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Feature extraction is one of the most important preprocessing steps in predicting the interactions between RNAs and proteins by applying machine learning approaches. Despite many efforts in this area, still, no suitable structural feature extraction tool has been designed. Therefore, an online toolbox, named RPINBASE which can be applied to different scopes of biological applications, is introduced in this paper. This toolbox employs efficient nested queries that enhance the speed of the requests and produces desired features in the form of positive and negative samples. To show the capabilities of the proposed toolbox, the developed toolbox was investigated in the aptamer design problem, and the obtained results are discussed. RPINBASE is an online toolbox and is accessible at http://rpinbase.com. • Generating queryable positive samples from PDB complexes • Generating queryable artificial proposed negative samples (based on family and clan) • Providing a wide range of extracted features for primary and secondary structures of RNA and protein macromolecules. • Selecting efficient and high performance dataset powered by preprocessed and stored data to download feature vectors quickly. • Possibility of sample filtering by PDB information and structural features of macromolecules. [ABSTRACT FROM AUTHOR]