New method for accurate prediction of solvent accessibility from protein sequence

Abstract

A novel method was developed for predicting the solvent accessibility. Based on single sequence data, this method achieved 71.5% accuracy with a correlation coefficient of 0.42 in a database of 704 proteins with threshold of 20% for a two-state-defining solvent accessibility. Prediction in a data subset of 341 monomeric proteins achieved 72.7% accuracy with a correlation coefficient of 0. 43. On the average, prediction over short chains gives better results than that over long chains. With a solvent accessibility threshold of 20%, prediction over 236 monomeric proteins with chain length < 300 amino acid residues achieved 75.3% accuracy with a correlation coefficient of 0.44 by jackknife analysis, which is higher than that obtained by previous methods using multiple sequence alignments.