From the gating charge response to pore domain movement: Initial motions of Kv1.2 dynamics under physiological voltage changes

Abstract

Recent structures of the potassium channel provide an essential beginning point for explaining how the pore is gated between open and closed conformations by changes in membrane voltage. Yet, the molecular details of this process and the connections to transmembrane gradients are not understood. To begin addressing how changes within a membrane environment lead to the channel’s ability to sense shifts in membrane voltage and to gate, we performed double-bilayer simulations of the Kv1.2 channel. These double-bilayer simulations enable us to simulate realistic voltage drops from resting potential conditions to depolarized conditions by changes in the bath conditions on each side of the bilayer. Our results show how the voltage sensor domain movement responds to differences in transmembrane potential. The initial voltage sensor domain movement, S4 in particular, is modulated by the gating charge response to changes in voltage and is initially stabilized by the lipid headgroups. We show this response is directly coupled to the initial stages of pore domain motion. Results presented here provide a molecular model for how the pre-gating process occurs in sequential steps: Gating charge response, movement and stabilization of the S4 voltage sensor domain, and movement near the base of the S5 region to close the pore domain.     

An integrated network analysis reveals that nitric oxide reductase prevents metabolic cycling of nitric oxide by Pseudomonas aeruginosa

Nitric oxide (NO) is a chemical weapon within the arsenal of immune cells, but is also generated endogenously by different bacteria. Pseudomonas aeruginosa are pathogens that contain an NO-generating nitrite (NO₂⁻) reductase (NirS), and NO has been shown to influence their virulence. Interestingly, P. aeruginosa also contain NO dioxygenase (Fhp) and nitrate (NO₃⁻) reductases, which together with NirS provide the potential for NO to be metabolically cycled (NO→NO₃⁻→NO₂⁻→NO). Deeper understanding of NO metabolism in P. aeruginosa will increase knowledge of its pathogenesis, and computational models have proven to be useful tools for the quantitative dissection of NO biochemical networks. Here we developed such a model for P. aeruginosa and confirmed its predictive accuracy with measurements of NO, O₂, NO₂⁻, and NO₃⁻ in mutant cultures devoid of Fhp or NorCB (NO reductase) activity. Using the model, we assessed whether NO was metabolically cycled in aerobic P. aeruginosa cultures. Calculated fluxes indicated a bottleneck at NO₃⁻, which was relieved upon O₂ depletion. As cell growth depleted dissolved O₂ levels, NO₃⁻ was converted to NO₂⁻ at near-stoichiometric levels, whereas NO₂⁻ consumption did not coincide with NO or NO₃⁻ accumulation. Assimilatory NO₂⁻ reductase (NirBD) or NorCB activity could have prevented NO cycling, and experiments with ΔnirB, ΔnirS, and ΔnorC showed that NorCB was responsible for loss of flux from the cycle. Collectively, this work provides a computational tool to analyze NO metabolism in P. aeruginosa, and establishes that P. aeruginosa use NorCB to prevent metabolic cycling of NO.     

Synthesis,Molecular Modeling,and Biological Evaluation of Novel Chiral Thiosemicarbazone Derivatives as Potent Anticancer Agents

A series of new chiral thiosemicarbazones derived from homochiral amines in both enantiomeric forms were synthesized and evaluated for their in vitro antiproliferative activity against A549 (human alveolar adenocarcinoma), MCF‐7 (human breast adenocarcinoma), HeLa (human cervical adenocarcinoma), and HGC‐27 (human stomach carcinoma) cell lines. Some of compounds showed inhibitory activities on the growth of cancer cell lines. Especially, compound 17b exhibited the most potent activity (IC₅₀ 4.6 μM) against HGC‐27 as compared with the reference compound, sindaxel (IC₅₀ 10.3 μM), and could be used as a lead compound to search new chiral thiosemicarbazone derivatives as antiproliferative agents. Chirality 27:177–188, 2015. © 2014 Wiley Periodicals, Inc.     

Effects of Organic Solvents on the Coupling Between ATP Hydrolysis and Sliding of Microtubules in Axonemes from Chlamydomonas Flagella

ABSTRACT. The effects of organic solvents on the ATPase activity and the sliding disintegration of axonemes from Chlamydomonas were investigated. The axonemal ATPase was markedly activated by methanol accompanying with marked inhibition of the sliding disintegration of axonemes. On the contrary, glycerol inhibited the ATPase activity without serious inhibition of the sliding disintegration. As far as the axonemes are not irreversibly denatured by extremely high concentration of solvents, the effects of solvents both on the ATPase and the ability of sliding are reversible. Therefore, the inhibition of sliding accompanied by the activation of ATPase is probably due to an inability to couple the hydrolysis of ATP to sliding between dynein and microtubule in the presence of methanol. The axonemal ATPase was less sensitive to vanadate inhibition after exposure to methanol. This indicates that methanol makes the dyneinADP.Pi complex unstable and increases product release. On the other hand, glycerol and ethylene glycol seem to stabilize the force generation responsible for the sliding through stabilizing the dynein.ADP.Pi complex.     

The Treatment of Missing Values in Logistic Regression

The efficiencies of the estimators in the linear logistic regression model are examined using simulations under six missing value treatments. These treatments use either the maximum likelihood or the discriminant function approach in the estimation of the regression coefficients. Missing values are assumed to occur at random. The cases of multivariate normal and dichotomous independent variables are both considered. We found that in general, there is no uniformly best method. However, mean substitution and discriminant function estimation using existing pairs of values for correlations turn out to be favourable for the cases considered.     

The Monofactorial Model for Recurrence Risks with Generalized Penetrance

Recurrence risks are derived explicitly in terms of gene frequencies and penetrance coefficients for the general case in which all genotypes have incomplete penetrance. Maximum likelihood estimation of recurrence risks is achieved through the use of the semi-symmetric intraclass contingency table. The resulting formulas and estimation procedure can be useful for the analysis of population and family data, and in genetic counselling.