Coevolution of Lentiviral Vif with Host A3F and A3G: Insights from Computational Modelling and Ancestral Sequence Reconstruction
Bibliographic record
Abstract
The evolutionary arms race between host restriction factors and viral antagonists provides crucial insights into immune system evolution and viral adaptation. This study investigates the structural and evolutionary dynamics of the double-domain restriction factors A3F and A3G and their viral inhibitor, Vif, across diverse primate species. By constructing 3D structural homology models and integrating ancestral sequence reconstruction (ASR), we identified patterns of sequence diversity, structural conservation, and functional adaptation. Inactive CD1 (Catalytic Domain 1) domains displayed greater sequence diversity and more positive surface charges than active CD2 domains, aiding nucleotide chain binding and intersegmental transfer. Despite variability, the CD2 DNA-binding grooves remained structurally consistent with conserved residues maintaining critical functions. A3F and A3G diverged in loop 7' interaction strategies, utilising distinct molecular interactions to facilitate their roles. Vif exhibited charge variation linked to host species, reflecting its coevolution with A3 proteins. These findings illuminate how structural adaptations and charge dynamics enable both restriction factors and their viral antagonists to adapt to selective pressures. Our results emphasize the importance of studying structural evolution in host-virus interactions, with implications for understanding immune defense mechanisms, zoonotic risks, and viral evolution. This work establishes a foundation for further exploration of restriction factor diversity and coevolution across species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".