Lipids modulate the conformational dynamics of a secondary multidrug transporter

Direct interactions with lipids have emerged as key determinants of the folding, structure and function of membrane proteins, but an understanding of how lipids modulate protein dynamics is still lacking. Here, we systematically explored the effects of lipids on the conformational dynamics of the proton-powered multidrug transporter LmrP from Lactococcus lactis, using the pattern of distances between spin-label pairs previously shown to report on alternating access of the protein. We uncovered, at the molecular level, how the lipid headgroups shape the conformational-energy landscape of the transporter. The model emerging from our data suggests a direct interaction between lipid headgroups and a conserved motif of charged residues that control the conformational equilibrium through an interplay of electrostatic interactions within the protein. Together, our data lay the foundation for a comprehensive model of secondary multidrug transport in lipid bilayers

Backbone NMR reveals allosteric signal transduction networks in the β1-adrenergic receptor

G protein-coupled receptors (GPCRs) are physiologically important transmembrane signalling proteins that trigger intracellular responses upon binding of extracellular ligands. Despite recent breakthroughs in GPCR crystallography1–3, the details of ligand induced signal transduction are not well understood owing to missing dynamical information. In principle, such information can be provided by NMR4, but so far only limited data of functional relevance on few side-chain sites of eukaryotic GPCRs have been obtained 5–9. Here we show that receptor motions can be followed at virtually any backbone site in a thermostabilized mutant of the turkey β1-adrenergic receptor (β1AR) 10–12. Labelling with [15N] valine in a eukaryotic expression system provides over twenty resolved resonances that report on structure and dynamics in six ligand complexes and the apo form. The response to the various ligands is heterogeneous in the vicinity of the binding pocket, but gets transformed into a homogeneous readout at the intracellular side of helix 5 (TM5), which correlates linearly with ligand efficacy for the G protein pathway. The effect of several pertinent, thermostabilizing point mutations was assessed by reverting them to the native sequence. Whereas the response to ligands remains largely unchanged, binding of the G protein mimetic nanobody NB80 and G protein activation are only observed when two conserved tyrosines (Y227 and Y343) are restored. Binding of NB80 leads to very strong spectral changes throughout the receptor, including the extracellular ligand entrance pocket. This indicates that even the fully thermostabilized receptor undergoes activating motions in TM5, but that the fully active state is only reached in presence of Y227 and Y343 by stabilization with a G protein-like partner. The combined analysis of chemical shift changes from the point mutations and ligand responses identifies crucial connections in the allosteric activation pathway, and presents a general experimental method to delineate signal transmission networks at high resolution in GPCRs

Probabilistic risk assessment of radiotherapy application

The recent rapid development and increasing complexity of radiotherapy devices and applications has increased the importance of correct and safe treatment. Risk management is very important in radiotherapy (RT), because incorrect treatment can have serious consequences in terms of mortality or morbidity. However, there are currently few studies on risk analysis in RT. This quantitative and qualitative study of the radiotherapy system (all radiotherapy process) uses the fault tree method, one of the probabilistic risk assessment methods in radiotherapy applications, which is used to devise accident preventive actions. First of all, RT applications were divided into simulation, treatment planning and treatment delivery. For each, work flow charts were determined, and fault trees were created in SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations) software. Fault probabilities were determined using the expert judgment method. This analysis allowed the identification of the weak points of the system, both qualitatively and quantitatively. The analyzes also revealed that there was a 0.5% occurrence probability of a top event, determined as an incorrect dose or dose distribution in RT. It was determined that the greatest contribution to this probability value was matching error with image guidance, 7.88%. Fault tree analysis (FTA) was found to facilitate a detailed examination of the radiotherapy system. After the risk analysis, the appropriate quality control method for weak points should be determined and implemented for safety management in radiotherapy

Probabilistic risk assessment of radiotherapy application

The recent rapid development and increasing complexity of radiotherapy devices and applications has increased the importance of correct and safe treatment. Risk management is very important in radiotherapy (RT), because incorrect treatment can have serious consequences in terms of mortality or morbidity. However, there are currently few studies on risk analysis in RT. This quantitative and qualitative study of the radiotherapy system (all radiotherapy process) uses the fault tree method, one of the probabilistic risk assessment methods in radiotherapy applications, which is used to devise accident preventive actions. First of all, RT applications were divided into simulation, treatment planning and treatment delivery. For each, work flow charts were determined, and fault trees were created in SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations) software. Fault probabilities were determined using the expert judgment method. This analysis allowed the identification of the weak points of the system, both qualitatively and quantitatively. The analyzes also revealed that there was a 0.5% occurrence probability of a top event, determined as an incorrect dose or dose distribution in RT. It was determined that the greatest contribution to this probability value was matching error with image guidance, 7.88%. Fault tree analysis (FTA) was found to facilitate a detailed examination of the radiotherapy system. After the risk analysis, the appropriate quality control method for weak points should be determined and implemented for safety management in radiotherapy