PROFALIGN algorithm identifies the regions containing folding determinants by scoring pairs of hydrophobic profiles...

Profile comparison methods have been shown to be very powerful in creating accurate alignments of protein sequences, especially in the case of remotely related proteins (RRP). These methods take advantage of the observation that hydrophobic profiles are more conserved than the corresponding amino acid sequences. Here, we present the PROFALIGN algorithm, which allows one to perform a detailed comparative analysis, at both local and global levels of two protein sequence profiles. The user can either choose among four different hydrophobic scales (Miyazawa-Jernigan, Eisenberg, Engelman-Steiz, and Kyte-Doolittle) or can add a personal scale. The interface is designed for a wide range of users, including those who are not involved in protein research. It allows one to vary the alignment parameters (such as gap penalties, embedding, and profile smoothness). Secondary structure propensity is added as an optional alignment filter. Similar segments of two proteins are singled out on the basis of score. We have tested the algorithm with different Src homology 3 (SH3) domain fragments sharing low sequence homology but very similar three-dimensional (3D) structures. By using the Miyazawa-Jernigan hydrophobic scale, PROFALIGN was able to detect the strong correlation between the regions that are known to be crucial for SH3 transition state topology. PROFALIGN seems able to identify most of the mutual alignment of structures on the basis of their hydrophobic profiles, delimiting the regions containing the key determinants of folding. Therefore, the present methodology may be useful for the detection of the most structurally relevant positions inside remote related proteins.