Produces a structural similarity PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/27321907 score [11,16,17]. The Dali Database includes structural comparisons where Mangafodipir (trisodium) chemical information proteins from PDB90, a subset of the PDB where no two proteins share more than 90 sequence similarity, were used as queries against the full PDB [46]. For this study, we took into consideration all human proteins that were listed in the Dali database as being similar to an HIV-1 protein (NCBI Taxonomy ID: 11676) and having a z score above 2.0, with the HIV-1 protein being either the PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28192408 query or the hit. We refer to these human proteins as “HIV-similar” proteins. No proteins of unknown structure were considered.Interaction PredictionWe found known interactions between HIV-similar proteins and target human proteins, using data from theTo reduce the number of predictions as well as add information from functional studies, predictions were filtered based on previous implication of the human protein’s involvement in the HIV-1 infection process. One criterion was presence of the host protein in the HIV-1 virion. Host proteins known to be incorporated into or onto HIV-1 during budding were taken from several literature sources [23,24,47]. The presence of host proteins in or on HIV-1 may be a result of specific recruitment and serve a functional role, may result from localization of the protein near the site of budding, or may simply occur by chance. Predicted interactions between HIV-1 proteins and human proteins that are incorporated into the HIV-1 virion were retained. In addition, any human protein that is incorporated into the virion and is itself structurally similar to an HIV-1 protein was also included as a possible interaction. Another filtering criterion was the host protein’s essentiality for HIV-1 infection. Recently, several large-scale experiments using siRNA or shRNA knockdowns to identify host proteins involved in the HIV-1 life cycle have been published [19-22]. The probe ids of the genes implicated by Yeung et al. were mapped to their Entrez Gene IDs using the appropriate Affymetrix annotation file http://www.affymetrix.com/products_services/ arrays/specific/hgu133plus.affx#1_4[22]. This filter is referred to as the “Literature Filter.” Host proteins that were implicated in at least one of these studies as having a possible role in HIV-1 infection or replication, and which are also known to interact with an HIV-similar protein, were predicted to interact with an HIV-1 protein in the final predicted network. To create a smaller and potentially more reliable list for further experimental validation, we further filtered the predictions based on shared sub-cellular localization. The Cellular Component (CC) Filtered dataset contains interaction predictions where the two proteins share Gene Ontology (GO) cellular component annotation. Pairs of HIV-1 and human proteins predicted to interact were only included in this dataset if both proteins were annotated by DAVID as being present in the same cellular compartment [41,42]. Pairs with only the terms “cell” and “cell part” in common were excluded due to a large num-Doolittle and Gomez Virology Journal 2010, 7:82 http://www.virologyj.com/content/7/1/Page 12 ofber of such pairs and the relative lack of specificity of these high level terms.Validation of PredictionsSince within Dali there may be multiple PDB structures representing the same protein, there is some redundancy in the interaction predictions. In certain cases, multiple PDB structures for the same HIV-1 protein were found.