Predicting functional sites in biological sequences using canonical correlation analysis

Protein functional site prediction plays a key role in understanding protein function and in protein engineering. In this work we developed a novel method using canonical correlation analysis to predict protein ligand binding sites. The method was tested with a well-known benchmark dataset and consistently outperformed the existing method Xdet, which is based on Pearson correlation, by improving the lowest and highest ranked positives for more than 18% and 22% respectively.