Common polygenic variation in coeliac disease and confirmation of ZNF335 and NIFA as disease susceptibility loci

Coeliac disease (CD) is a chronic immune-mediated disease triggered by the ingestion of gluten. It has an estimated prevalence of approximately 1% in European populations. Specific HLA-DQA1 and HLA-DQB1 alleles are established coeliac susceptibility genes and are required for the presentation of gliadin to the immune system resulting in damage to the intestinal mucosa. In the largest association analysis of CD to date, 39 non-HLA risk loci were identified, 13 of which were new, in a sample of 12 014 individuals with CD and 12 228 controls using the Immunochip genotyping platform. Including the HLA, this brings the total number of known CD loci to 40. We have replicated this study in an independent Irish CD case–control population of 425 CD and 453 controls using the Immunochip platform. Using a binomial sign test, we show that the direction of the effects of previously described risk alleles were highly correlated with those reported in the Irish population, (P=2.2 × 10−16). Using the Polygene Risk Score (PRS) approach, we estimated that up to 35% of the genetic variance could be explained by loci present on the Immunochip (P=9 × 10−75). When this is limited to non-HLA loci, we explain a maximum of 4.5% of the genetic variance (P=3.6 × 10−18). Finally, we performed a meta-analysis of our data with the previous reports, identifying two further loci harbouring the ZNF335 and NIFA genes which now exceed genome-wide significance, taking the total number of CD susceptibility loci to 42

Thermodynamic Selection of Steric Zipper Patterns in the Amyloid Cross-β Spine

At the core of amyloid fibrils is the cross-β spine, a long tape of β-sheets formed by the constituent proteins. Recent high-resolution x-ray studies show that the unit of this filamentous structure is a β-sheet bilayer with side chains within the bilayer forming a tightly interdigitating “steric zipper” interface. However, for a given peptide, different bilayer patterns are possible, and no quantitative explanation exists regarding which pattern is selected or under what condition there can be more than one pattern observed, exhibiting molecular polymorphism. We address the structural selection mechanism by performing molecular dynamics simulations to calculate the free energy of incorporating a peptide monomer into a β-sheet bilayer. We test filaments formed by several types of peptides including GNNQQNY, NNQQ, VEALYL, KLVFFAE and STVIIE, and find that the patterns with the lowest binding free energy correspond to available atomistic structures with high accuracy. Molecular polymorphism, as exhibited by NNQQ, is likely because there are more than one most stable structures whose binding free energies differ by less than the thermal energy. Detailed analysis of individual energy terms reveals that these short peptides are not strained nor do they lose much conformational entropy upon incorporating into a β-sheet bilayer. The selection of a bilayer pattern is determined mainly by the van der Waals and hydrophobic forces as a quantitative measure of shape complementarity among side chains between the β-sheets. The requirement for self-complementary steric zipper formation supports that amyloid fibrils form more easily among similar or same sequences, and it also makes parallel β-sheets generally preferred over anti-parallel ones. But the presence of charged side chains appears to kinetically drive anti-parallel β-sheets to form at early stages of assembly, after which the bilayer formation is likely driven by energetics

Blinded predictions of distribution coefficients in the SAMPL5 challenge

In the context of the SAMPL5 challenge water-cyclohexane distribution coefficients for 53 drug-like molecules were predicted. Four different models based on molecular dynamics free energy calculations were tested. All models initially assumed only one chemical state present in aqueous or organic phases. Model A is based on results from an alchemical annihilation scheme; model B adds a long range correction for the Lennard Jones potentials to model A; model C adds charging free energy corrections; model D applies the charging correction from model C to ionizable species only. Model A and B perform better in terms of mean-unsigned error ([Formula: see text] D units − 95 % confidence interval) and determination coefficient [Formula: see text] , while charging corrections lead to poorer results with model D ([Formula: see text] and [Formula: see text] ). Because overall errors were large, a retrospective analysis that allowed co-existence of ionisable and neutral species of a molecule in aqueous phase was investigated. This considerably reduced systematic errors ([Formula: see text] and [Formula: see text] ). Overall accurate [Formula: see text] predictions for drug-like molecules that may adopt multiple tautomers and charge states proved difficult, indicating a need for methodological advances to enable satisfactory treatment by explicit-solvent molecular simulations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-016-9969-1) contains supplementary material, which is available to authorized users

Factors associated with psychotropic drug use among community-dwelling older persons: A review of empirical studies

BACKGROUND: In the many descriptive studies on prescribed psychotropic drug use by community-dwelling older persons, several sociodemographic and other factors associated with drug use receive inconsistent support. METHOD: Empirical reports with data on at least benzodiazepine or antidepressant drug use in samples of older persons published between 1990 and 2001 (n = 32) were identified from major databases and analyzed to determine which factors are most frequently associated with psychotropic drug use in multivariate analyses. Methodological aspects were also examined. RESULTS: Most reports used probability samples of users and non-users and employed cross-sectional designs. Among variables considered in 5 or more reports, race, proximity to health centers, medical consultations, sleep complaints, and health perception were virtually always associated to drug use. Gender, mental health, and physical health status were associated in about two-thirds of reports. Associations with age, marital status, medication coverage, socioeconomic status, and social support were usually not observed. CONCLUSIONS: The large variety of methods to operationalize drug use, mental health status, and social support probably affected the magnitude of observed relationships. Employing longitudinal designs and distinguishing short-term from long-term use, focusing on samples of drug users exclusively, defining drug use and drug classes more uniformly, and utilizing measures of psychological well-being rather than only of distress, might clarify the nature of observed associations and the direction of causality. Few studies tested specific hypotheses. Most studies focused on individual characteristics of respondents, neglecting the potential contribution of health care professionals to the phenomenon of psychotropic drug use among seniors

Molecular dynamics simulation approach to investigate dynamic behaviour of system through the application of newtonian mechanics

Molecular dynamics simulations have been successfully incorporated and evolved into a mature technique within a variety of pharmaceutical research programs to study the complex biological and chemical systems. Broadly used in modern drug design, molecular docking methods can be used effectively to understand the macromolecular structure-to-function relationships and ligand conformations adopted within the binding sites of macromolecular targets. Information gathered about the dynamic properties of ligand–receptor binding such as free energy by evaluating critical phenomena involved in the intermolecular recognition process. These results can be employed to shift the usual paradigm of structural bioinformatics from studying single structures to analyse conformational ensembles. Today, as a variety of docking algorithms are available, an understanding of advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this chapter is to examine the current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advancements in the field and role played by integration of structure-and ligand-based methods