Andersson H.,Gothenburg University |
Grafenstein J.,Gothenburg University |
Isobe M.,National Sun Yat - sen University |
Isobe M.,Nagoya University |
And 4 more authors.
Journal of Organic Chemistry | Year: 2017
Photolysis of ethyl 3-azido-4,6-difluorobenzoate at room temperature in the presence of oxygen results in the regioselective formation of ethyl 5,7-difluoro-4-azaspiro[2.4]hepta-1,4,6-triene-1-carboxylate, presumably via the corresponding ketenimine intermediate which undergoes a photochemical four-electron electrocyclization followed by a rearrangement. The photorearrangement product was identified by multinuclear solution NMR spectroscopic techniques supported by DFT calculations. © 2017 American Chemical Society.
Thorson R.A.,University of Wisconsin - Stevens Point |
Woller G.R.,University of Wisconsin - Stevens Point |
Driscoll Z.L.,University of Wisconsin - Stevens Point |
Geiger B.E.,University of Wisconsin - Stevens Point |
And 7 more authors.
European Journal of Organic Chemistry | Year: 2015
A model system for the investigation of intramolecular halogen bonds is introduced. Two molecules capable of intramolecular halogen bonding have been studied in comparison with eight control compounds by 15N, 13C, and 19F NMR spectroscopy. Iodine- and bromine-centered halogen bonds are indicated by decreases in the 15N NMR chemical shifts of the halogen bond acceptor atom of approximately 6 and 1 ppm, respectively. 13C NMR chemical shifts of the alkynyl carbons in 2-ethynylpyridine systems are good indicators of halogen bonding, with differences of up to 2.4 ppm between halogen-bonded and related control compounds. Halogen bond strengths in different solvents, as indicated by 19F NMR chemical shifts, decrease in the following order: Cyclohexane > toluene > benzene > dichloromethane > acetone > pyridine. Chemical shift effects associated with the structural and electronic properties of intramolecular halogen-bonded systems are modeled well by calculations at the B3LYP/6-311+G(2d,p) level of theory. © 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bedin M.,Gothenburg University |
Karim A.,Gothenburg University |
Reitti M.,Gothenburg University |
Carlsson A.-C.C.,Gothenburg University |
And 11 more authors.
Chemical Science | Year: 2015
A detailed investigation of the influence of counterions on the [N-I-N]+ halogen bond in solution, in the solid state and in silico is presented. Translational diffusion coefficients indicate close attachment of counterions to the cationic, three-center halogen bond in dichloromethane solution. Isotopic perturbation of equilibrium NMR studies performed on isotopologue mixtures of regioselectively deuterated and nondeuterated analogues of the model system showed that the counterion is incapable of altering the symmetry of the [N-I-N]+ halogen bond. This symmetry remains even in the presence of an unfavorable geometric restraint. A high preference for the symmetric geometry was found also in the solid state by single crystal X-ray crystallography. Molecular systems encompassing weakly coordinating counterions behave similarly to the corresponding silver(i) centered coordination complexes. In contrast, systems possessing moderately or strongly coordinating anions show a distinctly different behavior. Such silver(i) complexes are converted into multi-coordinate geometries with strong Ag-O bonds, whereas the iodine centered systems remain linear and lack direct charge transfer interaction with the counterion, as verified by 15N NMR and DFT computation. This suggests that the [N-I-N]+ halogen bond may not be satisfactorily described in terms of a pure coordination bond typical of transition metal complexes, but as a secondary bond with a substantial charge-transfer character. © The Royal Society of Chemistry 2015.
Carlsson A.-C.C.,Gothenburg University |
Carlsson A.-C.C.,Colorado State University |
Mehmeti K.,Gothenburg University |
Uhrbom M.,Gothenburg University |
And 14 more authors.
