Computation of protein geometry and its applications: Packing and function prediction

This chapter discusses geometric models of biomolecules and geometric constructs, including the union of ball model, the weigthed Voronoi diagram, the weighted Delaunay triangulation, and the alpha shapes. These geometric constructs enable fast and analytical computaton of shapes of biomoleculres (including features such as voids and pockets) and metric properties (such as area and volume). The algorithms of Delaunay triangulation, computation of voids and pockets, as well volume/area computation are also described. In addition, applications in packing analysis of protein structures and protein function prediction are also discussed.Comment: 32 pages, 9 figure

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

On the crystal growth of nanoscale schwertmannite

Schwertmannite (Fe16O16(OH)12(SO4)2), commonly found in acidic aqueous systems, forms rapidly into a “hedge-hog” morphology, where nano-dimension whiskers project outwards from an electron-dense interior. Schwertmannite whiskers were recently found to contain the highly disordered and maghemite-like structural components present in ferrihydrite, and on this basis, schwertmannite was postulated to be an intermediate phase (in terms of crystallinity and kinetics of formation) to the least and most crystalline forms of ferrihydrite, 2- and 6-line, respectively. To test this hypothesis and help elucidate the schwertmannite growth mechanism, we reduced supersaturation (a function of pH and ferric concentration) during the crystallization of 2-line ferrihydrite from ferric sulphate liquors. Lower supersaturations resulted in schwertmannite formation, often in an admixture or possibly nucleated on 2-line ferrihydrite aggregates. Alternate experiments performed in the presence of arsenic (as a crystal growth modifier) produced X-ray diffraction (XRD) patterns consistent with admixed ferrihydrite and schwertmannite, but with a morphology where aligned ferrihydrite nanoparticles appeared to approximate the structure of schwertmannite whiskers. We postulate that as similar structural components constitute 2-line ferrihydrite and schwertmannite, but are only minor components in 6-line ferrihydrite, the proportion of each component (with the maghemite-like phase dominating) permits the specific alignment and growth of the intriguing schwertmannite morphology

Dataset: Age determination results from site Beaverdam_Creek

Minimum DEPTH, sediment/rock: 0.000 m * Maximum DEPTH, sediment/rock: 54.000