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Torsional and Electronic Factors Control the C-H???O Interaction.

ABSTRACT: The precise role of non-conventional hydrogen bonds such as the C-H???O interaction in influencing the conformation of small molecules remains unresolved. Here we survey a series of ?-turn mimetics using X-ray crystallography and NMR spectroscopy in conjunction with quantum calculation, and conclude that favourable torsional and electronic effects are important for the population of states with conformationally influential C-H???O interactions. Our results also highlight the challenge in attempting to deconvolute a myriad of interdependent noncovalent interactions in order to focus on the contribution of a single one. Within a small molecule that is designed to resemble the complexity of the environment within peptides and proteins, the interplay of different steric burdens, hydrogen-acceptor/-donor properties and rotational profiles illustrate why unambiguous conclusions based solely on NMR chemical shift data are extremely challenging to rationalize.

SUBMITTER: Driver RW

PROVIDER: S-EPMC5113693 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Torsional and Electronic Factors Control the C-H⋅⋅⋅O Interaction.

Driver Russell W RW Claridge Timothy D W TD Scheiner Steve S Smith Martin D MD

Chemistry (Weinheim an der Bergstrasse, Germany) 20161006 46

The precise role of non-conventional hydrogen bonds such as the C-H⋅⋅⋅O interaction in influencing the conformation of small molecules remains unresolved. Here we survey a series of β-turn mimetics using X-ray crystallography and NMR spectroscopy in conjunction with quantum calculation, and conclude that favourable torsional and electronic effects are important for the population of states with conformationally influential C-H⋅⋅⋅O interactions. Our results also highlight the challenge in attempt ...[more]

PMID: 27709689

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Project description:BackgroundGenetic and lifestyle factors have considerable effects on obesity and related diseases, yet their effects in a clinical cohort are unknown. This study in a patient biobank examined associations of a BMI polygenic risk score (PRS), and its interactions with lifestyle risk factors, with clinically measured BMI and clinical phenotypes.MethodsThe Mass General Brigham (MGB) Biobank is a hospital-based cohort with electronic health record, genetic, and lifestyle data. A PRS for obesity was generated using 97 genetic variants for BMI. An obesity lifestyle risk index using survey responses to obesogenic lifestyle risk factors (alcohol, education, exercise, sleep, smoking, and shift work) was used to dichotomize the cohort into high and low obesogenic index based on the population median. Height and weight were measured at a clinical visit. Multivariable linear cross-sectional associations of the PRS with BMI and interactions with the obesity lifestyle risk index were conducted. In phenome-wide association analyses (PheWAS), similar logistic models were conducted for 675 disease outcomes derived from billing codes.ResultsThirty-three thousand five hundred eleven patients were analyzed (53.1% female; age 60.0 years; BMI 28.3 kg/m2), of which 17,040 completed the lifestyle survey (57.5% female; age: 60.2; BMI: 28.1 (6.2) kg/m2). Each standard deviation increment in the PRS was associated with 0.83 kg/m2 unit increase in BMI (95% confidence interval (CI) =0.76, 0.90). There was an interaction between the obesity PRS and obesity lifestyle risk index on BMI. The difference in BMI between those with a high and low obesogenic index was 3.18 kg/m2 in patients in the highest decile of PRS, whereas that difference was only 1.55 kg/m2 in patients in the lowest decile of PRS. In PheWAS, the obesity PRS was associated with 40 diseases spanning endocrine/metabolic, circulatory, and 8 other disease groups. No interactions were evident between the PRS and the index on disease outcomes.ConclusionsIn this hospital-based clinical biobank, obesity risk conferred by common genetic variants was associated with elevated BMI and this risk was attenuated by a healthier patient lifestyle. Continued consideration of the role of lifestyle in the context of genetic predisposition in healthcare settings is necessary to quantify the extent to which modifiable lifestyle risk factors may moderate genetic predisposition and inform clinical action to achieve personalized medicine.

Project description:BackgroundPancreatic cancer risk is poorly quantified in relation to the temporal presentation of medical comorbidities and lifestyle. This study aimed to examine this aspect, with possible influence of demographics.MethodsWe conducted a retrospective case-control study on the ethnically-diverse population of East London, UK, using linked electronic health records. We evaluated the independent and two-way interaction effects of 19 clinico-demographic factors in patients with pancreatic cancer (N = 965), compared with non-malignant pancreatic conditions (N = 3963) or hernia (control; N = 4355), reported between April 1, 2008 and March 6, 2020. Risks were quantified by odds ratios (ORs) and 95% confidence intervals (CIs) from multivariable logistic regression models.ResultsWe observed increased odds of pancreatic cancer incidence associated with recent-onset diabetes occurring within 6 months to 3 years before cancer diagnosis (OR 1.95, 95% CI 1.25-3.03), long-standing diabetes for over 3 years (OR 1.74, 95% CI 1.32-2.29), recent smoking (OR 1.81, 95% CI 1.36-2.4) and drinking (OR 1.76, 95% CI 1.31-2.35), as compared to controls but not non-malignant pancreatic conditions. Pancreatic cancer odds was highest for chronic pancreatic disease patients (recent-onset: OR 4.76, 95% CI 2.19-10.3, long-standing: OR 5.1, 95% CI 2.18-11.9), amplified by comorbidities or harmful lifestyle. Concomitant diagnosis of diabetes, upper gastrointestinal or chronic pancreatic conditions followed by a pancreatic cancer diagnosis within 6 months were common, particularly in South Asians. Long-standing cardiovascular, respiratory and hepatobiliary conditions were associated with lower odds of pancreatic cancer.ConclusionsSeveral factors are, independently or via effect modifications, associated with higher incidence of pancreatic cancer, but some established risk factors demonstrate similar magnitude of risk measures of developing non-malignant pancreatic conditions. The findings may inform refined risk-stratification strategies and better surveillance for high-risk individuals, and also provide a means for systematic identification of target population for prospective cohort-based early detection research initiatives.

Dataset Information

Torsional and Electronic Factors Control the C-H???O Interaction.

Publications

Torsional and Electronic Factors Control the C-H⋅⋅⋅O Interaction.

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