Protein structure prediction | EPFL Graph Search

Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes). Starting in 1994, the performance of current methods is assessed biannually in the CASP experiment (Critical Assessment of Techniques for Protein Structure Prediction). A continuous evaluation of protein structure prediction web servers is performed by the community project CAMEO3D. Protein structure and terminology Proteins are chains of amino acids joined together by peptide bonds. Many conformations of this chain are possible due to the rotation of the main chain a

Flow Boiling of Carbon Dioxide at Different Channel Orientations for the Thermal Management of Future Detector Technologies at the High-Luminosity Large Hadron Collider at CERN

David Schmid

The global warming potential (GWP) of working fluids in thermodynamic cycles and their environmental impact have been gaining considerable attention within the recent years. The global objectives on climate protection are becoming increasingly ambitious, whereas the general demand for refrigeration appliances with enhanced cooling capacities is constantly growing all over the world. One promising approach to reconcile these contradictory expectations is the replacement of synthetic working fluids with natural refrigerants.The European Organization for Nuclear Research (CERN) supports the development of green technologies within the upgrades of their future accelerator facilities and Carbon Dioxide (CO2) has been identified as an eco-friendly candidate with excellent heat transfer characteristics that has the potential for replacing detrimental refrigerants in future scientific and industrial cooling applications. Inspired by the positive experiences with several mid-scale refrigeration systems, the ATLAS and CMS experiments decided to use CO2 as working fluid for the thermal management of their future Particle Tracker detectors requiring cooling capacities in the order of 0.5 MW.Pressure drop and heat transfer properties are key factors for designing thermodynamic cycles properly. Motivated by the lack of experimental data of flow boiling CO2 in vertical directions, a comprehensive research program has been launched to investigate the two-phase flow behaviour of CO2, in particular in vertical up- and downward direction. As a first step, a test facility to study the two-phase flow characteristics has been built. The setup allows measurements of the significant two-phase flow parameters in horizontal, vertical up- and downward direction in macro-scale pipes with inner diameters of 8 mm. The test conditions of the experiments cover saturation temperatures from -25 °C to +5 °C and the mass velocity ranges from 100 kg m^-2 s^-1 to 450 kg m^-2 s^-1.The performance of pressure drop models has been analyzed with data sets of 512 measurements in horizontal and 295 data points for each vertical up- and downflow direction respectively. 18 frictional pressure drop models have been compared to the horizontal data set and 21 void fraction correlations have been combined with the frictional pressure drop models accounting for the static head, resulting in 378 factorial combinations to anticipate the pressure losses in vertical directions. The best models have been identified for the entire data sets for all flow directions. Moreover, a subdivided analysis, split up according to the flow regimes, has been carried out to highlight the most accurate prediction methods with regard to the flow regimes.The heat transfer properties of flow boiling CO2 have been investigated in vertical upward direction with diabatic measurements of 5 kW m^-2 and 11 kW m^-2 respectively. The dryout phenomena is observed to be influenced by the heat flux, the mass velocity and the saturation temperature. To avoid operation at reduced heat transfer coefficients, a correlation to predict the dryout inception is suggested. The comparison of the data set to established prediction methods reveals, that the heat transfer coefficients of vertical upflow are generally underpredicted. As a consequence, an enhancement factor for vertical upflow of two-phase CO2 is suggested for two prediction models.

EPFL2022

Two strategies to improve transient gene expression in HEK293E and/or CHO-DG44 cells

Guillaume Lüthi

Transient gene expression (TGE) is based on episomal DNA expression. This technique is used for the production of recombinant proteins that can be used as therapeutics. TGE is for example extremely useful for shortening the time between candidate proteins screening and their production. Understanding and optimizing TGE is a major concern in the field of recombinant proteins. Thus, we selected here two different approaches to further improve TGE. First, we studied effect of signal peptide (SP) modification on TNFR-Fc protein in transiently transfected HEK293E and CHO-DG44 cells. Secondly, we studied effect of Valproic acid on the production of TNFR-Fc protein in HEK293E cells and on its influence on plasmid methylation. Modification of TNFR-Fc was done with eighteen others SPs. Artificial SPs exhibiting different scores using a prediction method and SPs coming from naturally secreted proteins were tested. None of them could induce a better secretion than the native SP. Nevertheless, they all showed comparable secretion abilities, except one that could not induce protein secretion. We showed here that SP modification could not increase protein secretion in HEK293E or in CHO-DG44. But also that without a valid SP, protein secretion is inhibited. Addition of VPA in HEK293E cells transfected with pXLG-A3 plasmid increased IgG productivity by 11 fold. Nevertheless, we showed here that VPA did not increase TNFR-Fc productivity to the same extent (1.2 fold) even by optimization of its concentration. Furthermore, we investigated the effect of plasmid methylation (TNFRFc and IgG) on TGE using VPA. We found that IgG expression was less influenced by this modification than TNFR-Fc. In fact, TNFR-Fc plasmid methylation drastically decreased specific productivity (0.2 fold). And VPA could almost entirely compensate this effect (0.8 fold). We therefore hypothesized that VPA has an impact on pDNA methylation in the context of TGE.

2011