Identification of Disease-Related 2-Oxoglutarate/Fe (II)-Dependent Oxygenase Based on Reduced Amino Acid Cluster Strategy

Abstract

The 2-oxoglutarate/Fe (II)-dependent (2OG) oxygenase superfamily is mainly responsible for protein modification, nucleic acid repair and/or modification, and fatty acid metabolism and plays important roles in cancer, cardiovascular disease, and other diseases. They are likely to become new targets for the treatment of cancer and other diseases, so the accurate identification of 2OG oxygenases is of great significance. Many computational methods have been proposed to predict functional proteins to compensate for the time-consuming and expensive experimental identification. However, machine learning has not been applied to the study of 2OG oxygenases. In this study, we developed OGFE_RAAC, a prediction model to identify whether a protein is a 2OG oxygenase. To improve the performance of OGFE_RAAC, 673 amino acid reduction alphabets were used to determine the optimal feature representation scheme by recoding the protein sequence. The 10-fold cross-validation test showed that the accuracy of the model in identifying 2OG oxygenases is 91.04%. Besides, the independent dataset results also proved that the model has excellent generalization and robustness. It is expected to become an effective tool for the identification of 2OG oxygenases. With further research, we have also found that the function of 2OG oxygenases may be related to their polarity and hydrophobicity, which will help the follow-up study on the catalytic mechanism of 2OG oxygenases and the way they interact with the substrate. Based on the model we built, a user-friendly web server was established and can be friendly accessed at http://bioinfor.imu.edu.cn/ogferaac.

Analysis of the 2OG‐Fe (II) oxygenase family reveals new insights associated with flowering regulation in Saccharum spontaneum

“…Our results are consistent with previous studies that showed 2OG‐Fe (II) oxygenases are involved in various aspects of plant development in O. sativa and A. thaliana , especially flowering (Low et al., 2020; Steinbauer et al., 2018; Zhou et al., 2021). A recent study on barley revealed that a 2OG‐Fe (II) oxygenase gene ( HvDMR6 ) is a functional ortholog of A. thaliana DMR6 , which is required for floral organ development (Low et al., 2020).…”

Research progress of reduced amino acid alphabets in protein analysis and prediction

“…In recent years, we successively constructed iDEF-PseRAAC, RaacLogo, RaacBook, OGFE-RAAC and other protein analysis and prediction platforms based on RAA alphabets, which enriched the application scope of RAA alphabets and emphasized the important role of simplified amino acid composition in sequence-structure–function ( Fig. 1 D and Table 1 ) [12] , [13] , [14] , [15] , [59] .…”

“…The simplified amino acid composition greatly reduces the dimensions of traditional feature engineering, effectively suppresses the negative effects of noise, and provides the model with richer biological prior knowledge to extract key features [12] , [13] . In addition, it is highly inclusive and has good compatibility with many existing methods, which helps to promote the further integration of traditional machine learning and biology [14] , [15] .…”

Genomic diversity and biogeographic distributions of a novel lineage of bacteriophages that infect marine OM43 bacteria

“…The prevalence of genes encoding these two proteins suggests that they may play a vital role in these phages; however, their specific functions remain to be explored. The 2OG-Fe(II) oxygenase superfamily is typically involved in the oxidation of organic substrate using a dioxygen molecule, which is mainly responsible for protein modification, nucleic acid repair and/or modification, and fatty acid metabolism ( 60 , 61 ). Fe-S cluster participates in a wide variety of cellular biological processes ( 62 ).…”