Title: A complete review of computational methods for human and HIV-1 protein interaction prediction
Authors: Debasmita Pal; Kartick Chandra Mondal
Addresses: Department of Information Technology, Jadavpur University, Kolkata, West Bengal, India ' Department of Information Technology, Jadavpur University, Kolkata, West Bengal, India
Abstract: Human Immunodeficiency Virus Type 1 (HIV-1) has grabbed the attention of virologists in recent times owing to its life-threatening nature and epidemic spread throughout the globe. The virus exploits a complex interaction network of HIV-1 and human proteins for replication, and causes destruction to the human immunity power. Antiviral drugs are designed to utilise the information on viral-host Protein-Protein Interactions (PPIs), so that the viral replication and infection can be prevented. Therefore, the prediction of novel interactions based on experimentally validated interactions, curated in the public PPI database, could help in discovering new therapeutic targets. This article gives an overview of HIV-1 proteins and their role in virus-replication followed by a discussion on different types of antiretroviral drugs and HIV-1-human PPI database. Thereafter, we have presented a brief explanation of different computational approaches adopted to predict new HIV-1-human PPIs along with a comparative study among them.
Keywords: HIV-1 proteins; antiretroviral drugs; human proteins; interaction prediction; association rules mining; protein-protein interactions; PPIs; virus replication; HIV.
International Journal of Bioinformatics Research and Applications, 2016 Vol.12 No.1, pp.19 - 46
Received: 26 Jan 2015
Accepted: 04 Aug 2015
Published online: 19 Mar 2016 *