Conservation of Amino Acids into Multiple Alignments Involved in Pairwise Interactions in Three-Dimensional Protein Structures
We present an original strategy, that involves a bioinformatic software structure, in order to perform an exhaustive and objective statistical analysis of three-dimensional structures of proteins. We establish the relationship between multiple sequences alignments and various structural features of proteins. We show that amino acids implied in disulfide bonds, salt bridges and hydrophobic interactions are particularly conserved. Effects of identity, global similarity within alignments, and accessibility of interactions have been studied. Furthermore, we point out that the more variable the sequences within a multiple alignment, the more informative the multiple alignment. The results support multiple alignments usefulness for predictions of structural features.