Journal of the American Chemical Society | Year: 2016
We have investigated the influence of electron density on the three-center [N-I-N]+ halogen bond. A series of [bis(pyridine)iodine]+ and [1,2-bis((pyridine-2-ylethynyl)benzene)iodine]+ BF4 - complexes substituted with electron withdrawing and donating functionalities in the para-position of their pyridine nitrogen were synthesized and studied by spectroscopic and computational methods. The systematic change of electron density of the pyridine nitrogens upon alteration of the para-substituent (NO2, CF3, H, F, Me, OMe, NMe2) was confirmed by 15N NMR and by computation of the natural atomic population and the π electron population of the nitrogen atoms. Formation of the [N-I-N]+ halogen bond resulted in >100 ppm 15N NMR coordination shifts. Substituent effects on the 15N NMR chemical shift are governed by the π population rather than the total electron population at the nitrogens. Isotopic perturbation of equilibrium NMR studies along with computation on the DFT level indicate that all studied systems possess static, symmetric [N-I-N]+ halogen bonds, independent of their electron density. This was further confirmed by single crystal X-ray diffraction data of 4-substituted [bis(pyridine)iodine]+ complexes. An increased electron density of the halogen bond acceptor stabilizes the [N···I···N]+ bond, whereas electron deficiency reduces the stability of the complexes, as demonstrated by UV-kinetics and computation. In contrast, the N-I bond length is virtually unaffected by changes of the electron density. The understanding of electronic effects on the [N-X-N]+ halogen bond is expected to provide a useful handle for the modulation of the reactivity of [bis(pyridine)halogen]+-type synthetic reagents. © 2016 American Chemical Society.
Carlsson A.-C.C.,Gothenburg University |
Grafenstein J.,Gothenburg University |
Budnjo A.,Gothenburg University |
Budnjo A.,University of Bergen |
And 8 more authors.
Journal of the American Chemical Society | Year: 2012
Halogen bonding is a recently rediscovered secondary interaction that shows potential to become a complementary molecular tool to hydrogen bonding in rational drug design and in material sciences. Whereas hydrogen bond symmetry has been the subject of systematic studies for decades, the understanding of the analogous three-center halogen bonds is yet in its infancy. The isotopic perturbation of equilibrium (IPE) technique with 13C NMR detection was applied to regioselectively deuterated pyridine complexes to investigate the symmetry of [N-I-N] + and [N-Br-N] + halogen bonding in solution. Preference for a symmetric arrangement was observed for both a freely adjustable and for a conformationally restricted [N-X-N] + model system, as also confirmed by computation on the DFT level. A closely attached counterion is shown to be compatible with the preferred symmetric arrangement. The experimental observations and computational predictions reveal a high energetic gain upon formation of symmetric, three-center four-electron halogen bonding. Whereas hydrogen bonds are generally asymmetric in solution and symmetric in the crystalline state, the analogous bromine and iodine centered halogen bonds prefer symmetric arrangement in solution. © 2012 American Chemical Society.
News Article | December 8, 2016
A machine learning method analyzing large amounts of health information has potential in assessing the risk of cognitively healthy older people for later dementia, according to research published in the Journal of Alzheimer's Disease Preventing dementia is a major public health priority worldwide, and intense work is being conducted to formulate effective preventive strategies. Healthy lifestyle changes may help prevent cognitive decline and dementia, but the challenge is to detect early on those who are most at risk and to choose the most relevant preventive measures. Recent developments in dementia prevention research include large online Brain Health Registries, multinational data discovery and sharing platforms, and internet-based prevention trials. Dealing with large amounts of health information - "big data"- is a challenging consequence of these developments. Machine learning represents a type of artificial intelligence where a group of methods is used to teach computers to make and improve predictions based on large datasets. These methods are just starting to be used in the context of dementia prevention. A team of medical doctors and engineers from Finland and Sweden addressed these challenges using a novel machine learning approach. They developed a dementia risk index - a tool for assessing people's risk of dementia and for indicating the most relevant target areas for preventive measures. An added advantage of the tool is the ability to show detailed individual dementia risk profiles in a visual format that is easy to interpret. The research team used data from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study conducted in Eastern Finland. Study participants were cognitively normal individuals aged 65-79 years from the general Finnish population who underwent detailed health-related assessments, including memory and other cognitive tests. The dementia risk index performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. The main included predictors were cognition, vascular factors, age, subjective memory complaints and apolipoprotein E (APOE) genotype. The researchers conclude that the risk