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Prediction of \(\beta\)-lactamase and its class by Chou’s pseudo-amino acid composition and support vector machine. (English) Zbl 1314.92055
Summary: \(\beta\)-Lactam class of antibiotics is used as major therapeutic agent against a number of pathogenic microbes. The widespread and indiscriminate use of antibiotics to treat bacterial infection has prompted evolution of several evading mechanisms from the lethal effect of antibiotics. \(\beta\)-Lactamases are endogenously produced enzyme that makes bacteria resistant against \(\beta\)-lactam antibiotics by cleaving the \(\beta\)-lactam ring. On the basis of primary structures, \(\beta\)-lactamase family of enzymes is divided into four classes namely A, B, C and D. Class B are metallo-enzymes while A, C and D does not need any metal in the enzyme catalysis. In the present study we developed a SVM based two level \(\beta\)-lactamases protein prediction method, which differentiate \(\beta\)-lactamases from non-\(\beta\)-lactamases at first level and then classify predicted \(\beta\)-lactamases into different classes at second level. We evaluated performance of different input vectors namely simple amino acid composition, Type-1 and Type-2 Chou’s pseudo amino acid compositions. Comparative performances indicated that SVM model trained on Type-1 pseudo amino acid composition has the best performance. At first level we were able to classify \(\beta\)-lactamases from non-\(\beta\)-lactamases with 90.63% accuracy. At second level we found maximum accuracy of 61.82%, 89.09%, 70.91% and 70.91% of class A, class B, class C and class D, respectively. A web-server as well as standalone, PredLactamase, is also developed to make the method available to the scientific community, which can be accessed at

92C40 Biochemistry, molecular biology
92D20 Protein sequences, DNA sequences
Full Text: DOI
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