Text Mining Improves Prediction of Protein Functional Sites

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions

Outbreak of H3N2 influenza at a US military base in Djibouti during the H1N1 pandemic of 2009.

PMC3855413BACKGROUND: Influenza pandemics have significant operational impact on deployed military personnel working in areas throughout the world. The US Department of Defense global influenza-like illness (ILI) surveillance network serves an important role in establishing baseline trends and can be leveraged to respond to outbreaks of respiratory illness. OBJECTIVE: We identified and characterized an operationally unique outbreak of H3N2 influenza at Camp Lemonnier, Djibouti occurring simultaneously with the H1N1 pandemic of 2009 [A(H1N1)pdm09]. METHODS: Enhanced surveillance for ILI was conducted at Camp Lemonnier in response to local reports of a possible outbreak during the A(H1N1)pdm09 pandemic. Samples were collected from consenting patients presenting with ILI (utilizing a modified case definition) and who completed a case report form. Samples were cultured and analyzed using standard real-time reverse transcriptase PCR (rt-RT-PCR) methodology and sequenced genetic material was phylogenetically compared to other published strains. RESULTS: rt-RT-PCR and DNA sequencing revealed that 25 (78%) of the 32 clinical samples collected were seasonal H3N2 and only 2 (6%) were A(H1N1)pdm09 influenza. The highest incidence of H3N2 occurred during the month of May and 80% of these were active duty military personnel. Phylogenetic analysis revealed that sequenced H3N2 strains were genetically similar to 2009 strains from the United States of America, Australia, and South east Asia. CONCLUSIONS: This outbreak highlights challenges in the investigation of influenza among deployed military populations and corroborates the public health importance of maintaining surveillance systems for ILI that can be enhanced locally when needed.JH Libraries Open Access Fun

Structure and Biological Activities of Beta Toxin from Staphylococcus aureus▿ †

Beta toxin is a neutral sphingomyelinase secreted by certain strains of Staphylococcus aureus. This virulence factor lyses erythrocytes in order to evade the host immune system as well as scavenge nutrients. The structure of beta toxin was determined at 2.4-Å resolution using crystals that were merohedrally twinned. This structure is similar to that of the sphingomyelinases of Listeria ivanovii and Bacillus cereus. Beta toxin belongs to the DNase I folding superfamily; in addition to sphingomyelinases, the proteins most structurally related to beta toxin include human endonuclease HAP1, Escherichia coli endonuclease III, bovine pancreatic DNase I, and the endonuclease domain of TRAS1 from Bombyx mori. Our biological assays demonstrated for the first time that beta toxin kills proliferating human lymphocytes. Structure-directed active site mutations show that biological activities, including hemolysis and lymphotoxicity, are due to the sphingomyelinase activity of the enzyme