by eanrsmoMIRACLE FRP TOOL V1.49 | 135 Model Added | [Latest] ✊🏿
MIRACLE FRP TOOL V1.49 | 135 Model Added | [Latest]
The final version of the product is, as far as I know, the same as the published paper. It is a good paper and one I can recommend. It is even the perfect use case of the AlphaFold2 package, with a continuous double helix with some added features. I have two points, though: (1) the authors are perfectly aware of this, and (2) my recommendations are based in part on the fact that no one had ever heard of this paper or had ever seen the tool. My recommendations are thus somewhat biased by the fact that no one but the authors has seen the tool.
After nearly a year of waiting, the paper is finally out. The authors reported that the AlphaFold2 model can predict the tertiary structure with an RMSD of 3.4 Å, which is about what we predicted from our analysis of the data. Given that the authors did a full 10,000-residue sequence search (where we did not), that finding is very good. (However, we did predict the structure of the β-blob for an enzyme, something they do not do.)
This is an important paper for the community of researchers doing protein research, and for all of the readers of this blog. It is a survey of the predictive accuracy of ProteinContact, and two other tools, PDBe and pdb2pqr . In the paper they show (I think) that our methods are the best of the three, a bit better than PDBe. (I did not check the table in the manuscript, but I think that they looked at this and found similar results, although they didn’t call it that.
The diagram above also shows how AlphaFold 2 was able to learn a set of features that distinguish myoglobin proteins, including those that are not evolutionarily related, from the MSA. The model learned that the proteins that contain valine or leucine at position 15 of position 47 are preferentially slightly acidic and therefore larger than the proteins that contain isoleucine. The model also learned that valine-containing proteins are more compact than isoleucine-containing ones, and leucine-containing proteins are less angular than isoleucine-containing ones. And the model learned that more compactness was positively correlated with the position of the protein in the hierarchy.
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