Dear All
I'm trying to predict secondary structure, disorder and solvent accessibility fo a protein. According to you, which support to my analysis could give the same predictions perfomed on some of homolog proteins?
Thanks in advance
Dear All
I'm trying to predict secondary structure, disorder and solvent accessibility fo a protein. According to you, which support to my analysis could give the same predictions perfomed on some of homolog proteins?
Thanks in advance
To get a general idea, I would recommed reading the Wikipedia article on secondary structure prediction. As a general rule, secondary structure prediction is relatively mature and thus able to assist a variety of analyses. With 3D structure, things get more complicated.
For a list of secondary structure prediction software, see this Wikipedia article. However, don't be disctracted by only the GOR method having its own article (it is quite old and not often used anymore). PSIPRED and PredictProtein are more modern approaches that are used nowadays (again, see the article for webserver links).
I'm not sure what you mean by disorder, so I'll leave that out (but I may edit later if you elaborate on that point).
For solvent accessibility, there are two method that are widely used as far as I know, which are SAS and SABLE.
Including information from homologs is the idea behind PSIPRED. Given that this is quite a famous and accepted method, the answer is: yes, this can support your predictions.
Besides PSIPRED and PredictProtein, I would also recommend Jpred. It is more than just a secondary structure prediction program. If you are making homology based model for example, and if the sequence identity of your model sequence is quite low with the template, you could use the alignment derived from Jpred and in that case the alignment is based on secondary structure. Besides predicting secondary structure, it also predicts solvent accessibility and coiled coil regions using Lupas method.
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Have you checked the CASP9 publication? They just assessed the best current methods for structure prediction.