## 3 Results
### Structure Prediction, Refinement and Validation
#### 3.5.3 Structure Validation, Refinement, Quality Assessment, and Model Selection  
Based on the Ramachandran plots, the RoseTTAFold model (Figure 1e) of VLP was the best-predicted structure, but it was not a high-quality model, as it would have had over 90% of its residues in the most favored regions. Therefore, we refined all the 3D modeled structures using the GalaxyRefine server, which performed repacking and sidecahain rebuilding processes to relax the structures through MDS. GalaxyRefine produced five refined models, from which we selected the models with the highest percentage of residues in the Ramachandran-favored regions and the lowest RMSD values. The selected iTASSER refined model exhibited 88.2% of residues in the Ramachandran favored regions and an RMSD value of 0.462 (Figure 1i). For RoseTTAFold, the selected refined model showed superior quality, with 97.8% of residues in the favored regions and an RMSD value of 0.348 (Figure 1k). The chosen refined AlphaFold model demonstrated 96.4% of residues in the favored areas with an RMSD value of 0.856 (Figure 1m). The refined 3D structures of VLP were evaluated using Ramachandran plot analysis, revealing differences in the quality of the models generated by iTASSER, RoseTTAFold, and AlphaFold. The iTASSER refined model showed 76.7% of residues in the most favored regions, 19.8% in additional allowed regions, 2.1% in generously allowed regions, and 1.3% in disallowed regions (Figure 1j). In contrast, the RoseTTAFold refined model demonstrated a higher quality, with 89.3% of residues in the most favored regions, 9.9% in additional allowed regions, 0.5% in generously allowed regions, and only 0.3% in disallowed regions (Figure 1l). Similarly, the refined AlphaFold model exhibited 90.4% of residues in the most favored regions, 8.0% in additional allowed regions, 1.3% in generously allowed regions, and 0.3% in disallowed regions (Figure 1n). By comparing these models, the AlphaFold refined structure had the highest percentage of residues in the most favored regions, indicating superior structural quality. RoseTTAFold and AlphaFold outperformed iTASSER in residues in the most favored regions and residues in disallowed regions, with RoseTTAFold slightly trailing AlphaFold. These results suggest that AlphaFold and RoseTTAFold provide more reliable models for VLP, with AlphaFold demonstrating a marginal advantage in overall structural accuracy. Due to this marginal difference, we further validated the structures predicted by AlphaFold and RoseTTAFold using MolProbity metrics, revealing significant differences in the quality of the models (as shown in Table 2). In terms of all-atom contacts, the RoseTTAFold refined model had a clashscore of 1.93 (99 th percentile), indicating very few severe steric overlaps (>0.4 A per 1000 atoms), compared with the refined AlphaFold model, which had a clashscore of 18.88 (36 th percentile). This result suggests that the RoseTTAFold model significantly minimizes steric clashes. Regarding protein geometry, the RoseTTAFold model had 0.27% poor rotamers and 98.91% favored rotamers, both metrics meeting the desired goals, whereas the AlphaFold model fell slightly short, with 0.55% poor rotamers and 97.54% favored rotamers. The RoseTTAFold model also performed better in terms of Ramachandran plot metrics, with 0.24% outliers and 97.83% favored regions, compared with AlphaFold's 0.72% outliers and 96.39% favored regions. The Rama distribution Z-score for RoseTTAFold was \(-\)0.25 \(\pm\) 0.38, indicating a good fit, whereas AlphaFold had a Z-score of \(-\)2.65 \(\pm\) 0.27, outside the acceptable range (absolute Z-score < 2). Additionally, the MolProbity score for RoseTTAFold was 1.00 (100 th percentile), indicating an excellent overall structural quality, while AlphaFold had a MolProbity score of 2.01 (75 th percentile).