Indexing and mapping of proteins using a modified nonlinear Sammon projection

Abstract

A modified Sammon algorithm was developed to display a relationship between proteins based on their amino acid composition. In the first stage of the method, a 19-dimensional compositional space of representative proteins was mapped into a 2-dimensional space (2-D) using the original Sammon projection creating a contour map. In the second stage, this contour map was used as a reference for new proteins projected into 2-D. Data analysis showed that proteins belonging to the same structural classes formed characteristic and distinct clusters, which could be potentially useful in the prediction of protein structural classes. However, we observed significant overlapping of the clusters which may explain the limited success of previous protein folding prediction based solely on amino acid composition. Regardless, the modified Sammon projections can generate a unique index for each individually projected protein related to its amino acid composition, which may be a useful tool in the exploratory classification of proteins.