Physical Activity Detection for Diabetes Mellitus Patients Using Recurrent Neural Networks.

Diabetes mellitus (DM) is a persistent metabolic disorder associated with the hormone insulin. The two main types of DM are type 1 (T1DM) and type 2 (T2DM). Physical activity plays a crucial role in the therapy of diabetes, benefiting both types of patients. The detection, recognition, and subsequent classification of physical activity based on type and intensity are integral components of DM treatment. The continuous glucose monitoring system (CGMS) signal provides the blood glucose (BG) level, and the combination of CGMS and heart rate (HR) signals are potential targets for detecting relevant physical activity from the BG variation point of view. The main objective of the present research is the developing of an artificial intelligence (AI) algorithm capable of detecting physical activity using these signals. Using multiple recurrent models, the best-achieved performance of the different classifiers is a 0.99 area under the receiver operating characteristic curve. The application of recurrent neural networks (RNNs) is shown to be a powerful and efficient solution for accurate detection and analysis of physical activity in patients with DM. This approach has great potential to improve our understanding of individual activity patterns, thus contributing to a more personalized and effective management of DM.

Saturation Transfer Difference NMR and Molecular Docking Interaction Study of Aralkyl-Thiodigalactosides as Potential Inhibitors of the Human-Galectin-3 Protein.

Human Galectin-3 (hGal-3) is a protein that selectively binds to ß-galactosides and holds diverse roles in both normal and pathological circumstances. Therefore, targeting hGal-3 has become a vibrant area of research in the pharmaceutical chemistry. As a step towards the development of novel hGal-3 inhibitors, we synthesized and investigated derivatives of thiodigalactoside (TDG) modified with different aromatic substituents. Specifically, we describe a high-yielding synthetic route of thiodigalactoside (TDG); an optimized procedure for the synthesis of the novel 3,3'-di-O-(quinoline-2-yl)methyl)-TDG and three other known, symmetric 3,3'-di-O-TDG derivatives ((naphthalene-2yl)methyl, benzyl, (7-methoxy-2H-1-benzopyran-2-on-4-yl)methyl). In the present study, using competition Saturation Transfer Difference (STD) NMR spectroscopy, we determined the dissociation constant (Kd) of the former three TDG derivatives produced to characterize the strength of the interaction with the target protein (hGal-3). Based on the Kd values determined, the (naphthalen-2-yl)methyl, the (quinolin-2-yl)methyl and the benzyl derivatives bind to hGal-3 94, 30 and 24 times more strongly than TDG. Then, we studied the binding modes of the derivatives in silico by molecular docking calculations. Docking poses similar to the canonical binding modes of well-known hGal-3 inhibitors have been found. However, additional binding forces, cation-π interactions between the arginine residues in the binding pocket of the protein and the aromatic groups of the ligands, have been established as significant features. Our results offer a molecular-level understanding of the varying affinities observed among the synthesized thiodigalactoside derivatives, which can be a key aspect in the future development of more effective ligands of hGal-3.

AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets.

BACKGROUND: Optimal sports performance requires a balance between intensive training and adequate rest. IMUs provide objective, quantifiable data to analyze performance dynamics, despite the challenges in quantifying athlete training loads. The ability of AI to analyze complex datasets brings innovation to the monitoring and optimization of athlete training cycles. Traditional techniques rely on subjective assessments to prevent overtraining, which can lead to injury and underperformance. IMUs provide objective, quantitative data on athletes' physical status during action. AI and machine learning can turn these data into useful insights, enabling data-driven athlete performance management. With IMU-generated multivariate time series data, this paper uses AI to construct a robust model for predicting fatigue and stamina. MATERIALS AND METHODS: IMUs linked to 19 athletes recorded triaxial acceleration, angular velocity, and magnetic orientation throughout repeated sessions. Standardized training included steady-pace runs and fatigue-inducing techniques. The raw time series data were used to train a supervised ML model based on frequency and time-domain characteristics. The performances of Random Forest, Gradient Boosting Machines, and LSTM networks were compared. A feedback loop adjusted the model in real time based on prediction error and bias estimation. RESULTS: The AI model demonstrated high predictive accuracy for fatigue, showing significant correlations between predicted fatigue levels and observed declines in performance. Stamina predictions enabled individualized training adjustments that were in sync with athletes' physiological thresholds. Bias correction mechanisms proved effective in minimizing systematic prediction errors. Moreover, real-time adaptations of the model led to enhanced training periodization strategies, reducing the risk of overtraining and improving overall athletic performance. CONCLUSIONS: In sports performance analytics, the AI-assisted model using IMU multivariate time series data is effective. Training can be tailored and constantly altered because the model accurately predicts fatigue and stamina. AI models can effectively forecast the beginning of weariness before any physical symptoms appear. This allows for timely interventions to prevent overtraining and potential accidents. The model shows an exceptional ability to customize training programs according to the physiological reactions of each athlete and enhance the overall training effectiveness. In addition, the study demonstrated the model's efficacy in real-time monitoring performance, improving the decision-making abilities of both coaches and athletes. The approach enables ongoing and thorough data analysis, supporting strategic planning for training and competition, resulting in optimized performance outcomes. These findings highlight the revolutionary capability of AI in sports science, offering a future where data-driven methods greatly enhance athlete training and performance management.

