A Two-step Similarity-based Method for Prediction of Drug's Target Group
Determination of drug's target protein is very important for studying drug-target interaction network, while drug-target interaction network is a key area in the drug discovery pipeline. Thus correct prediction of drug's target protein is very helpful to promote the development of drug discovery. In this study, we developed a two-step similarity-based method to predict drug's target group. In each step, a similarity score (obtained by graph representation in the first step, and chemical functional group representation in the second step) was employed to make prediction. Since some drugs can target proteins distributing in more than one group of proteins, the method provided a series of candidate target groups for each drug. As a result, the first-order prediction accuracy on training set and test set were 79.01% and 76.43%, respectively, which were much higher than the success rate of a random guess. The results show that using graph representation to encode drug is a good choice in this area. We expect that this contribution will provide some help to understand drugtarget interaction network.
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Document Type: Research Article
Publication date: March 1, 2013
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- Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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