Hows and whys of RNA folding.

Hello. I’m new here, and I’ve just finished the basic tutorials. I am not a biochem student, so forgive me if my questions are essentially noob :slight_smile:

Why is better to crowd source different ways to fold rather than simply write algorithms to consider every possible fold (given a certain number of nucleotides to start with) and evaluate each fold? One obvious answer is that if the number of nucleotides are many to star with, the number of possible permutations of folds go up exponentially. But then, automated ways are efficient at just this sort of thing, yes?

And thirdly, the energy counter on the top left corner, is the idea to keep this as low as possible. I am assuming that this is the energy it takes to ‘mutate’ one nucleotide to another, and thus any stable fold achieved using a minimum of energy expenditure is a ‘better’ design. Is the negative sign simply an indication that it represents energy ‘consumed’?

And thirdly, is it a given that a certain distribution of nucleotides always results in a certain ‘folding’? Does the game abstract out other parameters?

And lastly is there any write up that gives whys and the hows of folding RNAs. This could probably answer most of my questions above.

Hi, Thanks for your post.
To answer your first question, you are right, as the number of bases in RNA increases the number of possible folds increases exponentially. So when you get up to relevant sized RNA which are sever hundred or several thousand bases long, it becomes intractable for a computer to solve every possible fold.

The energy indicator in the corner is the measure of potential energy of the molecule. When you make a mutation that makes two bases to pair with each other, it is a favorable interaction and then free energy of the molecule gets lower (more negative), which is better.

A certain sequence of nucleotides should in theory should fold in to one specific structure, but this is certainly an absolute truth.

And you may want to check out some of the guides on getSatisfaction:

General Strategy Guide:…

Loops Guide:…

RNA Lab Guide:…

Hope this helps!

Insufferablejake: Thanks for the great questions. It looks like MBP got to a lot of your questions above. To answer the first – why can’t a computer do this – you might find this post interesting.

Thankyou Matt and Adrien for your answers, let me read up the links you’ve suggested.

Is a design with the lowest possible free energy total more likely to fold best of all available designs or is there a different range for each different shape that influences whether or not it will fold in nature?

This is a great question that deserves a thorough answer but I’ll give a short one for now. The lower the free energy, the more favorable your target structure is compared to a completely unfolded, non-base-paired structure (which is shown as a straight line when you are just starting a puzzle). It should be remembered that there are many suboptimal folds that are also possible, and as long as these folds have lots of base pairs they will also have a favorable (negative) free energy. The gap between the lowest free energy structure and the most favorable suboptimal fold, as well as the number of possible suboptimal folds, these will all come into play to determine how something ends up in nature. Note that the suboptimal folds are not shown by the game but you can imagine it from all the “wrong” answers you tried along the way. There are 3rd-party tools that can do this:…

So if you design a target where you use the same base-pair pattern over and over, you can be sure there will be suboptimal folds that show up in real life unless you add some randomness into it. Hopefully at some point the game will give you some sort of warning in these scenarios, until then just remember that lower free energy does not necessarily mean better.