Multiple sclerosis or neuromyelitis optica? Re-evaluating an 18th-century illness using 21st-century software

In this paper we report the application of an extensive database of symptoms, signs, laboratory findings and illnesses, to the diagnosis of an historical figure. The medical diagnosis of Augustus d'Este (1794–1848) – widely held to be the first documented case of multiple sclerosis – is reviewed, using the detailed symptom diary, which he kept over many years, as clinical data. Some of the reported features prompted the competing claim that d'Este suffered from acute porphyria, which in turn was used in support of the hypothesis that his grandfather, King George III, also suffered from the disease. We find that multiple sclerosis is statistically the most likely diagnosis, with neuromyelitis optica a strong alternative possibility. The database did not support a diagnosis of any of the acute porphyrias

A Supramolecular Ice Growth Inhibitor

Safranine O, a synthetic dye, was found to inhibit growth of ice at millimolar concentrations with an activity comparable to that of highly evolved antifreeze glycoproteins. Safranine inhibits growth of ice crystals along the crystallographic a-axis, resulting in bipyramidal needles extended along the directions as well as and plane-specific thermal hysteresis (TH) activity. The interaction of safranine with ice is reversible, distinct from the previously reported behavior of antifreeze proteins. Spectroscopy and molecular dynamics indicate that safranine forms aggregates in aqueous solution at micromolar concentrations. Metadynamics simulations and aggregation theory suggested that as many as 30 safranine molecules were preorganized in stacks at the concentrations where ice growth inhibition was observed. The simulations and single-crystal X-ray structure of safranine revealed regularly spaced amino and methyl substituents in the aggregates, akin to the ice-binding site of antifreeze proteins. Collectively, these observations suggest an unusual link between supramolecular assemblies of small molecules and functional proteins

Difference Hirshfeld fingerprint plots: A tool for studying polymorphs

A new tool has been developed to help elucidate the differences in packing between different polymorphs, especially when the differences of interest are small. The technique builds upon the Hirshfeld fingerprint plot pioneered by Spackman and co-workers by subtracting the value at every point in a fingerprint plot from the value at every point in another. This is found to reveal differences that are not readily apparent to the eye. By summing the absolute values of these differences, a quantitative measure of the difference between two fingerprint plots can be obtained. The technique was applied to Ni and Cu trans-bis(2-hydroxy-5-methylphenonethanoneoximato) complexes determined at two temperatures, with the Ni complex displaying temperature-dependent polymorphism. Difference Hirshfeld fingerprint plots were also generated for calculated structures from DFT simulations that were performed on the experimental structures. These demonstrated that the simulations reproduced the fine detail of the packing

Four small puzzles that Rosetta doesn't solve

A complete macromolecule modeling package must be able to solve the simplest structure prediction problems. Despite recent successes in high resolution structure modeling and design, the Rosetta software suite fares poorly on deceptively small protein and RNA puzzles, some as small as four residues. To illustrate these problems, this manuscript presents extensive Rosetta results for four well-defined test cases: the 20-residue mini-protein Trp cage, an even smaller disulfide-stabilized conotoxin, the reactive loop of a serine protease inhibitor, and a UUCG RNA tetraloop. In contrast to previous Rosetta studies, several lines of evidence indicate that conformational sampling is not the major bottleneck in modeling these small systems. Instead, approximations and omissions in the Rosetta all-atom energy function currently preclude discriminating experimentally observed conformations from de novo models at atomic resolution. These molecular "puzzles" should serve as useful model systems for developers wishing to make foundational improvements to this powerful modeling suite.Comment: Published in PLoS One as a manuscript for the RosettaCon 2010 Special Collectio

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

Knowledge-based energy functions for computational studies of proteins

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details about the Miyazawa-Jernigan contact statistical potential, distance-dependent statistical potentials, as well as geometric statistical potentials. We also describe a geometric model for developing both linear and non-linear potential functions by optimization. Applications of knowledge-based potential functions in protein-decoy discrimination, in protein-protein interactions, and in protein design are then described. Several issues of knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe

CCBuilder:An interactive web-based tool for building, designing and assessing coiled-coil protein assemblies

Motivation: The ability to accurately model protein structures at the atomistic level underpins efforts to understand protein folding, to engineer natural proteins predictably and to design proteins de novo . Homology-based methods are well established and produce impressive results. However, these are limited to structures presented by and resolved for natural proteins. Addressing this problem more widely and deriving truly ab initio models requires mathematical descriptions for protein folds; the means to decorate these with natural, engineered or de novo sequences; and methods to score the resulting models. Results: We present CCBuilder, a web-based application that tackles the problem for a defined but large class of protein structure, the α-helical coiled coils. CCBuilder generates coiled-coil backbones, builds side chains onto these frameworks and provides a range of metrics to measure the quality of the models. Its straightforward graphical user interface provides broad functionality that allows users to build and assess models, in which helix geometry, coiled-coil architecture and topology and protein sequence can be varied rapidly. We demonstrate the utility of CCBuilder by assembling models for 653 coiled-coil structures from the PDB, which cover >96% of the known coiled-coil types, and by generating models for rarer and de novo coiled-coil structures. Availability and implementation: CCBuilder is freely available, without registration, at http://coiledcoils.chm.bris.ac.uk/app/cc_builder