The Blue Obelisk Community

Poster presented at the VSMF symposium held at the Unilever Centre on 2011-01-17The Internet has brought together a group of chemists who are driven by wanting to do things better, but are frustrated with the Closed systems that chemists currently have to work with. they share a belief in the concepts of Open Data, Open Standards and Open Source. And they express this in software, data, algorithms, specifications, tutorials, demonstrations, articles and anything that helps get the message across. [http://www.blueobelisk.org/

Surface studies and density functional theory analysis of ruthenium polypyridyl complexes

In recent years, the computational method Density Functional Theory (DFT) has become more and more important as an effective tool for studying inorganic complexes. This thesis describes computational studies on ruthenium polypyridyltype complexes using DFT. An introduction to the theory behind DFT is presented in the first chapter, as well as a review of previous DFT studies on ruthenium polypyridyl-type complexes. The second chapter describes the details of the computational studies. This includes a description of the basis set, functional, and integration grid. This chapter also describes two pieces of in-house software: GaussSum written to process the output of the computational package Gaussian, and GauStock, which is used to calculate Hirshfeld atomic charges. Chapter 3 examines the electronic structure of a series of complexes related to [Ru(bpy)2(pytrz)]+. The calculated electronic structure is compared with results from experiment. Partial density of states (PDOS) spectra are used to visualise the results. Linkage isomerism and methylation reactions are examined using thermodynamics and, in the case of methylation reactions, also with kinetics. Chapter 4 compares the electronic structure of dinuclear complexes with their corresponding mononuclear analogues. PDOS spectra are used to highlight the changes that occur on addition of a second metal centre. The quality of the predicted Raman frequencies of [Ru(bpy)3]2+ is the focus of Chapter 5. The effect of basis set size, grid size and the inclusion of solvent effects is discussed. The results are compared with the experimental values. Chapter 6 presents the first DFT study of an osmium complex attached to a surface, in this case, to a gold (111) surface. A cluster model is used for the surface. The effect of adsorption on the energy levels of the complex is studied. The effect of oxidation on the adsorbate-substrate bond is also examined. Chapter 7 is an overview of the information available from DFT calculations. DFT is a very useful tool for examining the electronic structure of ruthenium polypyridyl complexes. PDOS spectra highlight changes in electronic structure between related complexes. Trends in oxidation potential are reproduced by the position of the metal PDOS peak. Predicted Raman frequencies agree well with experiment, although a scaling factor is required. Adsorption of an osmium complex on a gold surface causes molecular orbitals close to the surface to shift, while the relative positions of other molecular orbitals remain unchanged. The oxidised complex binds more strongly, due to the change in the nature of the frontier orbitals

Alterations in hepatic miRNA expression during negative energy balance in postpartum dairy cattle

peer-reviewedBackground Negative energy balance (NEB), an altered metabolic state, occurs in early postpartum dairy cattle when energy demands to support lactation exceed energy intake. During NEB the liver undergoes oxidative stress and increased breakdown of fatty acids accompanied by changes in gene expression. It is now known that micro RNAs (miRNA) can have a role in mediating such alterations in gene expression through repression or degradation of target mRNAs. miRNA expression is known to be altered by metabolism and environmental factors and miRNAs are implicated in expression modulation of metabolism related genes. Results miRNA expression was profiled in the liver of moderate yielding dairy cattle under severe NEB (SNEB) and mild NEB (MNEB) using the Affymetrix Gene Chip miRNA_2.0 array with 679 probe sets for Bos-taurus miRNAs. Ten miRNAs were found to be differentially expressed using the ‘samr’ statistical package (delta = 0.6) at a q-value FDR of < 12%. Five miRNAs including miR-17-5p, miR-31, miR-140, miR-1281 and miR-2885 were validated using RT-qPCR, to be up-regulated under SNEB. Liver diseases associated with these miRNAs include non-alcoholic fatty liver (NAFLD) and hepatocellular carcinoma (HCC). miR-140 and miR-17-5p are known to show differential expression under oxidative stress. A total of 32 down-regulated putative target genes were also identified among 418 differentially expressed hepatic genes previously reported for the same animal model. Among these, GPR37 (G protein-coupled receptor 37), HEYL (hairy/enhancer-of-split related with YRPW motif-like), DNJA1, CD14 (Cluster of differentiation 14) and GNS (glucosamine (N-acetyl)-6-sulfatase) are known to be associated with hepatic metabolic disorders. In addition miR-140 and miR-2885 have binding sites on the most down-regulated of these genes, FADS2 (Fatty acid desaturase 2) which encodes an enzyme critical in lipid biosynthesis. Furthermore, HNF3-gamma (Hepatocyte nuclear factor 3-gamma), a hepatic transcription factor (TF) that is involved in IGF-1 expression regulation and maintenance of glucose homeostasis is a putative target of miR-31. Conclusions This study shows that SNEB affects liver miRNA expression and these miRNAs have putative targets in hepatic genes down-regulated under this condition. This study highlights the potential role of miRNAs in transcription regulation of hepatic gene expression during SNEB in dairy cattle. Background Negative energy balance (NEB), an altered metabolic state, occurs in early postpartum dairy cattle when energy demands to support lactation exceed energy intake. During NEB the liver undergoes oxidative stress and increased breakdown of fatty acids accompanied by changes in gene expression. It is now known that micro RNAs (miRNA) can have a role in mediating such alterations in gene expression through repression or degradation of target mRNAs. miRNA expression is known to be altered by metabolism and environmental factors and miRNAs are implicated in expression modulation of metabolism related genes. Results miRNA expression was profiled in the liver of moderate yielding dairy cattle under severe NEB (SNEB) and mild NEB (MNEB) using the Affymetrix Gene Chip miRNA_2.0 array with 679 probe sets for Bos-taurus miRNAs. Ten miRNAs were found to be differentially expressed using the ‘samr’ statistical package (delta = 0.6) at a q-value FDR of < 12%. Five miRNAs including miR-17-5p, miR-31, miR-140, miR-1281 and miR-2885 were validated using RT-qPCR, to be up-regulated under SNEB. Liver diseases associated with these miRNAs include non-alcoholic fatty liver (NAFLD) and hepatocellular carcinoma (HCC). miR-140 and miR-17-5p are known to show differential expression under oxidative stress. A total of 32 down-regulated putative target genes were also identified among 418 differentially expressed hepatic genes previously reported for the same animal model. Among these, GPR37 (G protein-coupled receptor 37), HEYL (hairy/enhancer-of-split related with YRPW motif-like), DNJA1, CD14 (Cluster of differentiation 14) and GNS (glucosamine (N-acetyl)-6-sulfatase) are known to be associated with hepatic metabolic disorders. In addition miR-140 and miR-2885 have binding sites on the most down-regulated of these genes, FADS2 (Fatty acid desaturase 2) which encodes an enzyme critical in lipid biosynthesis. Furthermore, HNF3-gamma (Hepatocyte nuclear factor 3-gamma), a hepatic transcription factor (TF) that is involved in IGF-1 expression regulation and maintenance of glucose homeostasis is a putative target of miR-31. Conclusions This study shows that SNEB affects liver miRNA expression and these miRNAs have putative targets in hepatic genes down-regulated under this condition. This study highlights the potential role of miRNAs in transcription regulation of hepatic gene expression during SNEB in dairy cattle

