertiary long-range distance restraints. The analysis of NMR protein structures determined with minimal structural information is extended with a particular interest in the utility of these structures for a structure-based drug design program. As an example, the catalytic fragment of human fibroblast collagenase (MMP-1) was used to follow the effect of minimal restraint sets on the protein structure and its utility in drug design with a particular interest in the effect on the active site conformation. An MMP-1 structure that was calculated with the maximal number of restraints attainable with the constraint of a deuterated protein was shown to be very similar to a high-quality MMP-1 structure that was calculated from a complete set of restraints. The superposition of the active site backbone atoms for the high-quality and minimal restraint MMP-1 structures yielded an rmsd of 0.68 A where the size and shape of the S1' pocket are nearly identical. Additionally, an MMP-1-CGS-27023A complex based on a minimal set of NOE-based restraints reliably reproduced the structure of the complex, establishing the usefulness of the structures for drug design.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".