## 5 Multi-Level Visual Design and Analysis of RGN Predicted Results
### Differences between Structures  
The predicted structure has been aligned with the actual structure. Our work analyzes the differences between the two structures as a whole through the changes in deviation, torsion angle, and _dRMSD_. The deviation is the euclidean distance between the corresponding residues after the two structures are aligned. The torsion angle is the rotation angle between the bonds between the residues, where the change in the torsion angle affects the spatial coordinates of the residues and the entire spatial structure directly. _dRMSD_ change is a similarity change during the prediction of the RGN because the optimized signal of the RGN is the normalized _dRMSD_. We use the above aspects to analyze the predicted structure and the actual structure locally. Firstly, in terms of deviation attributes, the distance between the C\(\alpha\) atoms of each amino acid is mainly calculated because C\(\alpha\) atoms have their own spatial regions and determine the nature and physical form of the protein. Moreover, in the prediction results  
Figure 4: The mixed line and bar shows the comparison of _dRMSD_, _TM-Score_ and _GDT_TS_. Its horizontal axis represents the id of the protein chain, and the vertical axis represents the value of the evaluation criterion. This comprehensively shows the prediction situation of the RGN, enriches the analysis angle, and provides a channel for interactive analysis. of the RGN, only the three main chain atoms N, C\(\alpha\), and C are predicted. The figure below shows the change in the deviation attribute of a certain protein chain (Figure 5). For this protein chain, the distance between the predicted structure and the actual structure fluctuates greatly. As mentioned in Section 5.1, _TM-Score_ requires the structure to be aligned in advance, and it calculates the similarity value after the maximum alignment distance. It can be observed that the alignment distance of this protein chain is very short, and the _TM-Score_ is only 0.2. Secondly, for the torsion angle attribute, it determines the spatial structure of the entire protein and also has a direct impact on the stability level of the prediction result. The following figure shows the changes in the predicted structure and the actual structure of a certain protein chain with respect to the three torsion angles (Figure 6). The torsion angle is the source of all protein conformations and determines the local structural conformation of the protein. It can be seen that the torsion angle changes between the predicted structure and the actual structure fluctuate greatly (Figure 6), and further, it may cause the protein function performed by the predicted structure to be different from the actual structure (Figure 7). Finally, we analyze the changes in _dRMSD_ during the RGN prediction process (Figure 8). The RGN uses _dRMSD_ in the assessment stage to calculate the similarity between the predicted structure and the actual structure. It adds the _dRMSD_ normalized loss function in each iteration, and optimizes the RGN parameters according to the _dRMSD_ in the assessment stage, and generates its complete tertiary structure at the end. Figure 5: The area chart shows the deviation of a certain protein chain after alignment. Figure 6: The line chart shows the predicted structure (**blue**) and actual structure (**red**) of a certain protein chain at angles \(\phi\), \(\psi\), and \(\omega\), respectively. Figure 7: The tertiary structure visualization figure shows the partial fragments of a protein chain after the predicted structure (**blue**) and the actual structure (**red**) are aligned. Considering this level comprehensively, we link these three attributes with the other two levels. _TM-Score_ and _GDT_TS_ can be calculated according to the alignment deviation between the predicted structure and the actual structure. For the _dRMSD_ change trend, the RGN parameter changes can be analyzed, which has an important relationship with the analysis of the prediction accuracy of the RGN.