Machine Learning on Prediction of Relative Physical Activity Intensity Using Medical Radar Sensor and 3D Accelerometer.

BACKGROUND: One of the most critical topics in sports safety today is the reduction in injury risks through controlled fatigue using non-invasive athlete monitoring. Due to the risk of injuries, it is prohibited to use accelerometer-based smart trackers, activity measurement bracelets, and smart watches for recording health parameters during performance sports activities. This study analyzes the synergy feasibility of medical radar sensors and tri-axial acceleration sensor data to predict physical activity key performance indexes in performance sports by using machine learning (ML). The novelty of this method is that it uses a 24 GHz Doppler radar sensor to detect vital signs such as the heartbeat and breathing without touching the person and to predict the intensity of physical activity, combined with the acceleration data from 3D accelerometers. METHODS: This study is based on the data collected from professional athletes and freely available datasets created for research purposes. A combination of sensor data management was used: a medical radar sensor with no-contact remote sensing to measure the heart rate (HR) and 3D acceleration to measure the velocity of the activity. Various advanced ML methods and models were employed on the top of sensors to analyze the vital parameters and predict the health activity key performance indexes. three-axial acceleration, heart rate data, age, as well as activity level variances. RESULTS: The ML models recognized the physical activity intensity and estimated the energy expenditure on a realistic level. Leave-one-out (LOO) cross-validation (CV), as well as out-of-sample testing (OST) methods, have been used to evaluate the level of accuracy in activity intensity prediction. The energy expenditure prediction with three-axial accelerometer sensors by using linear regression provided 97-99% accuracy on selected sports (cycling, running, and soccer). The ML-based RPE results using medical radar sensors on a time-series heart rate (HR) dataset varied between 90 and 96% accuracy. The expected level of accuracy was examined with different models. The average accuracy for all the models (RPE and METs) and setups was higher than 90%. CONCLUSIONS: The ML models that classify the rating of the perceived exertion and the metabolic equivalent of tasks perform consistently.

Detection of Physical Activity Using Machine Learning Methods Based on Continuous Blood Glucose Monitoring and Heart Rate Signals.

Non-coordinated physical activity may lead to hypoglycemia, which is a dangerous condition for diabetic people. Decision support systems related to type 1 diabetes mellitus (T1DM) still lack the capability of automated therapy modification by recognizing and categorizing the physical activity. Further, this desired adaptive therapy should be achieved without increasing the administrative load, which is already high for the diabetic community. These requirements can be satisfied by using artificial intelligence-based solutions, signals collected by wearable devices, and relying on the already available data sources, such as continuous glucose monitoring systems. In this work, we focus on the detection of physical activity by using a continuous glucose monitoring system and a wearable sensor providing the heart rate-the latter is accessible even in the cheapest wearables. Our results show that the detection of physical activity is possible based on these data sources, even if only low-complexity artificial intelligence models are deployed. In general, our models achieved approximately 90% accuracy in the detection of physical activity.

Investigation of the Molecular Details of the Interactions of Selenoglycosides and Human Galectin-3.

