Prediction of protein secondary structure based on residue pairs

Abstract

The GOR program for predicting protein secondary structure is extended to include triple correlation. A score system for a residue pair to be at certain conformation state is derived from the conditional weight matrix describing amino acid frequencies at each position of a window flanking the pair under the condition for the pair to be at the fixed state. A program using this score system to predict protein secondary structure is established. After training the model with a learning set created from PDB\_SELECT, the program is tested with two test sets. As a method using single sequence for predicting secondary structures, the approach achieves a high accuracy near 70%.