Explanation please.

"The main difference for this protein will be scoring purely based on energy, and not RMSD - i.e., we won't be "cheating" in scoring the structures."

Might someone put this in laymans terms? I do know that the "scoring" is not related to the points per generation.

Here is the simple version:
Until now, we had been scoring based on RMSD. RMSD = root mean square deviation from the correct native structure. What this means is that we KNOW the native structure of the protein, which is has RMSD of 0.0 (it doesn't deviate from itself). Any generated structure is evaluated based on how closely it approaches the native structure, where the score is the RMSD. This method is "cheating" because normally we would be trying to fold proteins whose native structure is unknown - the folding will strive to find the structure which os closest to the native protein.

Thus, we will move to scoring by using energy-based scoring functions. In this case the protein's score will be based on its energy and compactness, without relying on the native structure for comparison. The idea remains that lowest-scoring proteins should most closely resemble the natural-occuring structure. However, in this case, the prediction is ab-initio, or in layman's terms, from scratch.

Note that when we talk about 'score' here, the lowest score from each generation is used to move on to the next generation. Thus it will affect the direction the folding simulation takes - it will always proceed towards the direction of lower energy where possible now, whereas before it would proceed to lower RMSD.

So, up until now we have been strolling around known garden paths and are about to begin a trek into the wilderness eh? ;)

Let's get on with it!! :walking:

EDIT: Oh, and thank you very much.

accepting the notion that you Hogueans have better things to do than address the ignorant-- but this stuff can be fascinating, even to the intellectually lazy or ungifted...
:)


is the whole thing- every "choice"- energy driven ? minimizing energy, all the time ??

if the energy landscape over "there" ressembles a high -energy "ridge", will the program not venture beyond it-- missing out on a possibility of lower energy "craters" beyond ?

if not energy driven every step of the way, one would think it would have to be one very clever program...

While not a "Hoguean" I believe that I can answer some of that question.

Consider that you want to find the lowest point in a very large plane. Even if we assume that the surface is continuous, there is no way to find the lowest point without checking every single point, because any point we don't check could be a valley of unknown depth.

So, while we would like to be able to find the optimal solution, we can't do this in any sort of reasonable time. So instead, we make several assumptions which make the problem easier and use heuristics to get a good solution within a reasonable amount of time (where reasonable is of course dependent on the computational resources you can bring to bear on the problem).

As time goes on, we're probably going to be going up the scale in terms of heuristics (and in terms of algorithm complexity) to hopefully get better and better solutions in the same amount of time. However, it is probably going to take quite a while before we have the computational power necessary to be able to find an optimal solution in any amount of reasonable time, even given much better heuristics.

Umm, if one of the problems is that this thing is so hueristic, would not a little shaving cream and a good sharp razor make things a bit clearer?

:rotfl:

They got the Algorithm, we got the time :) It's Wabbit season !