Computational studies on photolyase (Phr) proteins of cyanobacteria
Bibliographic record
Abstract
Photolyases (Phrs) are enzymes that utilize the blue/ultraviolet (UV-A) region of light for repairing UV-induced cyclopyramidine dimers. We studied Phr groups by bioinformatic analyses as well as active-site and structural modeling. Analysis of 238 amino acid sequences from 85 completely sequenced cyanobacterial genomes revealed five classes of Phrs, CPD Gr I, 6-4 Phrs/cryptochrome, Cry-DASH, Fe-S bacteria Phrs, and a group with fewer amino acids (276-385) in length. The distribution of Phr groups in cyanobacteria belonging to the order Synechococcales was found to be influenced by the habitats of the organisms. Class V Phrs are exclusively present in cyanobacteria. Unique motifs and binding sites were reported in groups II and III. The Fe-S protein binding site was only present in group V and the active site residues and putative CPD/6-4PP binding residues are charged amino acids present on the surface of the proteins. The majority of hydrophilic amino acid residues were present on the surface of the Phrs. Sequence analysis confirmed the diverse nature of Phrs, although sequence diversity did not affect the overall three-dimensional structure. Protein-ligand interaction analysis identified novel CPD/6-4PP binding sites on Phrs. This structural information of Phrs can be used for the preparation of efficient Phr-based formulations.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".