Heating with Steam Methane Reformed Hydrogen

Hydrogen produced from natural gas with steam methane reforming coupled with carbon capture and sequestration (SMRCCS) is proposed as fuel for consumer heating and cooking systems. This paper presents estimates of the energy losses and methane and carbon dioxide emission and global warming across the whole gas to hydrogen heat supply chain – from production to consumer. Processed natural gas is typically about 95% methane which is a potent greenhouse gas with a global warming potential (GWP) such that, with 20 year and 100 year GWP horizons, about 4% and 8% leakage respectively will cause as much global warming as the carbon dioxide formed when burning the methane. Data on gas emissions and SMRCCS costs and performance are sparse and wide ranging and this presents a major problem in accurately appraising the possible role of hydrogen from methane. The survey indicates emissions between 50 and 200 gCO2eq per unit of heat (kWhth) for SMRCCS H2 heat depending on leakage and GWP time horizon assumed. The second part of the paper reviews gas supply pricing and security and presents a cost minimised configuration of a SMRCCS hydrogen heating system derived with a simple model. Uncertainty in SMRCCS greenhouse gas emissions coupled with a net zero emission target and the long term issue of the physical and economic security of natural gas supply, bear on the potential advantages of SMRCCS as compared to other options, such as heating with renewable electricity driving consumer or district heating heat pumps

SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information

Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces generate reliable models without the need for complex software packages or downloading large databases. Here, we describe the latest version of the SWISS-MODEL expert system for protein structure modelling. The SWISS-MODEL template library provides annotation of quaternary structure and essential ligands and co-factors to allow for building of complete structural models, including their oligomeric structure. The improved SWISS-MODEL pipeline makes extensive use of model quality estimation for selection of the most suitable templates and provides estimates of the expected accuracy of the resulting models. The accuracy of the models generated by SWISS-MODEL is continuously evaluated by the CAMEO system. The new web site allows users to interactively search for templates, cluster them by sequence similarity, structurally compare alternative templates and select the ones to be used for model building. In cases where multiple alternative template structures are available for a protein of interest, a user-guided template selection step allows building models in different functional states. SWISS-MODEL is available at http://swissmodel.expasy.org/

SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information

Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces generate reliable models without the need for complex software packages or downloading large databases. Here, we describe the latest version of the SWISS-MODEL expert system for protein structure modelling. The SWISS-MODEL template library provides annotation of quaternary structure and essential ligands and co-factors to allow for building of complete structural models, including their oligomeric structure. The improved SWISS-MODEL pipeline makes extensive use of model quality estimation for selection of the most suitable templates and provides estimates of the expected accuracy of the resulting models. The accuracy of the models generated by SWISS-MODEL is continuously evaluated by the CAMEO system. The new web site allows users to interactively search for templates, cluster them by sequence similarity, structurally compare alternative templates and select the ones to be used for model building. In cases where multiple alternative template structures are available for a protein of interest, a user-guided template selection step allows building models in different functional states. SWISS-MODEL is available at http://swissmodel.expasy.or

Modelling cofactors in comparative protein structure models by evolutionary inference

Proteins perform their role through the interactions they establish with other proteins and with small molecules, like ions or organic cofactors. The identification of these partners and of the mechanisms involved in their functional interactions can provide helpful insights into the molecular details of the protein annotation and for the development of new drugs. As many proteins lack of experimental structures and of annotated ligands, computational methods are required in order to predict these details and to guide the direction of experimental investigation. In this context, our main aim is to enhance protein functional annotation and to improve comparative models by inferring their potential binding cofactors. Moreover, we want to evaluate the current state-of-the-art methods for binding site prediction in order to understand their advantages and limitations for future developments. Additionally, we aimed to improve the assessment of binding site prediction methods by creating an automated system of continuous model evaluation. Finally, we created a new binding site descriptor for the de novo ligand and binding site prediction in protein models. The content of this thesis is organized as follows. Chapter 1 introduces protein structure, binding sites and experimental techniques for structure determination; moreover, we illustrate the current approaches to model protein structures and to predict their ligand binding sites. In chapter 2, we describe the assessment of the ligand binding site predictions within the 9th edition of the Critical Assessment of protein Structure Prediction (CASP) experiment, while in chapter 3 we discuss the latest developments in the 10th round. Within chapter 4 we illustrate the evolution of this assessment into the Continuous Automated Model EvaluatiOn (CAMEO) Ligand Binding category and we describe the homology predictor, which is used as reference for the comparison of the other methods registered to CAMEO. Chapter 5 presents the new SWISS-MODEL server, which employs a base ligand modelling pipeline to place potential small molecules partners, inferred from the target’s template, into the built models. Motivated by the performances of the previous method and by the results seen in the last CASP editions, in chapter 6 we present a new method to model ligands, especially ions and organic cofactors, into comparative models; this approach is based on the analysis of the similarities between a target and its homologous proteins. In chapter 7, we describe a novel descriptor for ligand binding sites, based on moment invariants and developed for the de novo prediction of ligands. Finally, in chapter 8 we draw the general conclusions of the work presented in this thesis

Osteoporosis and lactose intolerance

<p>A) Recombination pattern (according to jpHMM) of the URF_0206 (15228_1_49) discovered in the ICONIC dataset and the sequences L39106 and AF064699, prototypes of the recombinants CRF02_AG and CRF06_cpx, respectively. B) Bootscanning analysis of the URF_0206 performed using SimPlot and diagram showing the definitive recombination pattern.</p