Development of Residue Look-Up Tables and Graphical Representation of Solvent Accessibility in Proteins
نویسندگان
چکیده
We previously developed the first method to predict real valued accessible surface area in proteins, which was shown to contain more information than 100% correct predictions in a binary space of exposure states. Neural networks used for solvent accessibility predictions, however work as good predictors with invisible modeling of knowledge they learn. In view of this a direct statistical analysis of solvent accessibility of residues was desired, in terms of the contribution of residue neighbors in making them buried or exposed to solvent. Present work aims at compiling singlet to quintets of residue fragments and examining, how the solvent accessibility of residues is affected by the change in a neighboring residue in C-terminal, N-terminal or other positions of these residues. In addition, a graphical method of representing solvent accessibility was developed. Online graphical plots for all proteins in the entire Protein Data Bank (PDB) were made available on the web at www.netasa.org/ asa-view/.
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