## 8 Case Study and Feedback
### Case Study
#### 8.1.2 Progressive Visual Analysis Results of Molecular Pockets  
This paper evaluates the usability of visual analysis methods according to the needs of domain experts. According to the pocket characteristics in GPX4, the allosteric pockets in the protein were found. We analyze the characteristics of GPX4 protein molecular dynamic pocket to determine whether this method can quickly locate a specific location and time from the overall dynamic simulation data. This paper also supports cross-analysis of various characteristics of pockets to help experts find pockets of interest from all pockets. To establish the overall impression of the whole molecular pocket and provide a transition method from the overall pocket to the local pocket, this paper provides a navigation view. The navigation map shows the overall characteristics of the protein in the simulation time, the hydrophilic and hydrophobic characteristics, and an overview of all pocket volume changes (Figure 15a). By examining the hydrophilic and hydrophobic characteristics of the pockets, it can be seen that hydrophilic amino acids dominate in all pockets. After checking the volume change of each pocket roughly through the line chart, we notice that pocket 4 is similar to pocket 1 in the change of pocket shape. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Method** & **Pocket 2** & **Pocket 3** & **Pocket 4** & **Pocket 5** & **Pocket 6** & **Pocket 7** & **Pocket 8** \\ \hline P2V-DTW & 1416.6 & 1555.2 & 1416.2 & 1474.5 & 1425.6 & 1446.4 & 1294.7 \\ Similarity Rank & 3 & 7 & 2 & 6 & 4 & 5 & 1 \\ D3 Pockets [2] & 0.1002 & 0.0549 & 0.0286 & 0.0323 & 0.0168 & 0.0192 & 0.0174 \\ Similarity Rank & 1 & 2 & 4 & 3 & 7 & 5 & 6 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of pocket similarity calculation methods. Figure 15: (**a**) The calculated primary pocket profile. (**b**) Automatically extracts the pocket according to the pocket similarity. Through the column chart on the right side of the navigation chart, we determine the correlation between the pockets, select the normal pocket and the four pockets most similar to the normal pocket and put them into the pocket comparison view. As shown in the column diagram in Figure 15a, the orthosteric pocket (Pocket 1) of GPX4 protein is most similar to pocket 2, pocket 4, pocket 6, and pocket 8. We put the four pockets most similar to pocket 1 into the contrast view, and use the contrast view to analyze the local changes of pockets. In Figure 15b, pocket 8, pocket 6, pocket 4, pocket 2, and pocket 1 are from top to bottom. For a few selected pockets, experts need to further understand whether the size of these pockets has changed greatly and whether the pockets exist stably in the simulation process. We can observe that the volume fluctuation of pocket 8 and pocket 6 is relatively large, and the volume fluctuation of pocket 4 and pocket 2 is small. Because the opacity of each channel is encoded by the number of pockets, the opacity is high and stable. We can clearly see that the opacity of pocket 4, pocket 2, and pocket 1 is higher than that of pocket 8 and pocket 6. The river channel corresponding to pocket 4 is more opaque than other rivers, which proves that pocket 4 is more stable in a pocket similar to pocket 1. The merge component can also be used to compare the stability and correlation between pockets. In Figure 16, pocket 1 is merged and compared with pocket 2, pocket 4, pocket 6, and pocket 8, respectively. In the first stage, the shape and opacity of pocket 2 and pocket 4 are close to that of pocket 1. By comprehensively investigating the morphological changes and opacity changes of different pockets and pocket 1 at various stages, it is found that pocket 4 is the most similar to ortho pocket 1 in morphology and has good stability. At this time, experts can observe the detailed features of pocket 4 and orthosteric pocket 1 by activating the magnifying glass component.