Background: Presynaptic and postsynaptic neurotoxins are two important categories of
neurotoxins. Due to the important role of presynaptic and postsynaptic neurotoxins in
pharmacology and neuroscience, their identification has become very important biologically.
Methods: In this study, statistical tests and F-scores were used to calculate differences between
amino acids and biological properties. The support vector machine was used to predict presynaptic
and postsynaptic neurotoxins using reduced amino acid alphabet types.
Results: Using the reduced amino acid alphabet as input parameters of the support vector machine,
the overall accuracy of our classifier increased to 91.07%, which was the highest overall accuracy
observed in this study. When compared with the other published methods, better predictive results
were obtained by our classifier.
Conclusion: In summary, we analyzed the differences between two neurotoxins with respect to
amino acids and biological properties, constructing a classifier that predicts these two neurotoxins
using the reduced amino acid alphabet.