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Members of the ATP-binding cassette (ABC) transporter family are present in three kingdoms of life and play a vital role in most cellular functions. ABC transporters function as either importers that bring nutrients and other molecules into cells, or as exporters that pump toxins, drugs and lipids across membranes. Currently, the limitation of 3D structures highlights the importance of the functional annotation for transporters using bioinformatics-based methods. In this work, we focused on annotation of substrate specificity for ABC transporters. Three types of the subunit proteins of ABC transporters, namely permease protein, ATP-binding protein and substrate binding protein all contribute much to the transport process, but have unique structures and properties. However previous computational methods have only considered the three subunit proteins in the same way and cannot individually characterize each type of subunit protein. Here, through individual feature evaluation and selection, specific representation for each type of subunit protein was implemented. Then three subunit-specific models were built to consistently analyse four major classes of ABC transporters with different transport targets. Our method achieved a 5-fold cross validation accuracy of 93.35%, 84.34%, 87.24% and 81.96% for sugar transporter, ion transporter, amino acid/protein transporter and others, respectively. Our method also showed an overall prediction accuracy of 88.02% with a Mathew's correlation coefficient of 0.6736 on an independent dataset. The results suggest that considering three subunit proteins separately and developing individual models for three substrate protein groups are recommendable. This method would be an effective tool for computational annotation of substrate specificity for ABC transporters.