Browsing by Author "Chen, Bo"

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    An integrated clinico-metabolomic model improves prediction of death in sepsis
    (American Association for the Advancement of Science, 2013) Langley, Raymond J.; Tsalik, Ephraim L.; van Velkinburgh, Jennifer C.; Glickman, Seth W.; Rice, Brandon J.; Wang, Chunping; Chen, Bo; Carin, Lawrence; Suarez, Arturo; Mohney, Robert P.; Freeman, Debra H.; Wang, Mu; You, Jinsam; Wulff, Jacob; Thompson, J. Will; Moseley, M. Arthur; Reisinger, Stephanie; Edmonds, Brian T.; Grinnell, Brian; Nelson, David R.; Dinwiddie, Darrell L.; Miller, Neil A.; Saunders, Carol J.; Soden, Sarah S.; Rogers, Angela J.; Gazourian, Lee; Fredenburgh, Laura E.; Massaro, Anthony F.; Baron, Rebecca M.; Choi, Augustine M. K.; Corey, G. Ralph; Ginsburg, Geoffrey S.; Cairns, Charles B.; Otero, Ronny M.; Fowler, Vance G., Jr.; Rivers, Emanuel P.; Woods, Christopher W.; Kingsmore, Stephen F.; Medicine, School of Medicine
    Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would ultimately die differed markedly from those of patients who would survive. The different profiles of proteins and metabolites clustered into the following groups: fatty acid transport and β-oxidation, gluconeogenesis, and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of five metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.
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    Monte Carlo Simulations of HIV Capsid Protein Homodimer
    (ACS, 2015-06) Zhu, Fangqiang; Chen, Bo; Department of Physics, School of Science
    Capsid protein (CA) is the building block of virus coats. To help understand how the HIV CA proteins self-organize into large assemblies of various shapes, we aim to computationally evaluate the binding affinity and interfaces in a CA homodimer. We model the N- and C-terminal domains (NTD and CTD) of the CA as rigid bodies and treat the five-residue loop between the two domains as a flexible linker. We adopt a transferrable residue-level coarse-grained energy function to describe the interactions between the protein domains. In seven extensive Monte Carlo simulations with different volumes, a large number of binding/unbinding transitions between the two CA proteins are observed, thus allowing a reliable estimation of the equilibrium probabilities for the dimeric vs monomeric forms. The obtained dissociation constant for the CA homodimer from our simulations, 20–25 μM, is in reasonable agreement with experimental measurement. A wide range of binding interfaces, primarily between the NTDs, are identified in the simulations. Although some observed bound structures here closely resemble the major binding interfaces in the capsid assembly, they are statistically insignificant in our simulation trajectories. Our results suggest that although the general purpose energy functions adopted here could reasonably reproduce the overall binding affinity for the CA homodimer, further adjustment would be needed to accurately represent the relative strength of individual binding interfaces.