Scores of amino acid 0D-3D information as applied in cleavage site prediction and better specificity elucidation for human immunodeficiency virus type 1 protease

Abstract

A new set of descriptors, namely score vectors of the zero dimension, one dimension, two dimensions and three dimensions (SZOTT), was derived from principle component analysis of a matrix of 1369 structural variables including 0D, 1D, 2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis (LDA) and support vector machines (SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis (LDA) and support vector machines (SVM) are as follows. The Matthews correlation coefficients (MCC) by the resubstitution test, leave-one-out cross validation (LOOCV) and external validation are 0.879 and 0.911, 0.849 and 0.901, 0.822 and 0.846, respectively. The receiver operating characteristic (ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.