# PNMAVis: Visual Analysis Tool of Protein Normal Mode for Understanding Cavity Dynamics
## 8 Discussion and Conclusions  
In this paper, a new interactive visualization method to understand the dynamics of cavities has been presented. The method uses visualization techniques to process high-dimensional normal mode data, and allows the user to explore the cavity, as well as aid the user in the discovery of aliasing sites. The method has three advantages over previous approaches:  
1. Our work realizes a set of linked 2D and 3D Views, which can be explored interactively to quickly locate the direct factors (cavity-lining amino acid atoms) and indirect factors (key atoms) that affect the dynamic characteristics of the cavity.
2. Using normal mode data to establish the relationship between cavity-lining amino acid atom movement, key amino acid atom movement, and cavity shape changes, so as to help users find potential allosteric sites.
3. The system utilizes multiple views from multiple perspectives for the user to explore the stability of the cavity, including cavity characteristics and the properties of the amino acids surrounding the cavity.  
To explore and to validate the effectiveness of our method, a predicted allosteric site has been supported by previous reports or internal experimental studies, such as CDK2 (PDB code: 2C6K [41]). The results show that by interactively exploring the system, we find that the known allosteric sites are in the same cluster as the majority of the cavity-lining amino acids; thus, we reasonably believe that other amino acids (excluding cavity-lining amino acids) in this cluster are also potentially allosteric sites (**T1-T6**).  
Our method is designed to help users to explore the dynamics of cavities, and to help them identify key amino acids. However, when we consider the effects of distant amino acids on the cavity, our method only considers the motion properties of the amino acids, and ignores other properties of the amino acids, such as whether it has allosteric properties, the cavity in which the amino acid is located, etc. In the future, we plan to combine other properties of amino acids with normal mode data, in order to discover aliasing pockets by combining visualization methods, which is an interesting direction for future work.  
**Author Contributions:** Conceptualization, D.G. and L.F.; methodology, D.G. and L.F.; software, Y.G. and T.Z.; validation, Y.W. and T.Z.; formal analysis, D.G.; investigation, L.F.; resources, L.F.; data curation, Y.G. and L.F.; writing--original draft preparation, L.F.; writing--review and editing, Y.W. and L.F.; visualization, L.F. and T.Z.; supervision, X.X.; funding acquisition, D.G. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by grants from the National Key R&D Program of China and the National Science Foundation of China (Grant no. 61802334, no. 61902340), Natural Science Foundation of Hebei Province (F2022203015), and Innovation Capability Improvement Plan Project of Hebei Province (22567637H).  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors wish to thank [PERSON] in Chinese Marine University for his advice on domain knowledge. We are very grateful for the experimental data provided by Caver Analyst 2.0 [42] and WEBhm@[35].  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.