Shatabda Swakkhar, Saha Sanjay, Sharma Alok, Dehzangi Abdollah
Department of Computer Science and Engineering, United International University, House 80, Road 8A, Dhanmondi, Dhaka-1209, Bangladesh.
Institute for Integrated and Intelligent Systems, Griffith University, Australia; School of Engineering and Physics, University of the South Pacific, Fiji; RIKEN Center for Integrative Medical Sciences, Japan.
J Theor Biol. 2017 Dec 21;435:229-237. doi: 10.1016/j.jtbi.2017.09.022. Epub 2017 Sep 21.
Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very important to know the subcellular location of the phage proteins in a host cell in order to understand their working mechanism. In this paper, we propose iPHLoc-ES, a prediction method for subcellular localization of bacteriophage proteins. We aim to solve two problems: discriminating between host located and non-host located phage proteins and discriminating between the locations of host located protein in a host cell (membrane or cytoplasm). To do this, we extract sets of evolutionary and structural features of phage protein and employ Support Vector Machine (SVM) as our classifier. We also use recursive feature elimination (RFE) to reduce the number of features for effective prediction. On standard dataset using standard evaluation criteria, our method significantly outperforms the state-of-the-art predictor. iPHLoc-ES is readily available to use as a standalone tool from: https://github.com/swakkhar/iPHLoc-ES/ and as a web application from: http://brl.uiu.ac.bd/iPHLoc-ES/.
噬菌体蛋白是能够对细菌功能产生重大影响的病毒，可用于基于噬菌体的治疗。噬菌体在宿主细菌中的功能取决于其在这些宿主细胞中的位置。了解噬菌体蛋白在宿主细胞中的亚细胞定位对于理解其作用机制非常重要。在本文中，我们提出了iPHLoc-ES，一种用于预测噬菌体蛋白亚细胞定位的方法。我们旨在解决两个问题：区分位于宿主内和非宿主内的噬菌体蛋白，以及区分位于宿主细胞内的蛋白的位置（膜或细胞质）。为此，我们提取噬菌体蛋白的进化和结构特征集，并采用支持向量机（SVM）作为分类器。我们还使用递归特征消除（RFE）来减少特征数量以进行有效预测。在使用标准评估标准的标准数据集上，我们的方法显著优于现有最佳预测器。iPHLoc-ES可以从以下网址作为独立工具轻松使用：https://github.com/swakkhar/iPHLoc-ES/ ，也可以从以下网址作为网络应用程序使用：http://brl.uiu.ac.bd/iPHLoc-ES/ 。