Human galectin-3 (hGal-3) is involved in a variety of biological processes and is implicated in wide range of diseases. As a result, targeting hGal-3 for clinical applications has become an intense area of research. As a step towards the development of novel hGal-3 inhibitors, we describe a study of the binding of two Se-containing hGal-3 inhibitors, specifically that of di(ß-D-galactopyranosyl)selenide (SeDG), in which two galactose rings are linked by one Se atom and a di(ß-D-galactopyranosyl)diselenide (DSeDG) analogue with a diseleno bond between the two sugar units. The binding affinities of these derivatives to hGal-3 were determined by 15N-1H HSQC NMR spectroscopy and fluorescence anisotropy titrations in solution, indicating a slight decrease in the strength of interaction for SeDG compared to thiodigalactoside (TDG), a well-known inhibitor of hGal-3, while DSeDG displayed a much weaker interaction strength. NMR and FA measurements showed that both seleno derivatives bind to the canonical S face site of hGal-3 and stack against the conserved W181 residue also confirmed by X-ray crystallography, revealing canonical properties of the interaction. The interaction with DSeDG revealed two distinct binding modes in the crystal structure which are in fast exchange on the NMR time scale in solution, explaining a weaker interaction with hGal-3 than SeDG. Using molecular dynamics simulations, we have found that energetic contributions to the binding enthalpies mainly differ in the electrostatic interactions and in polar solvation terms and are responsible for weaker binding of DSeDG compared to SeDG. Selenium-containing carbohydrate inhibitors of hGal-3 showing canonical binding modes offer the potential of becoming novel hydrolytically stable scaffolds for a new class of hGal-3 inhibitors.

Selenoglycosides as Lectin Ligands: 77 Se-Edited CPMG-HSQMBC NMR Spectroscopy To Monitor Biomedically Relevant Interactions.

The fundamental importance of protein-glycan recognition calls for specific and sensitive high-resolution techniques for their detailed analysis. After the introduction of 19 F NMR spectroscopy to study the recognition of fluorinated glycans, a new 77 Se NMR spectroscopy method is presented for complementary studies of selenoglycans with optimised resolution and sensitivity, in which direct NMR spectroscopy detection on 77 Se is replaced by its indirect observation in a 2D 1 H,77 Se HSQMBC spectrum. In contrast to OH/F substitution, O/Se exchange allows the glycosidic bond to be targeted. As an example, selenodigalactoside recognition by three human galectins and a plant toxin is readily indicated by signal attenuation and line broadening in the 2D 1 H,77 Se HSQMBC spectrum, in which CPMG-INEPT long-range transfer ensures maximal detection sensitivity, clean signal phases, and reliable ligand ranking. By monitoring competitive displacement of a selenated spy ligand, the selective 77 Se NMR spectroscopy approach may also be used to screen non-selenated compounds. Finally, 1 H,77 Se CPMG-INEPT transfer allows further NMR sensors of molecular interaction to be combined with the specificity and resolution of 77 Se NMR spectroscopy.

Aralkyl selenoglycosides and related selenosugars in acetylated form activate protein phosphatase-1 and -2A.

Aralkyl and aryl selenoglycosides as well as glycosyl selenocarboxylate derivatives were assayed on the activity of protein phosphatase-1 (PP1) and -2A (PP2A) catalytic subunits (PP1c and PP2Ac) in search of compounds for PP1c and PP2Ac effectors. The majority of tested selenoglycosides activated both PP1c and PP2Ac by ∼2-4-fold in a phosphatase assay with phosphorylated myosin light chain substrate when the hydroxyl groups of the glycosyl moiety were acetylated, but they were without any effects in the non-acetylated forms. A peptide from the myosin phosphatase target subunit-1 (MYPT123-38) that included an RVxF PP1c-binding motif attenuated activation of PP1c by 2-Trifluoromethylbenzyl 2,3,4,6-tetra-O-acetyl-1-seleno-ß-d-glucopyranoside (TFM-BASG) and 4-Bromobenzyl 2,3,4,6-tetra-O-acetyl-1-seleno-ß-d-glucopyranoside (Br-BASG). MYPT123-38 stimulated PP2Ac and contributed to PP2Ac activation exerted by either Br-BASG or TFM-BASG. Br-BASG and TFM-BASG suppressed partially binding of PP1c to MYPT1 in surface plasmon resonance based binding experiments. Molecular docking predicted that the hydrophobic binding surfaces in PP1c for interaction with either the RVxF residues of PP1c-interactors or selenoglycosides are partially overlapped. Br-BASG and TFM-BASG caused a moderate increase in the phosphatase activity of HeLa cells in 1 h, and suppressed cell viability in 24 h incubations. In conclusion, our present study identified selenoglycosides as novel activators of PP1 and PP2A as well as provided insights into the structural background of their interactions establishing a molecular model for future design of more efficient phosphatase activator molecules.

Bivalent O-glycoside mimetics with S/disulfide/Se substitutions and aromatic core: Synthesis, molecular modeling and inhibitory activity on biomedically relevant lectins in assays of increasing physiological relevance.

