Objective To investigate whether recombinant human growth hormone (rhGH) reduces mortality and protects against Staphylococcus aureus sepsis-induced acute lung injury. Methods The bacteria-positive rate of blood smears and bacteria colony counts in bacteria plate culture, TNFa and IL-10 plasma levels, lung injury score, expression of intercellular adhesion molecule-1 (ICAM-1) as well as activation of nuclear factor-kappa B (NF-jB) in the lungs were determined 6, 12 and 24 h after 140 KM mice were injected with physiologic saline (i.p. group C, n = 20); S. aureus E311122 (1.75 9 10 12 cfu/L, 40 ml/kg, i.p. group S, n = 60); or S. aureus (as group S) with a subsequent treatment of rhGH (1.0 U kg -1 day -1 ), i.m. group T, n = 60). The cumulative survival rate of an additional 15 mice from each group was followed for 7 days post S. aureus injection. Results rhGH treatment significantly increased IL-10 plasma levels and the 7-day cumulative survival rate, whereas the bacteria-positive rate of blood smears, bacteria colony counts in bacteria plate cultures, lung injury score, ICAM-1 and NF-jB expression in the lungs were significantly reduced. In addition, rhGH treatment significantly suppressed the S. aureus sepsis-induced elevation of TNFa plasma levels.Conclusions These results indicate an ability of rhGH to prevent S. aureus sepsis-induced acute lung injury in mice, which may be attributed to attenuation of increased plasma TNFa levels, and elevated IL-10 plasma levels as well as reduced ICAM-1 expression and inhibited NF-jB activity in the lungs.

Squalene synthase (SQS) is the key precursor in the synthesis of cholesterol. Located downstream in relation to hydroxy methylglutaryl coenzyme A reductase and having no influence on the formation of biologically necessary isoprenoids make it an interesting target for the development of cholesterol lowering drugs with fewer side effects. To discover novel SQS inhibitors, three-dimensional quantitative structure-activity relationship pharmacophore models were built and further validated by cost function analysis, test set validation, and decoy set validation to obtain a reliable model for virtual screening against a database that contains 5.5 million compounds. The interactions between SQS and the ligands were predicted by an integrated protocol that contains molecular docking, molecular mechanics/generalized born surface area, and molecular dynamic simulation. After that, five compounds with best binding affinities and binding modes were obtained as potential hits for further study and three of them showed inhibitory effects against SQS.KEYWORDS binding free energy, molecular dynamic simulation, pharmacophore model, SQSIs, virtual screening Manzhou Hou and Guoyi Yan contributed equally to this work.

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