Author:
Liu Zhe,Gong Yingli,Bao Yihang,Guo Yuanzhao,Wang Han,Lin Guan Ning
Abstract
Alpha transmembrane proteins (αTMPs) profoundly affect many critical biological processes and are major drug targets due to their pivotal protein functions. At present, even though the non-transmembrane secondary structures are highly relevant to the biological functions of αTMPs along with their transmembrane structures, they have not been unified to be studied yet. In this study, we present a novel computational method, TMPSS, to predict the secondary structures in non-transmembrane parts and the topology structures in transmembrane parts of αTMPs. TMPSS applied a Convolutional Neural Network (CNN), combined with an attention-enhanced Bidirectional Long Short-Term Memory (BiLSTM) network, to extract the local contexts and long-distance interdependencies from primary sequences. In addition, a multi-task learning strategy was used to predict the secondary structures and the transmembrane helixes. TMPSS was thoroughly trained and tested against a non-redundant independent dataset, where the Q3 secondary structure prediction accuracy achieved 78% in the non-transmembrane region, and the accuracy of the transmembrane region prediction achieved 90%. In sum, our method showcased a unified model for predicting the secondary structure and topology structure of αTMPs by only utilizing features generated from primary sequences and provided a steady and fast prediction, which promisingly improves the structural studies on αTMPs.
Subject
Biomedical Engineering,Histology,Bioengineering,Biotechnology
Reference58 articles.
1. Tensorflow: a system for large-scale machine learning;Abadi,2016
2. Neural optimizer search with reinforcement learning;Bello,2017
3. Prediction of membrane-protein topology from first principles;Bernsel;Proc. Natl. Acad. Sci. U.S.A.,2008
4. The PSIPRED protein analysis workbench: 20 years on;Buchan;Nucleic Acids Res.,2019
5. Protein Data Bank (PDB): the single global macromolecular structure archive;Burley;Methods Mol. Biol.,2017
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献