index could be useful for identifying older individuals who are most at risk, and who may also benefit most from preventive interventions. They emphasize that the risk index is not meant for dementia diagnosis, but as a tool to help with making decisions about dementia prevention strategies, i.e. to whom these should be targeted, and what risk factors should be specifically addressed based on the visual risk profile. "The results of our study are very promising, as it is the first time this machine learning approach was used for estimating dementia risk in a cognitively normal general population," says the lead researcher, Alina Solomon, MD, PhD, from the University of Eastern Finland. "The risk index was designed to support clinical decision making, and we are very keen on exploring its potential practical use. However, we still need to validate this risk index in other populations outside Finland. We also need to investigate if it works in people older than 80 years, and if it can monitor changes in dementia risk over time, for example as a response to lifestyle interventions. These are some of the next steps we are planning now," Dr Solomon adds. "Large health information databases contain a lot of valuable information which is still partly hidden and under-exploited. Modern machine learning methods can be used to extract patterns of data that may be difficult to observe just by looking at the data by eye. Our objective has been to detect patterns that predict whether a person is more likely to get dementia in the future. Another area of interest has been how to present all these complex data in a simple form to make these modern technologies useful for clinicians and general public interested in dementia prevention", says Jyrki Lötjönen, PhD, one of the co-authors in the study and chief scientific officer at Combinostics Ltd. The study was funded by the European Union 7th Framework Programme via the VPH-DARE@IT project; Academy of Finland, Swedish Research Council and EU Joint Programme - Neurodegenerative Disease Research (JPND); the strategic funding of the University of Eastern Finland via the UEF-BRAIN consortium; Swedish Center for Innovative Medicine (CIMED), Sweden; Alzheimerfonden Sweden; and AXA Research Fund. ABOUT THE JOURNAL OF ALZHEIMER'S DISEASE (JAD) The Journal of Alzheimer's Disease is an international multidisciplinary journal to facilitate progress in understanding the etiology, pathogenesis, epidemiology, genetics, behavior, treatment and psychology of Alzheimer's disease. The journal publishes research reports, reviews, short communications, book reviews, and letters-to-the-editor. Groundbreaking research that has appeared in the journal includes novel therapeutic targets, mechanisms of disease and clinical trial outcomes. The Journal of Alzheimer's Disease has an Impact Factor of 4.151 according to Thomson Reuters' 2014 Journal Citation Reports. The Journal is published by IOS Press.
Nilsson J.,Gothenburg University |
Halim A.,Gothenburg University |
Moslemi A.-R.,Gothenburg University |
Pedersen A.,Swedish Center |
And 2 more authors.
Biochimica et Biophysica Acta - Molecular Basis of Disease | Year: 2012
Glycogenin-1 initiates the glycogen synthesis in skeletal muscle by the autocatalytic formation of a short oligosaccharide at tyrosine 195. Glycogenin-1 catalyzes both the glucose-O-tyrosine linkage and the α1,4 glucosidic bonds linking the glucose molecules in the oligosaccharide. We recently described a patient with glycogen depletion in skeletal muscle as a result of a non-functional glycogenin-1. The patient carried a Thr83Met substitution in glycogenin-1. In this study we have investigated the importance of threonine 83 for the catalytic activity of glycogenin-1. Non-glucosylated glycogenin-1 constructs, with various amino acid substitutions in position 83 and 195, were expressed in a cell-free expression system and autoglucosylated in vitro. The autoglucosylation was analyzed by gel-shift on western blot, incorporation of radiolabeled UDP- 14C-glucose and nano-liquid chromatography with tandem mass spectrometry (LC/MS/MS). We demonstrate that glycogenin-1 with the Thr83Met substitution is unable to form the glucose-O-tyrosine linkage at tyrosine 195 unless co-expressed with the catalytically active Tyr195Phe glycogenin-1. Our results explain the glycogen depletion in the patient expressing only Thr83Met glycogenin-1 and why heterozygous carriers without clinical symptoms show a small proportion of unglucosylated glycogenin-1. © 2011 Elsevier B.V.
Erdelyi M.,Gothenburg University |
Erdelyi M.,Swedish Center
Chemical Society Reviews | Year: 2012
Halogen bonding is the electron density donation based weak interaction of halogens with Lewis bases. Its applicability for molecular recognition processes long remained unappreciated and has so far mostly been studied in silico and in solid state. As most physiological processes and chemical reactions take place in solution, investigations in solutions are of highest relevance for its use in the pharmaceutical and material scientific toolboxes. Following a short discussion of the phenomenon of halogen bonding, this tutorial review presents an overview of the methods hitherto applied for gaining an improved understanding of its behaviour in solutions and summarizes the gained knowledge in order to indicate the scope of the techniques and to facilitate exciting future developments. © The Royal Society of Chemistry 2012.