AUTHOR=Zhang Zhaoxi , Wang Juan , Liu Jiameng TITLE=DeepRTCP: Predicting ATP-Binding Cassette Transporters Based on 1-Dimensional Convolutional Network JOURNAL=Frontiers in Cell and Developmental Biology VOLUME=8 YEAR=2021 URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2020.614080 DOI=10.3389/fcell.2020.614080 ISSN=2296-634X ABSTRACT=

ATP-binding cassette (ABC) transporters can promote cells to absorb nutrients and excrete harmful substances. It plays a vital role in the transmembrane transport of macromolecules. Therefore, the identification of ABC transporters is of great significance for the biological research. This paper will introduce a novel method called DeepRTCP. DeepRTCP uses the deep convolutional neural network and a feature combined of reduced amino acid alphabet based tripeptide composition and PSSM to recognize ABC transporters. We constructed a dataset named ABC_2020. It contains the latest ABC transporters downloaded from Uniprot. We performed 10-fold cross-validation on DeepRTCP, and the average accuracy of DeepRTCP was 95.96%. Compared with the start-of-the-art method for predicting ABC transporters, DeepRTCP improved the accuracy by 9.29%. It is anticipated that DeepRTCP can be used as an effective ABC transporter classifier which provides a reliable guidance for the research of ABC transporters.