AI Article Synopsis
- The Src Homology 2 (SH2) domain is crucial for protein-protein interactions related to signal transmission, typically involving phosphotyrosine motifs.
- We developed a deep learning method to distinguish between proteins that have SH2 domains and those that don’t, using a database of protein sequences from various species.
- Our analysis identified a 288-dimensional feature model that effectively differentiates these proteins and discovered a new motif, YKIR, which plays a significant role in signal transduction within organisms.
Article Abstract
The Src Homology 2 (SH2) domain plays an important role in the signal transmission mechanism in organisms. It mediates the protein-protein interactions based on the combination between phosphotyrosine and motifs in SH2 domain. In this study, we designed a method to identify SH2 domain-containing proteins and non-SH2 domain-containing proteins through deep learning technology. Firstly, we collected SH2 and non-SH2 domain-containing protein sequences including multiple species. We built six deep learning models through DeepBIO after data preprocessing and compared their performance. Secondly, we selected the model with the strongest comprehensive ability to conduct training and test separately again, and analyze the results visually. It was found that 288-dimensional (288D) feature could effectively identify two types of proteins. Finally, motifs analysis discovered the specific motif YKIR and revealed its function in signal transduction. In summary, we successfully identified SH2 domain and non-SH2 domain proteins through deep learning method, and obtained 288D features that perform best. In addition, we found a new motif YKIR in SH2 domain, and analyzed its function which helps to further understand the signaling mechanisms within the organism.
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| http://dx.doi.org/10.1016/j.compbiomed.2023.107065 | DOI Listing |
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