Prediction of secondary structures of proteins using the sequence and spectroscopical data

An algorithm is presented which modifies the parameter of given methods of prediction of secondary protein structures by comparing the predictions with the frequency of secondary structures derived from infrared spectra in a way that the predictions align to the given data. Depending on the prediction method and accuracy of the given secondary structures a 1-6% increase in accuracy can be reached. The algorithm compares the difference between the predicted and real frequency of a given secondary structure in the protein and modifies accordingly the parameter used in the prediction method in order to give a new, more accurate prediction. A correlation between the accuracy of the prediction and increasing correctness between the prediction and infrared data was found using a set of 39 proteins.