PMTPred is developed to predict the Protein Methyltransferases (PMTs) with high accuracy using machine-learning approach. PMTs constitute a class of enzymes that catalyze the methylation of lysine or arginine residues on histones and non-histones proteins. A number of PMTs have been directly associated with the pathogenesis of diseases such as human cancers, inflammatory diseases, neurodegenerative diseases etc.

PMTPred is standalone software package for the prediction of PMTs. SVM-based prediction model was developed using optimal feature set having best prediction accuracy. Optimal feature set include composition of k-spaced amino acid pairs (CKSAAP) as an input feature. For a given query protein sequence, PMTPred predicts its class with prediction probability score. This software could be used to fast and accurate prediction and large scale annotation project for the PMTs with high speed and without any specific need of software installation.

Workflow of PMTPred