A review ofin silicoapproaches for analysis and prediction of HIV-1-human protein–protein interactions <s> The HIV-1-human protein interaction network <s> The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein‐protein interactions, post-translational modifications, enzyme‐substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease. <s> BIB001 </s> A review ofin silicoapproaches for analysis and prediction of HIV-1-human protein–protein interactions <s> The HIV-1-human protein interaction network <s> The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions, was created to catalog all interactions between HIV-1 and human proteins published in the peer-reviewed literature. The database serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. To facilitate this discovery approach, the following information for each HIV-1 human protein interaction is provided and can be retrieved without restriction by web-based downloads and ftp protocols: Reference Sequence (RefSeq) protein accession numbers, Entrez Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. Currently, 2589 unique HIV-1 to human protein interactions and 5135 brief descriptions of the interactions, with a total of 14 312 PMID references to the original articles reporting the interactions, are stored in this growing database. In addition, all protein–protein interactions documented in the database are integrated into Entrez Gene records and listed in the ‘HIV-1 protein interactions’ section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication. <s> BIB002
The National Institute of Allergy and Infectious Diseases has published the 'HIV1-Human Protein Interaction Database' (HHPID) BIB002 in 2009 . This database provides a concise but detailed summary of all known interactions including their brief descriptions. It is a valuable resource for the HIV-1 research community. The database was made publicly available at NCBIs website, http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/ in 2009. The HHPID database provides comprehensive data consisting of 5127 interactions between 19 HIV-1 proteins and 1432 human proteins (January, 2013). This curated database was constructed from approximately 3200 papers published between 1984 and 2007 and was validated by being linked to several publications. Over 14 312 PMID references to the original articles were collected for validating all the interactions in this growing database BIB002 . Moreover, each interaction is associated with a specific interaction type like 'upregulate', 'activate', 'bind', 'inhibited by' etc. A visualization of this database can be seen in Figure 2 . We have extensively searched and found 68 unique interaction types among the 5127 interactions. The bipartite network shown in Figure 2a is constructed from this data set and consists of 19 red nodes, which represent HIV-1 proteins, and 1432 green nodes, which represent human proteins. We broadly divide all the interaction types into regulatory classes: regulating, regulated by and bidirectional (regulation is in both ways), where the three classes contain 34, 25 and 9 interaction types, respectively. We create three subnetworks, each corresponding to an interaction class. Figure 2b-d) show interaction types of the three classes, respectively. The degree distribution in each subnetwork approximately obeys power law i.e. the number of nodes with large degree values are less frequent, whereas the number of nodes with lower degree values are more frequent. Following the distribution of interaction types in each subnetwork, 'upregulates', 'inhibits', 'downregualates', 'activates', 'binds', 'interacts with', 'inhibited by' and 'processed by' seem to be more common interactions in HHPID. Additionally, a significant number of interactions are observed to be associated with class-1 regulation type than the other two types of regulations. To understand which of the subnetworks mimics the topological properties of the whole HIV-1-human bipartite network, we plot relative degree of HIV-1 proteins in each subnetwork against the whole bipartite network. This is shown in Figure 3 . It is evident from the figure that there is a strong correlation between degree of subnetwork 1 or subnetwork 2 and the global network (R 2 ¼ 0.9949 and 0.9895 for subnetwork 1 and subnetwork 2, respectively). The fitted regression line (R 2 ¼ 0.8104) for subnetwork 3, which is constructed by considering the class 3 type of interactions, asserts the existence of correlation in degree between subnetwork 3 and the whole bipartite network but not so closely as subnetwork 1 and subnetwork 2. This suggests that the relative degree of HIV-1 proteins retain the same pattern strongly in subnetwork 1 and in subnetwork 2. We have also studied degree and betweenness centrality distributions of HIV-1 interacting human proteins specific to each of these three subnetworks. For this purpose we collect the human PPI data set from Human Protein Reference Database (HPRD) BIB001 , which consists of 39,240 interactions among 9589 human proteins. Figure 4a and b show, respectively, the degree and betweenness centrality distribution of HIV-1 interacting human proteins belonging to the three subnetworks in the corpus of entire human PPI network. The motivation behind this is to see to what extent the HIV-1 interacting human proteins, associated with specific type of regulation, are connected in the whole human PPI network. Not surprisingly, no such significant difference is observed in degree and betweenness centrality pattern. This suggests that the topological characteristics of HIV-1 interacting human proteins are weakly correlated with specific regulation type. Review on analysis and prediction of HIV-1-human PPI | 833 A review on HIV-1-human PPI network analysis approaches Here we have reviewed several pioneering works dedicated to the broad analysis of the HIV-1-human protein interaction network. Since 2009 with the introduction of HHPID data set, several works are published that use this data set from different perspectives. Almost all of them primarily focus on building a bipartite network constituting HIV-1 and human proteins as nodes and interactions between them as edges. The created network is analysed to gain a deeper insight into the HIV research that includes HIV-host perturbation, biological importance of the host proteins that show strong association with specific HIV interactions, different interaction patterns of host proteins with HIV-1 proteins and several other issues. The works we have reviewed in this section use the HHPID data set as well as use different data sources that are integrated with HHPID.