Predicting Interactions between Virus and Host Proteins Using Repeat Patterns and Composition of Amino Acids

Alguwaizani, Saud; Park, Byungkyu; Zhou, Xiang; Huang, De-Shuang; Han, Kyungsook

So far, many computational methods have been developed to predict PPIs. However, most of these methods predict PPIs within a single species and cannot be used to predict PPIs between different species because they do not distinguish interactions between proteins of the same species from those of different species. Recently, a few computational methods have been developed to predict virus-host PPIs using machine learning methods. For instance, a homology-based method [3] predicts PPIs between H. sapiens and M. tuberculosis H37Rv. Support vector machine (SVM) models developed by Cui et al. [4] and Kim et al. [5] predicted PPIs between human and two types of viruses (hepatitis C virus and human papillomavirus). However, these methods are intended for PPIs between virus of a single type and host of a single type. Recent computational methods developed for predicting virus-host PPIs [6] [7] [8] are also limited to PPIs between human and the human immunodeficiency virus 1 (HIV-1) and cannot predict PPIs of new viruses or new hosts which have no known PPIs to the methods. A recent SVM model called DeNovo can exceptionally predict PPIs of new viruses with a shared host [9] .