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Designing Proteins In Silico
Fluorophore writes "In a recent issue of the scientific journal Nature, scientists in the lab of Homme Hellinga at Duke University reported designing proteins using a cluster of 20 computers. These proteins were then tested in the lab and shown to bind their intended targets including TNT, serotonin and lactate. This is a tremendous step for computational biology, nicely reviewed in C&E News' top story. Designer proteins such as this can be developed for bioremediation of weapons dump sites (TNT) and sensitive sensors of drugs/contaminants that can easily be grown in bacteria."
One of the mantra of proteomics is that structure equals function. So increasing protien function increases the exactness of what structure must be.
Creating a self replicating protien would require insertion of a encoding sequence of dna of the host. And the self replication would involve that protien doing something like functioning as a promoter for that sequence, thus requiring a portion of the structure of the protien be able to recognize a specific sequence of DNA.
Creating a malicous or beneficial protien indicates that it has a specific target (such as a specific receptor on the HIV protien coat). This also requires a specific structure to be able to recognize that.
The problem with computationally designing a protien that both self replicates and serves a malicious or beneficial purpose is that the computation involved increases exponentially when adding a new function to a protien.
This is because you may get a structure that works well for one of the two targets, but then you have to check it against the other target, and it may work horribly for that second one. So then you repeat the cycle until you find something that works well for both.
So while it is technically correct that they could do it, it's going to be a difficult thing to do by computational methods (and probably even harder by conventional methods).
While this is a big step forward, it is not a humongous breakthrough. The big accomplishment is that the proteins were engineered to bind to socially relevent substate. There has been success in protein engineering for quite a while. Two big researchers are Stephen Mayo at CalTech ( http://www.mayo.caltech.edu ) and William DeGrado at the University of Pennsylvania. The true holy grail of this field is to create a functional protein from the ground up i.e. predict the three dimensinal structure from the amino acid sequence.
Well put. If your analysis of the paper is correct I am surprised that the paper was accepted to Nature. Nature Structure or Nature Biotechnology would have been more appropriate. Now if they had gotten significant levels of enzymatic activity then I would be impressed. However, your math for the interacting amino acid residues while probably correct can be dealt with with various algorithms. Namely the Dead-End Elimination algorithm, which if I recall, will, with accurate rotamer library, elimate all possible combinations of interacting rotamers and thus energetically unfavorable amino-acid combinations. This I believes seeks a desired global energy minimum and a cuts down on the overhead of needless computational paths.