Structural modeling of human AKAP3 protein and in silico analysis of single nucleotide polymorphisms associated with sperm motility
Bibliographic record
Abstract
AKAP3 is a member of the A-kinase anchoring proteins and it is a constituent of the sperm fibrous sheath. AKAP3 is needed for the formation of sperm flagellum structure, sperm motility, and male fertility. This study aims to model the AKAP3 tertiary structure and identify the probable impact of four mutations characterized in infertile men on the AKAP3 structure. The T464S, I500T, E525K, and I661T substitutions were analyzed using in silico methods. The secondary structure and three-dimensional model of AKAP3 were determined using PSI-BLAST based secondary structure prediction and Robetta servers. The TM-score was used to quantitatively measure the structural similarities between native and mutated models. All of the desired substitutions were classified as benign. I-Mutant results showed all of the substitutions decreased AKAP3 stability; however, the I500T and I661T were more effective. Superposition and secondary structure comparisons between native and mutants showed no dramatic deviations. Our study provided an appropriate model for AKAP3. Destabilization of AKAP3 caused by these substitutions did not appear to induce structural disturbances. As AKAP3 is involved in male infertility, providing more structural insights and the impact of mutations that cause protein functional diversity could elucidate the etiology of male fertility problems at molecular level.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".