High RMSD value but its stable

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I have developed a homology model of a protein with only 15% sequence similarity. Consequently, the AlphaFold homology model lacks high accuracy. To gain insight into the protein’s behavior, I conducted a 1000 ns molecular dynamics (MD) simulation on this model. However, I noticed that the root mean square deviation (RMSD) values consistently hover around ~1.2 nm throughout the simulation, which is relatively high. This suggests that the AlphaFold model may not have accurately captured the true conformation due to the low sequence identity.

For RMSD calculation, I used the following commands:

gmx trjconv -s md_0_1.tpr -f md_0_1.xtc -o md_0_1_noPBC.xtc -pbc mol -center (I selected group 1 (“Protein”) as the group to be centered and group 0 (“System”) for output.)
gmx rms -s md_0_1.tpr -f md_0_1_noPBC.xtc -o rmsd.xvg -tu ns (I chose backbone atoms for both the least-squares fit and the group for RMSD calculation.)

Please suggest what steps I should take next to effectively analyze the simulated protein. Am I going in the right direction?
rmsd_new400.xvg (2.5 MB)

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Have you watched your simulation? RMSD values alone do not say anything. At 1.x nm, it can be a key domain or interface unfolding, or an unstructured terminal tail wiggling around; the first will be bad and the second perfectly neutral. Larger, multidomain molecules will also naturally have larger RMSDs when fluctuating than smaller single-domain ones.

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Yes, I analyze other factors as well like rmsf, rg, sasa. All of them are stable. As this protein contains loops may be that can be one of the factors for high fluctuations. I think I got this. Thank you so much for your suggestion.