Conformation-independent structural comparison of macromolecules with ProSMART
Bibliographic record
Abstract
Structural comparison often aids insight into the function and mechanics of biological macromolecules. To make such analyses more accessible, we present the Procrustes Structural Matching Alignment and Restraints Tool (ProSMART), which is designed to allow fast but detailed comparative analysis of macromolecular structures despite potential dissimilarities in global arrangement, such as domain motion and distortion. Whilst obtaining a residue alignment between structures is a prerequisite for comparative analysis, conventional alignment methods may fail in cases where conformational differences are dramatic. However, ProSMART achieves a conformation-independent structural alignment by focusing purely on local dissimilarities, rather than enforcing chain/domain rigidity. This allows the sensible comparison of protein (or DNA/RNA) structures in the presence of conformational change. ProSMART allows analysis of the structural conservation of local backbone and side chains in a wide variety of scenarios - the method is sensitive enough to allow identification of subtle dissimilarities between structures sharing high sequence homology, whilst being versatile enough to allow identification of local similarities between more distantly-related structures. In addition, ProSMART can be used for the identification of conserved rigid substructures, which may or may not represent functional domains. ProSMART is also used for the generation of external restraints for use in crystallographic refinement. Results from ProSMART can be visualised in either CCP4mg or PyMOL. All residue-based scores are illustrated using intuitive colour gradients, allowing easy visual assessment of local backbone and side chain conservation. Complementary structural comparison tools such as ProSMART can help break the complexity of the constantly growing pool of available structural data into a more readily accessible form, and consequently may aid biological insight into macromolecular structures.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.011 |
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".