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Abstract Summary: In chemoinformatics and bioinformatics fields, one of the main computational challenges in various predictive modeling is to find a suitable way to effectively represent the molecules under investigation, such as small molecules, proteins and even complex interactions. To solve this problem, we developed a freely available R/Bioconductor package, called Compound–Protein Interaction with R (Rcpi), for complex molecular representation from drugs, proteins and more complex interactions, including protein–protein and compound–protein interactions. Rcpi could calculate a large number of structural and physicochemical features of proteins and peptides from amino acid sequences, molecular descriptors of small molecules from their topology and protein–protein interaction and compound–protein interaction descriptors. In addition to main functionalities, Rcpi could also provide a number of useful auxiliary utilities to facilitate the user’s need. With the descriptors calculated by this package, the users could conveniently apply various statistical machine learning methods in R to solve various biological and drug research questions in computational biology and drug discovery. Availability and implementation: Rcpi is freely available from the Bioconductor site ( http://bioconductor.org/packages/release/bioc/html/Rcpi.html ). Contact: oriental-cds@163.com
Cao et al. (Mon,) studied this question.