The emerging significance of recognition of cellular glycans by lectins for diverse aspects of pathophysiology is a strong incentive for considering development of bioactive and non-hydrolyzable glycoside derivatives, for example by introducing S/Se atoms and the disulfide group instead of oxygen into the glycosidic linkage. We report the synthesis of 12 bivalent thio-, disulfido- and selenoglycosides attached to benzene/naphthalene cores. They present galactose, for blocking a plant toxin, or lactose, the canonical ligand of adhesion/growth-regulatory galectins. Modeling reveals unrestrained flexibility and inter-headgroup distances too small to bridge two sites in the same lectin. Inhibitory activity was first detected by solid-phase assays using a surface-presented glycoprotein, with relative activity enhancements per sugar unit relative to free cognate sugar up to nearly 10fold. Inhibitory activity was also seen on lectin binding to surfaces of human carcinoma cells. In order to proceed to characterize this capacity in the tissue context monitoring of lectin binding in the presence of inhibitors was extended to sections of three types of murine organs as models. This procedure proved to be well-suited to determine relative activity levels of the glycocompounds to block binding of the toxin and different human galectins to natural glycoconjugates at different sites in sections. The results on most effective inhibition by two naphthalene-based disulfides and a selenide raise the perspective for broad applicability of the histochemical assay in testing glycoclusters that target biomedically relevant lectins.

[Hand hygiene technique assessment using electronic equipment in 26 Hungarian healthcare institutions]. / A kézhigiénés technika vizsgálata elektronikus ellenorzo berendezés segítségével 26 magyarországi betegellátó intézményben.

INTRODUCTION: Hand hygiene is probably the most effective tool of nosocomial infection prevention, however, proper feedback and control is needed to develop the individual hand hygiene practice. AIM: Assessing the efficiency of modern education tools, and digital demonstration and verification equipment during their wide-range deployment. METHOD: 1269 healthcare workers took part in a training organized by our team. The training included the assessment of the participants' hand hygiene technique to identify the most often missed areas. The hand hygiene technique was examined by a digital device. RESULTS: 33% of the participants disinfected their hands incorrectly. The most often missed sites are the fingertips (33% on the left hand, 37% on the right hand) and the thumbs (42% on the left hand, 32% on the right hand). CONCLUSION: The feedback has a fundamental role in the development of the hand hygiene technique. With the usage of electronic devices feedback can be provided efficiently and simply. Orv Hetil. 2017; 158(29): 1143-1148.

PSYCHE CPMG-HSQMBC: An NMR Spectroscopic Method for Precise and Simple Measurement of Long-Range Heteronuclear Coupling Constants.

Among the NMR spectroscopic parameters, long-range heteronuclear coupling constants convey invaluable information on torsion angles relevant to glycosidic linkages of carbohydrates. A broadband homonuclear decoupled PSYCHE CPMG-HSQMBC method for the precise and direct measurement of multiple-bond heteronuclear couplings is presented. The PSYCHE scheme built into the pulse sequence efficiently eliminates unwanted proton-proton splittings from the heteronuclear multiplets so that the desired heteronuclear couplings can be determined simply by measuring frequency differences between peak maxima of pure antiphase doublets. Moreover, PSYCHE CPMG-HSQMBC can provide significant improvement in sensitivity as compared to an earlier Zangger-Sterk-based method. Applications of the proposed pulse sequence are demonstrated for the extraction of (n)J((1)H,(77)Se) and (n)J((1)H,(13)C) values, respectively, in carbohydrates; further extensions can be envisioned in any J-based structural and conformational studies.

Precise measurement of long-range heteronuclear coupling constants by a novel broadband proton-proton-decoupled CPMG-HSQMBC method.

A broadband proton-proton-decoupled CPMG-HSQMBC method for the precise and direct measurement of long-range heteronuclear coupling constants is presented. The Zangger-Sterk-based homodecoupling scheme reported herein efficiently removes unwanted proton-proton splittings from the heteronuclear multiplets, so that the desired heteronuclear couplings can be determined simply by measuring frequency differences between singlet maxima in the resulting spectra. The proposed pseudo-1D/2D pulse sequences were tested on nucleotides, a metal complex incorporating P heterocycles, and diglycosyl (di)selenides, as well as on other carbohydrate derivatives, for the extraction of (n) J((1) H,(31) P), (n) J((1) H,(77) Se), and (n) J((1) H,(13) C) values, respectively.

