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Protein-Protein interactions discovered by the existing high-throughput techniques contain very high amount of false positives. Here we present an SVM based approach to generate a model that is built on sequence and non-sequence based information of the interacting proteins. This model is used to assess the reliability of given protein-protein interactions. It was run on the interaction data of a pathogenic bacterium; Treponema pallidum (causes Syphilis in humans) obtained from Yeast two hybrid experiments. Various kernels were used for building the model and of all, Sigmoid kernel performed well when used with all the features combined with area under the receiver operating curve (ROC) as 0.53.