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Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

An L-amino acid oxidase from Peruvian Bothrops pictus (Bpic-LAAO) snake venom was purified using a combination of size-exclusion and ion-exchange chromatography. Bpic-LAAO is a homodimeric glycosylated flavoprotein with molecular mass of ∼65 kDa under reducing conditions and ∼132 kDa in its native form as analyzed by SDS-PAGE and gel filtration chromatography, respectively. N-terminal amino acid sequencing showed highly conserved residues in a glutamine-rich motif related to binding substrate. The enzyme exhibited optimal activity towards L-Leu at pH 8.5, and like other reported SV-LAAOs, it is stable until 55 °C. Kinetic studies showed that the cations Ca 2+ , Mg 2+ and Mn 2+ did not alter Bpic-LAAO activity; however, Zn 2+ is an inhibitor. Some reagents such as β-mercaptoethanol, glutathione and iodoacetate had inhibitory effect on Bpic-LAAO activity, but PMSF, EDTA and glutamic acid did not affect its activity. Regarding the biological activities of Bpic-LAAO, this enzyme induced edema in mice (MED = 7.8 μg), and inhibited human platelet aggregation induced by ADP in a dose-dependent manner and showed antibacterial activity on Gram (+) and Gram (-) bacteria. Bpic-LAAO cDNA of 1494 bp codified a mature protein with 487 amino acid residues comprising a signal peptide of 11 amino acids. Finally, the phylogenetic tree obtained with other sequences of LAAOs, evidenced its similarity to other homologous enzymes, showing two well-established monophyletic groups in Viperidae and Elapidae families. Bpic-LAAO is evolutively close related to LAAOs from B. jararacussu, B. moojeni and B. atrox, and together with the LAAO from B. pauloensis, form a well-defined cluster of the Bothrops genus., (Copyright © 2017 Elsevier Ltd. All rights reserved.)