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April 24th, 2024: NPS@ updated (see NEWS).

A brief introduction to SOPMA
SOPMA (Self-Optimized Prediction Method with Alignment) is an improvement of SOPM method. These methods are based on the homologue method of Levin et al.. The improvement takes place in the fact that SOPMA uses information from a multiple sequence alignment (MSA) of protein belonging to the same family. If there are no homologous sequences the SOPMA prediction is the SOPM one.
Warning : It can be long to compute. So, be careful when using it in alignment (or it will exceed the NPS@'s maximum computing time).
NPS@ is the original server for this method.

Availability in NPS@
This method is available :

• from a dedicated page
• in secondary structure prediction consensus
• in protein multiple sequence alignment:
  • KALIGN
  • MAFFT
  • MSUCLE
• when you work with a sequence in NPS@ if you make a consensus secondary structure prediction on it

Parameters
You can set the number of conformational states to predict : 3 or 4.
The window size parameter sets the length of the peptides to use. The similarity threshold parameter is the threshold below which a subject peptide is rejected when it's compared with a query peptide of the sequence.

NPS@ SOPMA output example
You can see:

• the color coded prediction (a sequence line and below the corresponding predicted states)
• the sequence length
• the percentage of each secondary element
• two graphics, the first summarize the prediction, the second contains the score curve for each predicted state
• the parameters used
• links to the prediction result text file and to intermediate result text files

References

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