ALPHAPRED: A server for prediction of alpha turns in proteins

Bioinformatics Centre,IMTECH, New Delhi, INDIA



The AlphaPred server predicts the alpha turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure. Two neural networks with a single hidden layer having 10 units have been used where the first sequence-to-structure network is trained on PSI-BLAST obtained position specific matrices. The filtering has been done using second structure-to-structure network trained on output of first net and PSIPRED predicted secondary structure. The training has been carried out using error backpropagation with a sum of square error function(SSE). The network is trained and tested on a set of 193 non-homologous protein chains with 5-fold cross-validation. It predicts alpha turns in proteins with prediction accuracy of 78.0% and MCC value of 0.16.

The input is a single letter-code amino acid sequence either in fasta or plain text. The residues in the query sequence predicted as alpha turns are marked as a and non-turn residues are marked as '.'. The PSIPRED predicted secondary structure (H: Helix; E: Strand and C: Coil) is displayed along with the predicted turn/non-turn results.

If you are using this server then please site Kaur H & Raghava GP. (2004). Prediction of alpha-turns in proteins using PSI-BLAST profiles and secondary structure information. Proteins. 55: 83-90



Bioinformatics Centre, Indraprastha Institute of Information Technology, New Delhi, INDIA