Here we propose a predictor for drug-target interactions based on the Nearest Neighbor algorithm [34] . Since biochemical and physicochemical features [35] are important for characterizing proteins, in this study they are used to represent proteins as done by many previous investigators (see, e.g., [36, 37, 38] . To improve the predictor's performance, minimum Redundancy Maximum Relevance (mRMR) algorithm [39] is used to rank the features. Meanwhile, the Incremental Feature Selection and Forward Feature Selection are applied for feature selection. The protein targets for drugs are divided into enzymes, ion channels [40, 41, 42, 43] , GPCRs [44, 45] , and nuclear receptors [14] in this study. Finally, four predictors for predicting the interactions of drugs with each of the four protein families are developed in hopes that they can help provide useful information for drug design.