Predicting residue solvent accessibility from protein sequence by considering the sequence environment

The solvent accessibility of each residue is predicted on the basis of the protein sequence. A set of 338 monomeric, non-homologous and high-resolution protein crystal structures is used as a learning set and a jackknife procedure is applied to each entry. The prediction is based on the comparison of the observed and the average values of the solvent-accessible area. It appears that the prediction accuracy is significantly improved by considering the residue types preceding and/or following the residue whose accessibility must be predicted. In contrast, the separate treatment of different secondary structural types does not improve the quality of the prediction. It is furthermore shown that the residue accessibility is much better predicted in small than in larger proteins. Such a discrepancy must be carefully considered in any algorithm for predicting residue accessibility.