Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Don't proteins fold as they exit the ribosomal tunnel? If this is the case then the folding algorithm should model the sequence in which Amino acid chains exit. Correct? This should be a huge clue as to how side-chains bend and twist as they interact hydrophobic-ly and hydrophilic-ly. Sort of like strings of play-doh exiting a child's play-doh press.

Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Yes, that is a description of how GAs work. However, in the case of Rosetta they use simulated annealing methods (rather than GA methods) to find local (and hopefully global) minima. The end results of all these folds are amalgamated to produce a graph like this:-



So it hinges on what is meant by "These models are then recombined to create new population(s) of models iteratively." Like I said, doesn't sound "GA - y"

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Yes, that is a description of how GAs work. However, in the case of Rosetta they use simulated annealing methods (rather than GA methods) to find local (and hopefully global) minima. The end results of all these folds are amalgamated to produce a graph like this:-



So it hinges on what is meant by "These models are then recombined to create new population(s) of models iteratively." Like I said, doesn't sound "GA - y"

Maybe they should try a real GA rather than simulated annealing. The problem though with GA in this case is the "cost function". How are they going to define a cost function for a model?

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Yes, that is a description of how GAs work. However, in the case of Rosetta they use simulated annealing methods (rather than GA methods) to find local (and hopefully global) minima. The end results of all these folds are amalgamated to produce a graph like this:-
(snipped)

So it hinges on what is meant by "These models are then recombined to create new population(s) of models iteratively." Like I said, doesn't sound "GA - y"

Maybe they should try a real GA rather than simulated annealing. The problem though with GA in this case is the "cost function". How are they going to define a cost function for a model?

Crudely speaking, you use the energy that Rosetta calculates for that particular fold. However in practice this doesnt work perfectly as the energy calculations are, in places, approximated (for speed) and also not fully understood. Proteins also can have multiple low energy states in different shapes. Also things like pH can cause conformational change. Lastly to illustrate, I was discussing this at the Gecco conference in Madrid last summer, and I was told of a time that Rosetta was given a sequence and a fold (derived from crystallography) and Rosetta calculated it could lower the energy further. This is probably wrong as you can be pretty sure the natural fold is the lowest energy, pointing to the likely possibility that the calculations are imperfect

Crudely speaking, you use the energy that Rosetta calculates for that particular fold. However in practice this doesnt work perfectly as the energy calculations are, in places, approximated (for speed) and also not fully understood. Proteins also can have multiple low energy states in different shapes. Also things like pH can cause conformational change. Lastly to illustrate, I was discussing this at the Gecco conference in Madrid last summer, and I was told of a time that Rosetta was given a sequence and a fold (derived from crystallography) and Rosetta calculated it could lower the energy further. This is probably wrong as you can be pretty sure the natural fold is the lowest energy, pointing to the likely possibility that the calculations are imperfect

i'm noob in these, but i'm thinking that a lower energy fold minima may in some cases be possible but it may 1st need to transit to a 'higher energy' barrier to reach an even lower energy minima. if this is true i'd guess nature may after all settle for 'higher energy' minima? lol

i'm noob in these, but i'm thinking that a lower energy fold minima may in some cases be possible but it may 1st need to transit to a 'higher energy' barrier to reach an even lower energy minima. if this is true i'd guess nature may after all settle for 'higher energy' minima? lol

The answer to that is "maybe" and "it depends". Its certainly possible there is an activation energy type barrier blocking its access to a lower overall energy state. More likely though is that there are multiple low energy states and in fact biology utilises these various states with their associated conformational changes for biological purposes. Haemaglobin is the first that springs to mind, although there are thousands of examples.

Dont think Rosetta is really geared up to identify multiple states, but may be wrong....