# PNMAVis: Visual Analysis Tool of Protein Normal Mode for Understanding Cavity Dynamics
## 2 Data and Task Abstraction  
When exploring and analyzing the direct and indirect factors affecting cavity dynamics, domain experts usually try to answer the following questions:  
1. Is it the cavity-lining amino acids or other key amino acids that cause the drastic change of the protein cavity?
2. Which cavity-lining amino acids of the protein cause drastic changes in the cavity?
3. Which key amino acid atoms of the protein affect the movement of cavity-lining amino acids, resulting in drastic changes in the cavity?
4. How to explore the motion correlation between cavity-lining amino acids and key amino acids?
5. What is the relationship between cavity-lining amino acids, key amino acids, and cavity motion in three-dimensional space?  
To answer these questions, domain experts often use MD to simulate the possible trajectories of proteins to obtain the data of amino acid atom motion. However, these calculation methods have randomness, and so it is necessary to generate a large set of thousands of trajectories in order to draw statistically significant conclusions. A common alternative to MD simulation is to decompose the flexibility of proteins into a set of normal patterns. Using normal mode is also a difficult task, because normal mode calculation provides a considerable number of modes, but there is no information about regarding their possible participation. Without proper visual support, it becomes challenging to consider all of their potential combinations.  
In order to identify the requirements of visualization technology, we conducted several informal interviews with expert collaborators from the protein direction. We jointly identi  
Figure 2: A visual analysis system of protein normal mode for understanding cavity dynamics. The Protein View (**A**) displays basic protein information; The PC Detail View (**B**) contains the relationship between the fluctuation of the cavity-lining amino acids and the dynamics of the cavity; AAF HeatMap View (**C**) shows the fluctuation of amino acids under different modes; The AAFS Clustering View (**D**) is the visualization of the differences in the movements of amino acids in protein; AAFS Detailed Clustering View (**E**) describes the detailed information of a cluster; The PCDIF View (**F**) shows the key amino acids that affect the cavity; PCD 3D View (**G**) describes the change of molecule and cavity and surrounding amino acids over time.  
fied the following set of crucial tasks that must be supported by a visual analysis system to explore and analyze the normal mode of proteins for understanding cavity dynamics:  
* **T1**: Observe the cavity dynamics in different modes, and compare and analyze the distribution and fluctuation of amino acid atoms (Q1-Q4).
* **T2**: Observe the key chemical and physical properties (Q1, Q2) represented by cavity-lining amino acid atoms under different modes.
* **T3**: It can easily reveal the relationship between cavity-lining amino acid atoms and key amino acid atoms (Q3).
* **T4**: The possibility of identifying key amino acids by clustering amino acids with motions similarity (Q3, Q4).
* **T5**: Enhance the understanding of the effect of amino acids on cavity dynamics by studying 3D structures (Q5).
* **T6**: Analyze the possibility of influencing the cavity-lining amino acid atoms and key amino acid atoms with drastic changes in the cavity from the biological field cases and public data sets (Q1-Q5).