2. If you increase the y-axis upper limit from one to two Angstroms, the RMSD line will appear less noisy, and your conclusion about the (in)stability of the protein may change.
3. If you decrease the number of y-axis ticks from ten to five, the RMSD line will appear less noisy, and your conclusion about the (in)stability of the protein may change.
4. By plotting moving average, you can smooth out most of the noise, and your conclusion about the (in)stability of the protein may change.
5. Assess the convergence by comparing the quantity in question obtained from the first and second half of the MD trajectory; if you set a reasonable convergence threshold, your conclusion about the (in)stability of the protein may change.
6. Calculate RMSD after aligning different parts of the protein to identify which parts contribute most to the total RMSD value.
7. Some twenty years ago people were able to achieve excellent quantitative agreement with commensurable experimental data using structures and energies obtained from 500 ps (yes, picosecond) MD trajectories.
8. MD simulation is most useful if used for sampling of the configurational space near the initial structure---and for this purpose, in most cases, i would say, the shorter the trajectory, the better; rather than running one long MD simulation, it is generally better to run many short MD simulations, starting from different initial conditions---this is also very useful if one wants to assess the uncertainty of the quantitative results.
It looks like you just have a very flexible protein. 70 ns is not a very long time in terms of most simulations. Look at other structural properties to see if they have stabilized. RMSD is not a very good metric for really learning what the structure is doing.
Check RMSF and dssp... also do a cluster analysis or a PCA, to see if the motions are global or if the RMSD is reflecting the more flexible motifs (coils) of your protein.
2. If you increase the y-axis upper limit from one to two Angstroms, the RMSD line will appear less noisy, and your conclusion about the (in)stability of the protein may change.
3. If you decrease the number of y-axis ticks from ten to five, the RMSD line will appear less noisy, and your conclusion about the (in)stability of the protein may change.
4. By plotting moving average, you can smooth out most of the noise, and your conclusion about the (in)stability of the protein may change.
5. Assess the convergence by comparing the quantity in question obtained from the first and second half of the MD trajectory; if you set a reasonable convergence threshold, your conclusion about the (in)stability of the protein may change.
6. Calculate RMSD after aligning different parts of the protein to identify which parts contribute most to the total RMSD value.
7. Some twenty years ago people were able to achieve excellent quantitative agreement with commensurable experimental data using structures and energies obtained from 500 ps (yes, picosecond) MD trajectories.
8. MD simulation is most useful if used for sampling of the configurational space near the initial structure---and for this purpose, in most cases, i would say, the shorter the trajectory, the better; rather than running one long MD simulation, it is generally better to run many short MD simulations, starting from different initial conditions---this is also very useful if one wants to assess the uncertainty of the quantitative results.
You need to define what you mean by stability first. The idea of protein stability in an MD trajectory is not validated by RMSD. RMSD simply shows you how different is your trajectory from starting structure. So it is reference based. Check the energetics. Further, based on your description of the protein [two helices connected by a short loop], I would expect that plot for RMSD. As Justin has pointed out you need longer simulation [100-200ns window with triplicates]. And I also suggest that you define a much more precise metric [RMSF for such a protein will only be high as it is flexible] to quantify and understand the conformational behavior of your system. That is the critical step for any MD analysis.