Distinctive amino acid residue periodicities in terminal sequences of type III and type I secreted proteins from proteobacteria

Abstract

Abstract:The Fourier transform (FT) method was applied to specify the distribution of 14 predefined groups of amino acids (64 residues) at both termini of annotated type III and type I secreted proteins from proteobacteria. Type I proteins displayed a higher occurrence of significant periodicities at both C-and N-termini, indicating potent features to discriminate between secretion types, particularly by the use of variables selected from the full periodicity profiles at 19 orders of FT. The Fishers linear discriminant analysis, together with the stepwise selection of variables throughout equal pairs of combinations for all predefined groups of residues, revealed the C-terminal harmonics of aromatic (HFWY) and aliphatic (VLIA) residues as a set of strong predictor variables to classify both types of secreted proteins with an accuracy of 100% for original grouped cases and 96.4% for cross-validated grouped cases. The prediction accuracy of proposed discriminant function was estimated by repeated kfold cross-validation procedures where the original data set was randomly divided into k subsets, with one of the k-subsets serving as the test set and the remaining data forming the training set. The average error rate computed across all k-trials and repeats did not exceed that of leave-one-out procedure. The proposed set of predictor variables could be used to assess the compatibility between secretion pathways and secretion substrates of proteobacteria by means of discriminant analysis.

Distinctive attributes for predicted secondary structures at terminal sequences of non-classically secreted proteins from proteobacteria

“…The clusters of most effective predictor variables, i.e. the sets of property values at definite positions of numerical vectors that represent the secondary structures at C-termini of sequences (Table 3) were elucidated by the procedures of stepwise forward and backward selection [11].…”

“…The methods of multiple and Fisher's linear discriminant analysis [27][28][29] were applied using the software SPSS 11.0 for Windows (SPSS Inc., Ill., USA) and Statgraphics ® Plus (Manugistics Inc., Mar., USA) to find the appropriate combination of positional structural indices that gave the maximum ratio between the classes of annotated extracellular proteins. The procedures of forward and backward selection of variables to obtain a combination with a strong discriminatory power were employed throughout the study as described previously [11]. The measure of Press's Q statistics [28] was employed as a statistical test for the discrimination power of the classification matrix as described earlier [11] and above the critical values of Chi-square distribution (6.64 for p ≤ 0.01, 1 df) the estimates of classification accuracy were recognized to be significant.…”

“…The procedures of forward and backward selection of variables to obtain a combination with a strong discriminatory power were employed throughout the study as described previously [11]. The measure of Press's Q statistics [28] was employed as a statistical test for the discrimination power of the classification matrix as described earlier [11] and above the critical values of Chi-square distribution (6.64 for p ≤ 0.01, 1 df) the estimates of classification accuracy were recognized to be significant.…”

“…Estimates of prediction accuracy were calculated for the models by means of k-fold (k = 3; 4; 6; 8; 10) cross-validation (KCV) [30] including the leave-one-out (LOOCV) procedure when as the extreme case of KCV where k was equal to the total numbers of proteins in the original data set (Table 1) [11].…”

“…Nevertheless, these methods do not specify any certain secretion type presumably involved in non-classical protein secretion. Recently we proposed definite amino acid (R, E, G, I, M, P, S, Y, V) frequencies [10] and the periodic patterns of aliphatic (A, L, I, V) and aromatic (H, F, W, Y) amino acids near the C-termini of sequences [11] and these variables were strong predictor variables to discriminate between annotated type I and type III proteins secreted form proteobacteria. On the other hand, several compositional and structural features at the N-and C-termini of the sequences have been proposed as possible determinants for secretion signals of nonclassically secreted proteins [1][2][3]5,6,12].…”