Thio- and selenoglycosides as ligands for biomedically relevant lectins: valency-activity correlations for benzene-based dithiogalactoside clusters and first assessment for (di)selenodigalactosides.

Substitution of the oxygen atom in the glycosidic linkage by a disulfide bond or by selenium makes the resulting glycoside resistant to hydrolysis. To clarify the consequences for affinity to lectins we prepared benzene-based mono- to trivalent dithiogalactosides. Inhibitory capacity increased with valency for a plant toxin, the synthetic compounds potently blocking its binding to a lactose-presenting matrix and to cells. Human galectins were much less sensitive to the disulfides than the toxin. This differential response constitutes a beneficial effect to avoid cross-reactivity in vivo. Symmetrical selenodigalactoside and diselenodigalactoside were prepared and similarly tested. Both compounds proved rather equally bioactive for the toxin, graded activity was measured for human galectins. This result directs attention to further studies to relate Se-dependent alterations in bond angle and length as well as van der Waals radius to binding properties of selenoglycosides to biomedically relevant lectins.

Fluorescence of a Histidine-Modified Enhanced Green Fluorescent Protein (EGFP) Effectively Quenched by Copper(II) Ions. Part II. Molecular Determinants.

The histidine-modified EGFP was characterized as a sensing element that preferentially binds nanomolar concentrations of Cu(2+) in a reversible manner (Kd = 15 nM). This research aims to determine the causes of nanomolar-affinity of this mutant by investigating significant structural and energetic alterations of the chromophore in the presence of different copper ion concentrations. In order to reveal the unknown parts of the quenching mechanism we have elaborated a specific approach that combines theoretical and experimental techniques. The theoretical experiment included the modeling of potential distortions of the chromophores and the corresponding changes in energy using quantum mechanical calculations. Differences between the modeled energy profiles of planar and distorted conformations represented the energies of activation for the chromophore distortions. We found that some values of the experimental activation energies, which were derived from fluorescence lifetime decay analysis (ex: 470 nm, em: 507 nm), were consistent with the theoretical ones. Thus, it has been revealed similarity between the theoretical activation energy (50 kJmol(-1)) for 40° phenolate-ring distortion and the experimental activation energy (52.17 kJmol(-1)) required for histidine-modified EGFP saturation with copper. This chromophore conformation was further investigated and it has been found that the large decrease in fluorescence emission is attributed to the significant charge transfer over the molecule which triggers proton transfer thereby neutralizing the cromophore.

Selenosugars targeting the infective stage of Trypanosoma brucei with high selectivity.

Earlier evidences showed that diglycosyl diselenides are active against the infective stage of African trypanosomes (top hits IC50 0.5 and 1.5 µM) but poorly selective (selectivity index <10). Here we extended the study to 33 new seleno-glycoconjugates with the aim to improve potency and selectivity. Three selenoglycosides and three glycosyl selenenylsulfides displayed IC50 against bloodstream Trypanosoma brucei in the sub-µM range (IC50 0.35-0.77 µM) and four of them showed an improved selectivity (selectivity index >38-folds vs. murine and human macrohages). For the glycosyl selenylsulfides, the anti-trypanosomal activity was not significantly influenced by the nature of the moiety attached to the sulfur atom. Except for a quinoline-, and to a minor extent a nitro-derivative, the most selective hits induced a rapid (within 60 min) and marked perturbation of the LMWT-redox homeostasis. The formation of selenenylsulfide glycoconjugates with free thiols has been identified as a potential mechanism involved in this process.

ß-sheet structures and dimer models of the two major tyrocidines, antimicrobial peptides from Bacillus aneurinolyticus.

The structures of two major tyrocidines, antibiotic peptides from Bacillus aneurinolyticus, in an aqueous environment were studied using nuclear magnetic resonance spectroscopy, restrained molecular dynamics (MD), circular dichroism, and mass spectrometry. TrcA and TrcC formed ß-structures in an aqueous environment. Hydrophobic and hydrophilic residues were not totally separated into nonpolar and polar faces of the peptides, indicating that tyrocidines have low amphipathicity. In all the ß-structures, residues Trp(4)/Phe(4) and Orn(9) were on the same face. The ability of the peptides to form dimers in aqueous environment was studied by replica exchange MD simulations. Both peptides readily dimerize, and predominant complex structures were characterized through cluster analysis. The peptides formed dimers by either associating sideways or stacking on top of each other. Dimers formed through sideways association were mainly stabilized by hydrogen bonding, while the other dimers were stabilized by hydrophobic interactions. The ability of tyrocidine peptides to form different types of dimers with different orientations suggests that they can form larger aggregates, as well.

