AUTHOR=Ahmed Zahoor , Zulfiqar Hasan , Khan Abdullah Aman , Gul Ijaz , Dao Fu-Ying , Zhang Zhao-Yue , Yu Xiao-Long , Tang Lixia 

TITLE=iThermo: A Sequence-Based Model for Identifying Thermophilic Proteins Using a Multi-Feature Fusion Strategy

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.790063

DOI=10.3389/fmicb.2022.790063

ISSN=1664-302X

ABSTRACT=Thermophilic proteins have important application value in biotechnology and industrial processes. The correct identification of thermophilic proteins provides important information for the application of these proteins in engineering. The identification method of thermophilic proteins based on biochemistry is laborious, time-consuming and high cost. Therefore, there is an urgent need for a fast and accurate method to identify thermophilic proteins. Considering this urgency, we constructed a reliable benchmark dataset containing 1368 thermophilic and 1443 non-thermophilic proteins. A multi lawyer perceptron (MLP) model based on multi-feature fusion strategy was proposed to discriminate thermophilic proteins from non-thermophilic proteins. On independent data set, the proposed model could achieve the accuracy of 96.26%, which proves that the model has a good application prospect. In order to use the model conveniently, a user-friendly software package called iThermo was established and can be freely accessed at http://lin-group.cn/server/iThermo/index.html. The high accuracy of the model and the practicability of the developed software package indicate that this study can accelerate the discovery and engineering application of thermal stable proteins.