MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction - Yin, Xi; Yang, Jing; Xiao, Feng; Yang, Yang; Shen, Hong-Bin (Nano-Micro Letters, 2017)
Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein’s structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A TMH, 87.1% of A P, 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. Highlights: 1 MemBrain is a fully automatic online tool for transmembrane protein structure prediction, which is able to predict the irregular half-transmembrane helix. 2 MemBrain’s theoretic predictions provide timely and important clues for further wet-lab experiments.