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Theory:
• Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the secondary structures of proteins and nucleic acid sequences based only on knowledge of their primary structure.
• For proteins, this means predicting the formation of protein structures such as alpha helices and beta strands, while for nucleic acids it means predicting the formation of nucleic acid structures like helixes and stem-loop structures through base pairing and base stacking interactions.
• Protein structure prediction is the prediction of the three-dimensional structure of a protein from its amino acid sequence that is the prediction of its secondary, tertiary, and quaternary structure from its primary structure. Structure prediction is fundamentally different from the inverse problem of protein design.
• Protein structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry, it is highly important in medicine and biotechnology.
• PHD are neural network systems (a sequence-to-structure level and a structure-structure level)to predict secondary structure (PHDsec), relative solvent accessibility (PHDacc) and transmembrane helices (PHDhtm).
• PHDsec focuses on predicting hydrogen bonds. The use of the evolutionary information held by a multiple sequence alignment increases the prediction accuracy. In the Predict Protein server, all is done with BLASTP and MaxHom. MaxHom filters the BLASTP result with a profile-based multiple alignment method.
• The PHD prediction done with NPS@ is better than the PHD prediction on the single sequence. But it's not exactly the same and could be a little bit less accurate than the Predict Protein one.
Procedure:
• Respective protein sequences of human cox2 (NP_000954.1) in Fasta format was retrieved from NCBI (ncbi.nlm.nih.gov).
• Log in to http://npsa-pbil.ibcp.fr/cgi-bin/npsa_au...a_phd.html
• Paste the respective sequences in the given input boxes.
• Click run.
• Results were displayed as soon as the given job completed.