Sequence Analysis, Structure Prediction, and Functional Validation of<i>phaC1/phaC2</i>Genes of<i>Pseudomonas</i>sp. LDC-25 and Its Importance in Polyhydroxyalkanoate Accumulation
Bibliographic record
Abstract
Polyhydroxyalkanoates (PHAs) are attractive biomaterials in both conventional medical devices and tissue engineering. PHA synthase is responsible for catalyzing the formation of Polyhydroxyalkanoates (PHA), but its structural information is limited. Hence, this study focuses to predict 3D model for phaC1 and phaC2 genes of field-soil strain Pseudomonas sp. LDC-25 and to validate the functional properties through in vitro studies. The phaC1/phaC2 genes were amplified, cloned, and sequenced. The sequence analysis showed > 90% homology to phaC loci and presence of alpha/beta hydrolase fold, but phaC2 loci of LDC-25 exhibits variation in the conserved residue (Ser is replaced by Ala). Threading approach demonstrated that Carboxylesterase (d1tqha) can be used as the modeling template. The predicted models showed the presence of conserved residues at 122 (G), 205 (S), and 236 (S). In vitro studies also supported that PHA accumulation ability was less in Pseudomonas sp. LDC-25 compared to other field isolate, Pseudomonas sp. LDC-5. FT-IR spectrum showed PHA specific peaks at 1735.62 cm(-1). Results of this study would help to detect the functional domains of the protein in order to elucidate their structure/function characteristics with special emphasis on invariant conserved residues.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".