DeepDRBP-2L: A New Genome Annotation Predictor for Identifying DNA-Binding Proteins and RNA-Binding Proteins Using Convolutional Neural Network and Long Short-Term Memory

DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two kinds of crucial proteins, which are associated with various cellule activities and some important diseases. Accurate identification of DBPs and RBPs facilitate both theoretical research and real world application. Existing sequence-based DBP predictors can accurately identify DBPs but incorrectly predict many RBPs as DBPs, and vice versa, resulting in low prediction precision. Moreover, some proteins (DRBPs) interacting with both DNA and RNA play important roles in gene expression and cannot be identified by existing computational methods. In this study, a two-level predictor named DeepDRBP-2L was proposed by combining Convolutional Neural Network (CNN) and the Long Short-Term Memory (LSTM). It is the first computational method that is able to identify DBPs, RBPs and DRBPs. Rigorous cross-validations and independent tests showed that DeepDRBP-2L is able to overcome the shortcoming of the existing methods and can go one further step to identify DRBPs. Application of DeepDRBP-2L to tomato genome further demonstrated its performance. The webserver of DeepDRBP-2L is freely available at http://bliulab.net/DeepDRBP-2L.

1 Introduction

DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two kinds of important proteins which play crucial roles in various biological processes, such as DNA replication, transcriptional control, chromatin stability and modification, epigenetic regulation, posttranscriptional gene regulation, alternative splicing, translation, etc. [1], [2], [3]. They have important functions for some diseases, such as cancer [4], myeloid leukaemia [3], [5]. Furthermore, some proteins (DRBPs) can bind to both DNA and RNA, which also play important roles in gene expression [3]. Accurate identification of DBPs, RBPs and DRBPs is significantly meaningful.