Aromatic glycosyl disulfide derivatives: evaluation of their inhibitory activities against Trypanosoma cruzi.

Aromatic oligovalent glycosyl disulfides and some diglycosyl disulfides were tested against three different Trypanosoma cruzi strains. Di-(ß-D-galactopyranosyl-dithiomethylene) benzenes 2b and 4b proved to be the most active derivatives against all three strains of cell culture-derived trypomastigotes with IC50 values ranging from 4 to 11 µM at 37 °C. The inhibitory activities were maintained, although somewhat lowered, at a temperature of 4 °C as well. Three further derivatives displayed similar activities against at least one of the three strains. Low cytotoxicities of the active compounds, tested on confluent HeLa, Vero and peritoneal macrophage cell cultures, resulted in significantly higher selectivity indices (SI) than that of the reference drug benznidazole. Remarkably, several molecules of the tested panel strongly inhibited the parasite release from T. cruzi infected HeLa cell cultures suggesting an effect against the intracellular development of T. cruzi amastigotes as well.

A large-scale assessment of hand hygiene quality and the effectiveness of the "WHO 6-steps".

BACKGROUND: Hand hygiene compliance is generally assessed by observation of adherence to the "WHO five moments" using numbers of opportunities as the denominator. The quality of the activity is usually not monitored since there is no established methodology for the routine assessment of hand hygiene technique. The aim of this study was to objectively assess hand rub coverage of staff using a novel imaging technology and to look for patterns and trends in missed areas after the use of WHO's 6 Step technique. METHODS: A hand hygiene education and assessment program targeted 5200 clinical staff over 7 days at the National University Hospital, Singapore. Participants in small groups were guided by professional trainers through 5 educational stations, which included technique-training and UV light assessment supported by digital photography of hands. Objective criteria for satisfactory hand hygiene quality were defined a priori. The database of images created during the assessment program was analyzed subsequently. Patterns of poor hand hygiene quality were identified and linked to staff demographic. RESULTS: Despite the assessment taking place immediately after the training, only 72% of staff achieved satisfactory coverage. Failure to adequately clean the dorsal and palmar aspects of the hand occurred in 24% and 18% of the instances, respectively. Fingertips were missed by 3.5% of subjects. The analysis based on 4642 records showed that nurses performed best (77% pass), and women performed better than men (75% vs. 62%, p<0.001). Further risk indicators have been identified regarding age and occupation. CONCLUSION: Ongoing education and training has a vital role in improving hand hygiene compliance and technique of clinical staff. Identification of typical sites of failure can help to develop improved training.

Fluorescence of a histidine-modified enhanced green fluorescent protein (EGFP) effectively quenched by copper(II) ions.

Two histidines were introduced by site-directed mutagenesis into the structure of Enhanced Green Fluorescent Protein, replacing the serine at position 202 and the glutamine at position 204 for increasing the sensitivity of the protein towards different metal ions by creating possible metal binding sites near the chromophore group. There is no appreciable difference between the absorbance and fluorescence spectra of the two proteins (wild type and the double-histidine mutant) indicating that the mutation does not change the environment of the fluorophore. Fluorescence quenching was measured at different pH (6.5-8) and temperatures (20-45 °C) varying the concentration of metal ions. Under optimal conditions (pH = 7.5, 20 °C) the mutant's Kd is 16 nM, it binds copper more than 200fold stronger than the wild type EGFP.

Resonance assignments of diastereotopic CH(2) protons in the anomeric side chain of selenoglycosides by means of (2) J(Se,H) spin-spin coupling constants.

Unambiguous resonance assignments of diastereotopic CH(2) protons in the anomeric side chain of nine alkyl- and aralkylselenoglycosides have been carried out on the basis of experimental CPMG-HSQMBC measurements and theoretical second order polarization propagator approach (SOPPA) calculations of geminal (77) Se-(1) H spin-spin coupling constants involving diastereotopic pro-R and pro-S protons. Theoretical conformational analyses have been performed at the MP2/6-311G** level. The conformational space of each of the selenoglycosides under study could be adequately described as a mixture of six interconverting conformers with the molar fractions depending on the nature of the side chain substituent at the selenium atom. The good agreement observed between measured and the weighted conformational averaged values of the calculated coupling constants provides a basis for reliable diastereotopic assignments in this type of carbohydrate structures.