Associations between the K232A polymorphism in the diacylglycerol-O-transferase 1 (DGAT1) gene and performance in Irish Holstein-Friesian dairy cattle

peer-reviewedSelection based on genetic polymorphisms requires accurate quantification of the effect or association of the polymorphisms with all traits of economic importance. The objective of this study was to estimate, using progeny performance data on 848 Holstein-Friesian bulls, the association between a non-conservative alanine to lysine amino acid change (K232A) in exon 8 of the diacylglycerol-O-transferase 1 (DGAT1) gene and milk production and functionality in the Irish Holstein-Friesian population. The DGAT1 gene encodes the diacylglycerol-O-transferase microsomal enzyme necessary to catalyze the final step in triglyceride synthesis. Weighted mixed model methodology, accounting for the additive genetic relationships among animals, was used to evaluate the association between performance and the K232A polymorphism. The minor allele frequency (K allele) was 0.32. One copy of the K allele was associated (P < 0.001) with 77 kg less milk yield, 4.22 kg more fat yield, 0.99 kg less protein yield, and 1.30 and 0.28 g/kg greater milk fat and protein concentration, respectively; all traits were based on predicted 305-day production across the first five lactations. The K232A polymorphism explained 4.8%, 10.3% and 1.0% of the genetic variance in milk yield, fat yield and protein yield, respectively. There was no association between the K232A polymorphism and fertility, functional survival, calving performance, carcass traits, or any conformation trait with the exception of rump width and carcass conformation. Using the current economic values for the milk production traits in the Irish total merit index, one copy of the K allele is worth €5.43 in expected profitability of progeny. Results from this study will be useful in quantifying the cost-benefit of including the K232A polymorphism in the Irish national breeding programme

Computational design and selection of optimal organic photovoltaic materials

Conjugated organic polymers are key building blocks of low-cost photovoltaic materials. We have examined over 90 000 copolymers using computational predictions to solve the "inverse design" of molecular structures with optimum properties for highly efficient solar cells (specifically matching optical excitation energies and excited-state energies). Our approach, which uses a genetic algorithm to search the space of synthetically accessible copolymers of six or eight monomer units, yields hundreds of candidate copolymers with predicted efficiencies over 8% (the current experimental record), including many predicted to be over 10% efficient. We discuss trends in polymer sequences and found in the most frequent monomers and dimers in these highly efficient targets and derive design rules for the selection of appropriate donor and acceptor molecules. We show how additional computationally intensive filtering steps can be used, for example, to eliminate targets likely to have poor hole mobilities. Our method effectively targets optimum electronic structure and optical properties far more efficiently than time-consuming serial experiments or computational studies and can be applied to similar problems in other areas of materials science

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

BACKGROUND: We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. RESULTS: Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. CONCLUSION: With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors

MACiE: a database of enzyme reaction mechanisms.

SUMMARY: MACiE (mechanism, annotation and classification in enzymes) is a publicly available web-based database, held in CMLReact (an XML application), that aims to help our understanding of the evolution of enzyme catalytic mechanisms and also to create a classification system which reflects the actual chemical mechanism (catalytic steps) of an enzyme reaction, not only the overall reaction. AVAILABILITY: http://www-mitchell.ch.cam.ac.uk/macie/.EPSRC (G.L.H. and J.B.O.M.), the BBSRC (G.J.B. and J.M.T.—CASE studentship in association with Roche Products Ltd; N.M.O.B. and J.B.O.M.—grant BB/C51320X/1), the Chilean Government’s Ministerio de Planificacio´n y Cooperacio´n and Cambridge Overseas Trust (D.E.A.) for funding and Unilever for supporting the Centre for Molecular Science Informatics.application note restricted to 2 printed pages web site: http://www-mitchell.ch.cam.ac.uk/macie