Open mostafa-razavi opened 4 years ago
1) What will happens if the study is repeated at two different sets of parameters that avoid the meta-stable points.
2) What if the sigma of CH_2 is changed, but the sigma of CH_3 is constant. The disagreement must be even larger.
3) Check if the direct simulations are properly equilibrated. Maybe run longer simulations (e.g. 5 M steps) and see if the MBAR prediction of Z is any better. Done!
4) Repeat the plot using N=1000 instead of 500 and see if the MBAR prediction is improved. Done!
- Check if the direct simulations are properly equilibrated. Maybe run longer simulations (e.g. 5 M steps) and see if the MBAR prediction of Z is any better.
Here is the equilibration plot of the meta-stable point. 2 M steps seems to be enough for
4) Repeat the plot using N=1000 instead of 500 and see if the MBAR prediction is imoroved.
The N=1000 results shows that using higher number of snapshots does not change the agreement between MBAR and direct sim. for IT points. However, there a significant and rather random difference between N=1000 and N=500 for near saturation temperature points on IC's. One of them get better and the other gets worse. These points have large uncertainties, so the big difference is justifiable.
What if the sigma of CH_2 is changed, but the sigma of CH_3 is constant. The disagreement must be even larger.
It turns out that the N_eff heavily depends on the number of sites of the sigma that has changed. When sigma_CH_3 and sigma_CH_2 are changed 0.02 A, N_eff in MBAR is 373-717 and 710-927. However, the MBAR performance seems to be similar.
Predicted at s3.760e120.0_s4.02e60.0:
Predicted at s3.760e120.0_s4.02e60.0
Conclusions: 1) U^res is much more predictable using MBAR than Z even for large eps variations of C12 CH_2 site 2) Z is hard to predict when sigma varies a lot, but when epsilon varies up to 4 K Z is still predictable
I used the following Mie simulations as references:
sig_CH3 | eps_CH3 | sig_CH2 | eps_CH3 |
---|---|---|---|
3.74 | 118 | 4.03 | 62 |
3.763 | 120.25 | 3.97 | 59.5 |
3.783 | 121.25 | 3.99 | 61 |
3.803 | 122.25 | 4.01 | 61.5 |
3.84 | 120 | 3.96 | 59 |
to predict the MiPPE Z and U^res, i.e. 3.783 | 121.25 | 3.99 | 61 and here is the result:
Conclusions: 1) In all cases, U^res is perfect. 2) For small simple molecules such as C2, Z is more predictable using MBAR. For larger molecules, MBAR is not very accurate.
Todo: 1) Figure out a way to to systematically show the inaccuracies of MBAR for large molecules 2) Maybe incorporate higher temperatures at high densities to avoid meta-sable region?
I ran the following direct simulations and I used the first as a reference simulation to predict the Z and U^res using MBAR (N=500) at the parameter set of the second and compare to the second direct simulation results. Both direct simulations are run for 2 million steps and averages and uncertainties are obtained using 5 blocks of the last 1 M steps.
Reference: C12_s3.760e120.0_s4.00e60.0 Prediction: C12_s3.780e120.0_s4.00e60.0
Only sigma_CH_3 was changed and sigma CH_2 was not changed. Note that only 2 sites out of the total 12 sites in C12 are CH_3, so one would expect a reasonable agreement between direct simulation and MBAR prediction.
Also, the sigma_CH3 difference between the reference and the prediction is 0.02 A which is less than the recommended value of 0.025 A.
!#The Z and U^res of C12_s3.760e120.0_s4.00e60.0 (ref.sim.)
Conclusions:
1) The MBAR predicts U^res better than Z. This was also mentioned in Messerly2018.
2) Even though the value of N_eff is way larger (~400) than the minimum recommended value of 50, the predicted Z values at some ITIC points disagree with direct simulation results.
3) The intra method (as opposed to single molecule) gives reasonable U^res values when MBAR is used.
4) Uncertainty of direct simulation Z is largest for the meta-stable point, and the MBAR prediction is the best for this point.